Association Between Familial Hypercholesterolemia and Prevalence of Type 2 Diabetes Mellitus

Supplementary Online Content

Besseling J, Kastelein JJP, Defesche JC, Hutten BA, Hovingh GK. Association between familial hypercholesterolemia and prevalence of type 2 diabetes mellitus. JAMA. doi:10.1001/jama.2015.1206

eTable 1. Non-Deleterious FH Mutations in the Netherlands eTable 2. Annual Number of Detected HeFH Patients eTable 3. Specification of Type and Daily Dose of Statin in Statin Users eTable 4. Stratified Analysis for the Associations Between the Presence of Type 2 DM and Familial Hypercholesterolemia eAppendix 1. Sensitivity Analyses: Definition of Type 2 DM and Odds Ratios in Multiple Imputation Data eTable 5. Multiple Imputation—Associations Between the Presence of Type 2 DM and Familial Hypercholesterolemia eAppendix 2. BMI as a Mediator for the Effect of Familial Hypercholesterolemia on Type 2 DM and Results eTable 6. BMI as Mediator of Association Between FH and Type 2 DM eAppendix 3. References

This supplementary material has been provided by the authors to give readers additional information about their work.

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 1. Non-Deleterious FH Mutations in the Netherlands

Name mutation Reference (cDNA) c.1063A>G Fouchier SW, Defesche JC, Umans-Eckenhausen MW, Kastelein JP. The molecular basis of familial hypercholesterolemia in The Netherlands. Hum Genet. 2001 Dec;109(6):602-15. c.1085A>C Fouchier SW, Defesche JC, Umans-Eckenhausen MW, Kastelein JP. The molecular basis of familial hypercholesterolemia in The Netherlands. Hum Genet. 2001 Dec;109(6):602-15. c.108C>A Fouchier SW, Defesche JC, Umans-Eckenhausen MW, Kastelein JP. The molecular basis of familial hypercholesterolemia in The Netherlands. Hum Genet. 2001 Dec;109(6):602-15. c.1171G>A Weiss N, Binder G, Keller C. Heterozygosity for the missense mutation Ala370-->Thr in exon 8 of the low density lipoprotein receptor gene does not cause hypercholesterolemia. Eur J Med Res. 1998 Feb 21;3(1-2):20-4. c.1187-9G>A Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.12154T>C Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.-127G>C Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.12940A>G Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.13130T>C Liyanage KE, Hooper AJ, Defesche JC, Burnett JR, van Bockxmeer FM. High-resolution melting analysis for detection of familial ligand-defective apolipoprotein B-100 mutations. Ann Clin Biochem. 2008 Mar;45(Pt c.131810T>C Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.13288T>A Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.148G>T Jensen HK et al. An alanine29-serine variant in exon 2 of the low density lipoprotein receptor gene: no association with hypercholesterolemia. Clin Genet. 1994 Aug;46(2):214-5. c.1658A>G Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.1690A>C Tricot-Guerber F et al. Identification of a mutation, N543H, in exon 11 of the LDLR gene in a French family with FH. Hum Mut. 1995;6(1):87-8. c.1761C>G Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.1816G>T Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.1867A>G Chang JH et al. Identi fication and characterization of LDL receptor gene mutations in hyperlipidemic Chinese. J Lipid Res. 2003 Oct;44(10):1850-8. c.1876G>A Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005

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Name mutation Reference (cDNA)

c.2140+5G->A Mozas P, Cenarro A, Civeira F, Castillo S, Ros E, Pocovi M. Mutation analysis in 36 unrelated Spanish subjects with familial hypercholesterolemia: identification of 3 novel mutations in the LDL c.2177C>T Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.2231G>A Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.2242G>A Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.2269C>A Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.2282C>T Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.2297C>T Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.2324T>C Polyphen and SIFT test in lab of Experimental Vascular Medicine, AMC c.2479G>A Lombardi MP, Redeker EJ, Defesche JC, Kamerling SW, Trip MD, Mannens MM, Havekes LM, Kastelein JJ. Molecular genetic testing for familial hypercholesterolemia: spectrum of LDL receptor gene mutations in The c.757C>T Fouchier SW, Defesche JC, Umans -Eckenhausen MW, Kastelein JP. The molecular basis of familial hypercholesterolemia in The Netherlands. Hum Genet. 2001 Dec;109(6):602-15. c.829G>A Ekstrom U, Abrahamson M, Sveger T, Sun XM, Soutar AK, Expression of an LDL receptor allele with two different mutations (E256K and I402T). Nilsson-Ehle P. Mol Pathol. 2000; 53: 31-36. c.932A>G Fouchier SW, Defesche JC, Umans-Eckenhausen MW, Kastelein JP. The molecular basis of familial hypercholesterolemia in The Netherlands. Hum Genet. 2001 Dec;109(6):602-15. c.939C>A Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 c.941-4 G>A Fouchier SW, Kastelein JJ, Defesche JC. Update of the molecular basis of familial hypercholesterolemia in The Netherlands. Hum Mut. 2005 FH: familial hypercholesterolemia

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 2. Annual Number of Detected HeFH Patients

HeFH patients detected - no. 1994 208 1995 141 1996 298 1997 536 1998 1,015 1999 864 2000 826 2001 544 2002 936 2003 1,524 2004 1,992 2005 2,369 2006 2,402 2007 2,174 2008 1,891 2009 1,620 2010 1,752 2011 1,583 2012 1,481 2013 885 HeFH: heterozygous familial hypercholesterolemia; no.: number Information on detection year was missing in 96 (0.38%) HeFH patients

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 3. Specification of Type and Daily Dose of Statin in Statin Users

HeFH patients Unaffected relatives (n = 7,290) (n = 3,431) Atorvastatin 10 mg 209 (2.9%) 236 (6.9%) 20 mg 470 (6.4%) 279 (8.1%) 40 mg 1,673 (22.9%) 400 (11.7%) 80 mg 353 (4.8%) 31 (0.9%) Fluvastatin 10 mg 4 (0.1%) 0 (0%) 20 mg 7 (0.1%) 12 (0.3%) 40 mg 40 (0.5%) 31 (0.9%) 80 mg 22 (0.3%) 15 (0.4%) Pravastatin 10 mg 24 (0.3%) 30 (0.9%) 20 mg 84 (1.2%) 67 (2.0%) 40 mg 297 (4.1%) 250 (7.3%) 80 mg 3 (<0.1%) 3 (0.1%) Rosuvastatin 10 mg 512 (7%) 284 (8.3%) 20 mg 344 (4.7%) 61 (1.8%) 40 mg 277 (3.8%) 29 (0.8%) Simvastatin 10 mg 180 (2.5%) 212 (6.2%) 20 mg 622 (8.5%) 536 (15.6%) 40 mg 2,076 (28.5%) 943 (27.5%) 80 mg 93 (1.3%) 12 (0.3%) HeFH: heterozygous familial hypercholesterolemia; mg: milligram

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 4. Stratified Analysis for the Associations Between the Presence of Type 2 DM and Familial Hypercholesterolemia

Odds 95% CI p-value Observed prevalence type 2 DM - % (95% CI); no. Sample size ratio Non-FH FH Non-FH FH Statin use Use versus no use Unadjusted 38,183 25,137 Non-statin users 0.32 0.26 - 0.41 <0.001 1.53 (1.40 - 1.65); 530 0.49 (0.38 - 0.59); 87 34,752 17,866 Statin users 0.26 0.22 - 0.30 <0.001 17.17 (15.91 - 18.43); 589 4.86 (4.36 - 5.35); 353 3,431 7,271 Adjusted* 24,898 12,300 Non-statin users 0.66 0.47 - 0.95 0.023 1.45 (1.30 - 1.61); 322 0.5 (0.34 - 0.65); 38 22,135 7,656 Statin users 0.44 0.37 - 0.53 <0.001 17.73 (16.31 - 19.16); 490 5.77 (5.10 - 6.44); 268 2,763 4,644 Low, moderate and high-intensity statin dose† Unadjusted 38,183 25,137 Low intensity 0.18 0.10 - 0.33 <0.001 14.09 (10.84 - 17.34); 62 2.92 (1.47 - 4.38); 15 440 513 Moderate intensity 0.21 0.18 - 0.25 <0.001 17.39 (15.95 - 18.83); 462 4.04 (3.48 - 4.6); 192 2,657 4,754 High intensity 0.33 0.23 - 0.46 <0.001 19.35 (15.12 - 23.57); 65 7.28 (6.14 - 8.42); 146 336 2,006 Adjusted * 24,898 12,300 Low intensity 0.29 0.13 - 0.68 0.004 13.62 (10.11 - 17.13); 50 3.49 (1.46 - 5.52); 11 367 315 Moderate intensity 0.39 0.32 - 0.49 <0.001 18.14 (16.50 - 19.78); 385 5.16 (4.34 - 5.98); 145 2,122 2,810 High intensity 0.41 0.28 - 0.61 <0.001 19.93 (15.21 - 24.64); 55 7.36 (6.05 - 8.68); 112 276 1,521 Cardiovascular disease Unadjusted 38,183 25,137 No history of CVD 0.50 0.44 - 0.57 <0.001 2.35 (2.20 - 2.51); 853 1.15 (1.01 - 1.28); 267 36,267 23,273 History of CVD 0.65 0.53 - 0.80 <0.001 13.88 (12.33 - 15.43); 266 9.28 (7.96 - 10.60); 173 1,916 1,864 Adjusted§ 24,898 12,300

Downloaded From: https://jamanetwork.com/ on 09/28/2021 ...continued eTable 4. Odds 95% CI p-value Observed prevalence type 2 DM - % (95% CI); no. Sample size ratio Non-FH FH Non-FH FH No history of CVD 0.40 0.32 - 0.49 <0.001 2.65 (2.45 - 2.86); 626 1.70 (1.46 - 1.94); 191 23,599 11,209 History of CVD 0.74 0.57 - 0.96 0.021 14.32 (12.41 - 16.22); 186 10.54 (8.72 - 12.36); 115 1,299 1,091 Smoking Unadjusted 38,132 24,886 Non-smokers 0.58 0.5 - 0.67 <0.001 2.59 (2.4 - 2.78); 698 1.47 (1.31 - 1.64); 294 26,910 19,969 Smokers 0.76 0.63 - 0.93 0.007 3.7 0(3.35 - 4.05); 415 2.75 (2.29 - 3.2); 135 11,222 4,917 Adjusted║ 24,898 12,300 Non-smokers 0.47 0.38 - 0.57 <0.001 2.89 (2.63 - 3.14); 487 2.17 (1.87 - 2.47); 195 16,880 8,973 Smokers 0.53 0.40 - 0.70 <0.001 4.05 (3.62 - 4.49); 325 3.34 (2.73 - 3.95); 111 8,018 3,327 Age-subgroups Unadjusted 38,163 25,111 <35 years 0.57 0.10 - 3.13 0.52 0.03 (0.00 - 0.06); 4 0.02 (-0.01 - 0.04); 2 12,893 11,256 ≥35 years 0.72 0.64 - 0.80 <0.001 4.41 (4.16 - 4.67); 1,115 3.16 (2.87 - 3.45); 438 25,270 13,855 Adjusted¶ 24,898 12,300 <35 years 0.50 0.05 - 4.54 0.536 0.03 (0.00 - 0.06); 4 0.02 (-0.01 - 0.04); 2 7,798 5,694 ≥35 years 0.48 0.41 - 0.57 <0.001 4.41 (4.16 - 4.67); 1,115 3.16 (2.87 - 3.45); 438 17,100 6,606 Periods of the screening program Unadjusted 38,183 25,137 1994-1998 0.40 0.23 - 0.72 0.002 1.54 (1.11 - 1.97); 49 1.54 (1.11 - 1.97); 49 3,181 2,198 1999-2003 0.59 0.45 - 0.78 <0.001 2.63 (2.27 - 2.99); 198 2.63 (2.27 - 2.99); 198 7,524 4,694 2004-2008 0.61 0.52 - 0.73 <0.001 3.24 (2.96 - 3.51); 515 3.24 (2.96 - 3.51); 515 15,916 10,828 2009-2013 0.67 0.55 - 0.82 <0.001 3.13 (2.81 - 3.45); 357 3.13 (2.81 - 3.45); 357 11,400 7,321 Adjusted¶ 24,898 12,300 1994-1998 (too few observations) 0.00 (0.00 - 0.00); 0 0.00 (0.00 - 0.00); 0 20 23

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Odds 95% CI p-value Observed prevalence type 2 DM - % (95% CI); no. Sample size ratio Non-FH FH Non-FH FH 1999-2003 0.58 0.30 - 1.14 0.115 4.33 (3.25 - 5.41); 59 4.33 (3.25 - 5.41); 59 1,363 610 2004-2008 0.43 0.34 - 0.53 <0.001 3.18 (2.89 - 3.47); 450 3.18 (2.89 - 3.47); 450 14,140 6,897 2009-2013 0.54 0.41 - 0.70 <0.001 3.23 (2.87 - 3.59); 303 3.23 (2.87 - 3.59); 303 9,375 4,762 Index patients versus non-index patients Unadjusted 38,183 25,137 Index patients 0.24 0.07 - 0.84 0.025 1.38 (-0.17 - 2.94); 3 0.33 (0.16 - 0.51); 14 217 4,189 Non index 0.72 0.64 - 0.81 <0.001 2.94 (2.77 - 3.11); 1,116 2.03 (1.84 - 2.22); 426 37,966 20,948 Adjusted ¶ 24,898 12,300 Index patients (too few observations) 0.00 (0.00 - 0.00); 0 4.59 (0.66 - 8.51); 5 15 109 Non index 0.48 0.40 - 0.56 <0.001 3.26 (3.04 - 3.48); 812 2.47 (2.19 - 2.74); 301 24,883 12,191 CI: confidence interval; CVD: cardiovascular disease; DM: diabetes mellitus; FH: familial hypercholesterolemia * adjusted for age, body mass index, high-density lipoprotein cholesterol, triglycerides (log transformed), smoking, history of CVD and family relations. † low intensity statin is defined as: cerivastatin 0,1 mg or 0,4 mg, fluvastatin 20 or 40 mg, lovastatin 20 mg, pitavastatin 1 mg, pravastatin 10 or 20 mg or simvastatin 10 mg; moderate intensity statin is defined as: atorvastatin 10 or 20 mg, fluvastatin 80 mg, lovastatin 40 mg, pitavastatin 2 or 4 mg, rosuvastatin 5 or 10 mg or simvastatin 20 or 40 mg; high intensity statin is defined as: atorvastatin 40 or 80 mg, rosuvastatin 20 or 40 mg or simvastatin 80 mg (in line with current AHA guidelines).1 ‡ CVD is defined as myocardial infarction, coronary artery bypass graft, percutaneous transluminal angioplasty or ischemic cerebrovascular accident. § adjusted for age, body mass index, high-density lipoprotein cholesterol, triglycerides (log transformed), smoking, statin use and family relations. ║ adjusted for age, body mass index, high-density lipoprotein cholesterol, triglycerides (log transformed), history of CVD, statin use and family relations. ¶ adjusted for age, body mass index, high-density lipoprotein cholesterol, triglycerides (log transformed), smoking, history of CVD, statin use and family relations.

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eAppendix 1. Sensitivity Analyses: Definition of Type 2 DM and Odds Ratios in Multiple Imputation Data

Definition of type 2 diabetes mellitus (DM)

The type of diabetes was not specified in the questionnaire and we selected those patients that were highly likely to have type 1 diabetes mellitus (DM), based on an age below 30 or age below 40 and use of insulin and these patients were classified as non type 2 DM. This method might have influenced the association we found between type 2 DM and familial hypercholesterolemia. Therefore, we tested this association as well in two scenario’s in which type 2 DM was defined otherwise.

First, we assumed that everyone that reported to have diabetes on the questionnaire had type 2 DM. In this case, 486/25,137 (1.93%) patients with familial hypercholesterolemia had type 2 DM, compared to 1,184/38,183 (3,10%) of unaffected relatives (p<0.001). The unadjusted odds ratio (OR) for type 2 DM in familial hypercholesterolemia was 0.65 (95% CI: 0.61 - 0.68; p<0.001). Adjusted for age, body mass index (BMI), high-density lipoprotein cholesterol (HDL-C), triglycerides (log transformed), use of statins, smoking, and cardiovascular disease, the odds ratio (OR) was 0.48 (95% CI: 0.45 - 0.53; p<0.001)

Next, we explored the worst case scenario, in which all familial hypercholesterolemia patients that we considered to have type 1 DM, actually did have type 2 DM, while the unaffected relatives that we considered to have type 1 DM truly had type 1 DM. If our selection of type 1 DM patients was wrong and led to an overestimation of the difference between patients with familial hypercholesterolemia and unaffected relatives regarding type 2 DM prevalence, this scenario will remove this attribution bias. All patients with familial hypercholesterolemia that were allocated to have type 1 DM, were transferred to the type 2 DM group. The prevalence of type 2 DM in this scenario was 1.93% (486/25,137) in familial hypercholesterolemia patients and 2.93% (1,119/38,183) in unaffected relatives (P<0.001). The unadjusted and adjusted OR for type 2 DM in familial hypercholesterolemia in this scenario were 0.68 (95%CI: 0.65 - 0.72; p<0.001) and 0.52 (95%CI: 0.48 - 0.57; p<0.001), respectively.

Odds ratios in multiple imputation data

We performed a sensitivity analysis to test the assumption that missing data was missing completely at random. To do so, we repeated the multivariable logistic regression analyses to determine the association between familial hypercholesterolemia in five multiple imputation datasets. All subjects heterozygous familial hypercholesterolemia patients (25,137) and unaffected relatives (n = 38,183) were eligible for analysis. Missing values were imputed using the

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aregImpute algorithm.2 Missing values were imputed based on all available clinical parameters in the dataset, including the outcome variable.

The unadjusted prevalence of type 2 diabetes mellitus (DM) in familial hypercholesterolemia patients and unaffected relatives was 1.75 and 2.93%, respectively (p=X.XXX). In Table 5 we provide the odds ratio’s for the association between type 2 DM versus familial hypercholesterolemia and the different subgroups. There were no differences compared with the results of the multivariable logistic regression analyses in the complete case analysis (table 2 of the manuscript). Overall, the odds ratios tended to be very slightly lower in the multiple imputation analysis, but we deem these differences not to be significant.

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 5. Multiple Imputation—Associations Between the Presence of Type 2 DM and Familial Hypercholesterolemia

Odds ratio for type 95% CI 2 DM FH - unadjusted 0.62 0.55 - 0.69 FH - adjusted* 0.45 0.39 - 0.52 Affected gene* 0.65† 0.61 - 0.70 No mutation‡ 1.00 - APOB mutations 0.60 0.46 - 0.78 LDLR mutations 0.42 0.37 - 0.49 Type of LDL-receptor mutation* 0.58† 0.53 - 0.64 No mutation‡ 1.00 - Receptor-defective 0.49 0.41 - 0.58 Receptor-negative 0.39 0.31 - 0.48 APOB: apolipoprotein B; FH: familial hypercholesterolemia; LDLR: low-density lipoprotein receptor; DM: diabetes mellitus. * adjusted for age, body mass index, high-density lipoprotein cholesterol, triglycerides (log transformed), use of statins, smoking, cardiovascular disease, and family relations † test for linear trend ‡ reference category

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eAppendix 2. BMI as a Mediator for the Effect of Familial Hypercholesterolemia on Type 2 DM and Results

The study by Swerdlow suggests that bodyweight might be a mediator on the causal pathway between both HMGCR SNPs, as well as statin use, with type 2 DM.3 Also in our study, BMI might possibly be a mediator between familial hypercholesterolemia and type 2 DM. We explored this by the method of Baron and Kenny.4 It has to be stated upfront however, that using this approach, we cannot distinguish between bodyweight acting as a mediator or as a confounder. This is due to the cross-sectional nature of our data and the subsequent lack of information on the temporal relationship between bodyweight and type 2 DM, which is essential for the decision whether a variable is a mediator or a confounder.

Three steps are necessary to identify a potential mediator: 1) establish the association between exposure and outcome; 2) establish the association between exposure and the potential mediator; 3) explore whether the magnitude of the association between the exposure and outcome is influenced by the potential mediator. We used univariable and multivariable logistic and linear regression modeling to perform these three steps. The generalized estimating equation with exchangeable correlation structure was used to adjust for family relations within the data. We used body mass index (BMI) as an indicator of bodyweight. The exposure, outcome and potential mediator of interest were familial hypercholesterolemia, type 2 DM and BMI, respectively.

Results

The beta-coefficients and corresponding p-values of the three steps are summarized in Table 6. Familial hypercholesterolemia was significantly associated with both type 2 DM (step 1) as well as BMI (step 2). The beta-coefficient of the association between familial hypercholesterolemia and type 2 DM was closer to zero (0) when BMI was added to the regression model. This indicates that BMI might be a mediator on the association between familial hypercholesterolemia. However, since we do not know the temporal relationship between BMI and type 2 DM, it is also possible that BMI is only a confounder.

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eTable 6. BMI as Mediator of Association Between FH and Type 2 DM

Beta-coefficient p-value Step 1: association FH and type 2 DM -0.486 <0.001 Step 2: association FH and BMI -0.489 <0.001 Step 3: association FH and type 2 DM, adjusted for BMI -0.197 0.002 BMI: body mass index; FH: familial hypercholesterolemia; DM: diabetes mellitus

Downloaded From: https://jamanetwork.com/ on 09/28/2021 eAppendix 3. References

1 Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2013; 63: 2889–934.

2 Harrel FE. The “Hmisc” Package, version 3.14-4. 2014. http://cran.r- project.org/web/packages/Hmisc/Hmisc.pdf (accessed 23 Jul2014).

3 Swerdlow DI, Preiss D, Kuchenbaecker KB, et al. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials [published online September 24, 2014]. Lancet 2014; : 1–11.

4 Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986; 51: 1173–82.

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