The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Variation in PCSK9 and HMGCR and Risk of Cardiovascular Disease and Diabetes
Open accessAbstract
BACKGROUND: Pharmacologic inhibitors of proprotein convertase subtilisin-kexin type 9 (PCSK9) are being evaluated in clinical trials for the treatment of cardiovascular disease. The effect of lowering low-density lipoprotein (LDL) cholesterol levels by inhibiting PCSK9 on the risk of cardiovascular events or diabetes is unknown. METHODS: We used genetic scores consisting of independently inherited variants in the genes encoding PCSK9 and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR; the target of statins) as instruments to randomly assign 112,772 participants from 14 studies, with 14,120 cardiovascular events and 10,635 cases of diabetes, to groups according to the number of LDL cholesterol-lowering alleles that they had inherited. We compared the effects of lower LDL cholesterol levels that were mediated by variants in PCSK9, HMGCR, or both on the risk of cardiovascular events and the risk of diabetes. RESULTS: Variants in PCSK9 and HMGCR were associated with nearly identical protective effects on the risk of cardiovascular events per decrease of 10 mg per deciliter (0.26 mmol per liter) in the LDL cholesterol level: odds ratio for cardiovascular events, 0.81 (95% confidence interval [CI], 0.74 to 0.89) for PCSK9 and 0.81 (95% CI, 0.72 to 0.90) for HMGCR. Variants in these two genes were also associated with very similar effects on the risk of diabetes: odds ratio for each 10 mg per deciliter decrease in LDL cholesterol, 1.11 (95% CI, 1.04 to 1.19) for PCSK9 and 1.13 (95% CI, 1.06 to 1.20) for HMGCR. The increased risk of diabetes was limited to persons with impaired fasting glucose levels for both scores and was lower in magnitude than the protective effect against cardiovascular events. When present together, PCSK9 and HMGCR variants had additive effects on the risk of both cardiovascular events and diabetes. CONCLUSIONS: In this study, variants in PCSK9 had approximately the same effect as variants in HMGCR on the risk of cardiovascular events and diabetes per unit decrease in the LDL cholesterol level. The effects of these variants were independent and additive. (Funded by the Medical Research Council and the National Heart, Lung, and Blood Institute.).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“As an extension of MR, drug target MR has emerged as efficient way to estimate therapeutic potential by using genetic variants in genes encoding drug targets (referred to as cis variants) to mimic the actions of drugs.”
From Genetic insights into causal effects of lipids and lipid-modifying targets on calcific aortic valve stenosis: a Mendelian randomized study (2025) · cites this paper as [13]
The cited source says what the claim attributes to it.
In the citing paper
“Likewise, these observations are supported by data from a recent mendelian randomization study in which variants in PCSK9 and variants in HMGCR were associated with nearly identical lower risks of cardiovascular events per unit reduction in LDL cholesterol.29”
From Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease (2017) · cites this paper as [29]
In the citing paper
“mendelian randomisation studies 8,[19][20][21] of genetic polymorphisms that mimic the effects of statins, ezetimibe, or PCSK9 inhibitors suggest that lifelong reductions in LDL cholesterol, irrespective of the mechanism, are associated with an increased risk of diabetes.”
In the citing paper
“Mendelian randomisation analyses 8,20,21 have shown that genetically determined loss of function of PCSK9 is associated with an increased risk of incident diabetes, but clinical trials of PCSK9 inhibitors have shown no such effect.9”
In the citing paper
“Therefore, the clinical benefit of therapies that lower LDL-C by reducing LDL particle mass will be proportional to the absolute reduction in LDLC, because-on average-the reduction in LDL-C and LDL particles will be concordant [34,50,54,55].”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [54]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816
Cholesterol Treatment Trialists' (CTT) Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)61350-5 · Cited by 6,550
Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N., & Davey Smith, G. (2008) · Statistics in Medicine · doi:10.1002/sim.3034 · Cited by 4,618
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Ezetimibe Added to Statin Therapy after Acute Coronary Syndromes
Cannon, C. P., Blazing, M. A., Giugliano, R. P., McCagg, A., White, J. A., Theroux, P., Darius, H., Lewis, B. S., Ophuis, T. O., Jukema, J. W., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1410489 · Cited by 4,487
Self-citationMulti-Ethnic Study of Atherosclerosis: Objectives and Design
Bild, D. E. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf113 · Cited by 3,942
Sequence Variations in PCSK9, Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983
A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447
Efficacy and Safety of Alirocumab in Reducing Lipids and Cardiovascular Events
Robinson, J. G., Farnier, M., Krempf, M., Bergeron, J., Luc, G., Averna, M., Stroes, E. S., Langslet, G., Raal, F. J., El Shahawy, M., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501031 · Cited by 2,296
Self-citation
Cited by
Sorted by citations
Items 701–747 of 747
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.24873194
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26656576
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26656582
Borges, M. C., Haycock, P. C., Zheng, J., Hemani, G., Holmes, M. V., Smith, G. D., Hingorani, A. D., & Lawlor, D. A. (2022) · Figshare · doi:10.6084/m9.figshare.20057442
Atreya, M. R., Cvijanovich, N. Z., Fitzgerald, J. C., Weiss, S. L., Bigham, M. T., Jain, P. N., Schwarz, A. J., Lutfi, R., Nowak, J. E., Allen, G. L., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26599705
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26656579
Additional file 1 of Impact of PCSK9 inhibitors in glycaemic control and new-onset diabetes
González-Lleó, A. M., Sánchez-Hernández, R. M., Plana, N., Ibarretxe, D., Rehues, P., Ribalta, J., Llop, D., Wägner, A. M., Masana, L., & Boronat, M. (2024) · Figshare · doi:10.6084/m9.figshare.24940593
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26656594
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26656585
Atreya, M. R., Cvijanovich, N. Z., Fitzgerald, J. C., Weiss, S. L., Bigham, M. T., Jain, P. N., Schwarz, A. J., Lutfi, R., Nowak, J. E., Allen, G. L., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26599708
Borges, M. C., Haycock, P. C., Zheng, J., Hemani, G., Holmes, M. V., Smith, G. D., Hingorani, A. D., & Lawlor, D. A. (2022) · Figshare · doi:10.6084/m9.figshare.20057445
Hong, S.-J., Lee, Y.-J., Kang, W. C., Hong, B.-K., Lee, J.-Y., Lee, J.-B., Yang, T.-H., Yoon, J., Lee, S.-J., Ahn, C.-M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26517826
Choi, J. Y., Choi, C. U., Choi, B. G., Park, Y., Kang, D. O., Jang, W. Y., Kim, W., Na, J. O., Kim, J. W., Kim, E. J., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13719390
Huang, J., 顾俊旭, Wang, K., Zhang, A.-M., Hong, T.-T., Li, S.-S., Yao, X.-Q., Yang, M., Yin, Y., Zhang, N., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24873075
Wang, K., Shi, M., Huang, C., Fan, B., Luk, A. O. Y., Kong, A. P. S., Ronald, C. W., Chan, J. T. S., & Chow, E. (2022) · Figshare · doi:10.6084/m9.figshare.21200749
Wu, Z., Huang, Z., Lichtenstein, A. H., Liu, Y., Chen, S., Jin, Y., Na, M., Bao, L., Wu, S., & Gao, X. (2021) · Figshare · doi:10.6084/m9.figshare.14788405
Atreya, M. R., Cvijanovich, N. Z., Fitzgerald, J. C., Weiss, S. L., Bigham, M. T., Jain, P. N., Schwarz, A. J., Lutfi, R., Nowak, J. E., Allen, G. L., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26599702
Additional file 2 of A phenome-wide association study of genetically mimicked statins
Li, S., & Schooling, C. M. (2021) · Figshare · doi:10.6084/m9.figshare.14880635
Muzammil, K., Hooshiar, M. H., Varmazyar, S., Omar, T. M., Karim, M. M., Aadi, S., Kalavi, S., & Yasamineh, S. (2024) · Figshare · doi:10.6084/m9.figshare.26697524
Luo, S., Lam, H. S., Chan, Y. H., Tang, C. S. M., He, B., Kwok, M. K., Leung, G. M., Schooling, C. M., & Au Yeung, S. L. (2024) · Figshare · doi:10.6084/m9.figshare.24465344
Xiao, W., Li, Y., Zhuang, Z., Song, Z., Wang, W., Huang, N., Dong, X. Y., Jia, J., Liu, Z., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25963123
The impact of anti-gout medications on eight cardiovascular diseases: a Mendelian randomized study
Peng, P., Wang, J., Huang, M., Hu, C., Liu, S., Liu, J., Cai, J., Wei, X., & Sun, H. (2026) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-025-03984-7
Adeeb, N. B. A., Bakar, R. A., Daud, N. A. A., Al-Ani, H. A., Noor, D. A. M., Ahmad, I., & Zilfalil, B. A. (2024) · Malaysian Journal of Medicine and Health Sciences · doi:10.47836/mjmhs.20.3.43
Salari, S., Moeinipour, Y., Elahabadi, G., Moeinipour, A., & Mohammadpour, A. H. (2026) · Behavioural Pharmacology · doi:10.1097/fbp.0000000000000872
Berrandou, T.-E. (2026) · Annales d Endocrinologie · doi:10.1016/j.ando.2026.102509
Etude du rôle de la protéine PCSK9 dans la cellule bêta pancréatique
Saitoski, K. (2021) · theses.fr (ABES) · doi:10.70675/58b8c006z57e2z47a2zbb66z1e469544d6a5
Le rôle du récepteur aux LDL et de PCSK9 dans le diabète de type 2
Ramin‐Mangata, S. (2020) · theses.fr (ABES) · doi:10.70675/26622ba5zb0fcz4d30za6e6z5c95a0b5a33d
HMGCR genetic variation and risk of new-onset type 2 diabetes in statin users
Albawa’neh, A. S., Alqasrawi, M. N., Al-Mahayri, Z. N., Marzouka, N., Dabaghie, L., Hamza, D., Khasawneh, L. Q., Misra, V., Ouda, H. Z., & Ali, B. R. (2026) · Human Genomics · doi:10.1186/s40246-026-00962-7
Xiang, L., Sun, J., Yang, L., Luo, Y., Wang, Y., Chen, K., & Meng, X. (2026) · Biology Direct · doi:10.1186/s13062-026-00769-5
Sánchez‐Quesada, J. L., & Pérez, A. (2026) · Frontiers in Endocrinology · doi:10.3389/fendo.2026.1813342
Ray, D., Bate, T., O’Mara, T. A., Sasieni, P. D., Gunter, M. J., Martin, R. M., Smith‐Byrne, K., Haycock, P., & Yarmolinsky, J. (2026) · medRxiv · doi:10.64898/2026.04.28.26351848
Bhatti, M. I., Safiullah, M., Qadri, M., Butt, A. A., & Ahmed, R. (2026) · American Journal of Cardiovascular Drugs · doi:10.1007/s40256-026-00797-6
Tian, H., Kamineni, M., Truong, B. M. T., Raghu, V. K., Dron, J. S., Hornsby, W., Koyama, S., Yu, Z., & Natarajan, P. (2026) · medRxiv · doi:10.64898/2026.05.19.26353617
Takov, K., Depuydt, M. A. C., Stevens, C. A. T., Fogacci, F., Vico, T. A., Dalt, L. D., Mußbacher, M., Oleksiak, A., Hendrikx, T., Cutruzzolà, A., et al. (2026) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2026.120787
Liu, M., Zhang, X., Feng, M., He, Q., & Feng, Z. (2026) · PLoS ONE · doi:10.1371/journal.pone.0350294
An HMMR-derived SHBG genetic score predicts lower type 2 diabetes risk
Zhuang, J., Ku, C., Wu, M., Xie, J., Li, C., Qin, Z., Abdrakhmanov, A. S., Zheng, J., & Zhang, Y. (2026) · Regenesis repair rehabilitation. · doi:10.1016/j.rerere.2026.05.001
SAIMSARA (2026) · SAIMSARA Journal · doi:10.62487/saimsarac25dcb0d
Inclisiran—will it fulfill its promise?
Zadeh, S. S. T., Fogacci, F., & Hadaegh, F. (2026) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2026.104848
Baya, N. A., Lassen, F. H., Hill, B., Venkatesh, S. S., Currant, H., Lindgren, C. M., & Palmer, D. S. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.05.013 · Cited by 2
Mendelian randomization applied to cancer: What it has and has not achieved
Smith-Byrne, K., Breeur, M., Yarmolinsky, J., & Smith, G. D. (2026) · Cancer Epidemiology · doi:10.1016/j.canep.2026.103182
Bhak, Y., Helmy, A. E., Needham, E., Menon, D. K., Warrier, V., Samanta, R. J., Åkerlund, C. A. I., Amrein, K., Anđelić, N., Andreassen, L., et al. (2026) · Neurocritical Care · doi:10.1007/s12028-026-02575-3
Precision genome editing strategies for enduring lipid lowering in atherosclerosis
Chowdhury, D., Singh, N., Garai, S., Pandey, D. P., & Bodakhe, S. H. (2026) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2026.179312
Wang, S., Tang, Y., Sui, Y., Zhao, H., Khan, A., Yin, W., Chen, Q., Xu, T., Liu, Z., Zhang, Z., et al. (2026) · Nature Cardiovascular Research · doi:10.1038/s44161-026-00865-9 · Cited by 1
Kalafati, I. P., Kyriazopoulou-Korovesi, A.-A., Nikolaou, E., Papaioannou, M., Konstantaki, C., Angelidakis, L., Gianniou, D. D., Mikropoulou, E. V., Γιαρδόγλου, Π., Valakos, D., et al. (2026) · Pharmacology Research & Perspectives · doi:10.1002/prp2.70322
Decoding Atrial Fibrillation Heterogeneity
Yoshimura, H., Chung, S., Lip, G. Y. H., Schmidt, A. F., & Providencia, R. A. (2026) · JACC Advances · doi:10.1016/j.jacadv.2026.103352
PCSK9 in the Immunometabolism of Type 2 Diabetes
Villari, P., & Labate, A. M. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27219723
Metadata
- Authors
- Ference, B. A., Robinson, J. G., Brook, R. D., Catapano, A. L., Chapman, M. J., Neff, D. R., Voros, S., Giugliano, R. P., Davey Smith, G., Fazio, S., & Sabatine, M. S.
- Affiliations
- University of Iowa (US)
- ORCID
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2016-12
- Volume
- 375
- Issue
- 22
- Pages
- 2144-2153
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2557654447
- Cited by
- 743
- References
- 39
- Citations by year
- 2026: 38 · 2025: 55 · 2024: 77 · 2023: 64 · 2022: 74 · 2021: 76 · 2020: 75 · 2019: 86 · 2018: 97 · 2017: 92 · 2016: 8
- FWCI
- 104.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (submittedVersion, other-oa)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- Bristol Research (University of Bristol) (submittedVersion, other-oa)
- Funders
- National Heart, Lung, and Blood Institute
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Paraoxonase enzyme and polymorphisms
- Keywords
- PCSK9, HMGCR, LDL cholesterol, cardiovascular disease, diabetes mellitus, genetic variants, PCSK9 inhibitors, statins, genetic score, impaired fasting glucose, additive genetic effects, cardiovascular risk prediction, LDL-C lowering therapy, HMG-CoA reductase inhibition, cardiovascular events, diabetes risk
- MeSH terms
- Proprotein Convertase 9, Cardiovascular Diseases, Diabetes Mellitus, Female, Humans, Hydroxymethylglutaryl CoA Reductases, Cholesterol, LDL, Male, Middle Aged, Random Allocation, Risk, Genetic Variation, Genetic Predisposition to Disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review