Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis
Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian random...
Uložené v:
| Vydané v: | PLoS medicine Ročník 17; číslo 3; s. e1003062 |
|---|---|
| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
Public Library of Science
01.03.2020
Public Library of Science (PLoS) |
| Predmet: | |
| ISSN: | 1549-1676, 1549-1277, 1549-1676 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.
We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.
These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. |
|---|---|
| AbstractList | Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.BACKGROUNDCirculating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.METHODS AND FINDINGSWe conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD.CONCLUSIONSThese findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. Methods and findings We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39–73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10−8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%–93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10−8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation–higher trait; 95% CI: 1.49–1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25–1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56–1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31–2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57–1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02–1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation–higher HDL cholesterol (OR 0.80; 95% CI: 0.75–0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77–0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. Conclusions These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. Methods and findings We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39–73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10−8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%–93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10−8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation–higher trait; 95% CI: 1.49–1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25–1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56–1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31–2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57–1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02–1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation–higher HDL cholesterol (OR 0.80; 95% CI: 0.75–0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77–0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. Conclusions These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. BackgroundCirculating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.Methods and findingsWe conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.ConclusionsThese findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD. |
| Author | Holmes, Michael V. Richardson, Tom G. Ala-Korpela, Mika Sanderson, Eleanor Davey Smith, George Palmer, Tom M. Ference, Brian A. |
| AuthorAffiliation | 5 NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland 6 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Australia 9 Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom University of Pennsylvania, UNITED STATES 2 Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, United Kingdom 7 Centre for Naturally Randomized Trials, University of Cambridge, Cambridge, United Kingdom 3 Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Australia 4 Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland 1 Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom 8 MRC/BHF Cardiovascular Epidemiology Un |
| AuthorAffiliation_xml | – name: 9 Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom – name: University of Pennsylvania, UNITED STATES – name: 1 Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom – name: 7 Centre for Naturally Randomized Trials, University of Cambridge, Cambridge, United Kingdom – name: 8 MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom – name: 5 NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland – name: 2 Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, United Kingdom – name: 10 Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom – name: 3 Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Australia – name: 6 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Australia – name: 4 Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland |
| Author_xml | – sequence: 1 givenname: Tom G. orcidid: 0000-0002-7918-2040 surname: Richardson fullname: Richardson, Tom G. – sequence: 2 givenname: Eleanor orcidid: 0000-0001-5188-5775 surname: Sanderson fullname: Sanderson, Eleanor – sequence: 3 givenname: Tom M. orcidid: 0000-0003-4655-4511 surname: Palmer fullname: Palmer, Tom M. – sequence: 4 givenname: Mika orcidid: 0000-0001-5905-1206 surname: Ala-Korpela fullname: Ala-Korpela, Mika – sequence: 5 givenname: Brian A. surname: Ference fullname: Ference, Brian A. – sequence: 6 givenname: George orcidid: 0000-0002-1407-8314 surname: Davey Smith fullname: Davey Smith, George – sequence: 7 givenname: Michael V. orcidid: 0000-0001-6617-0879 surname: Holmes fullname: Holmes, Michael V. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32203549$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9Uk1v1DAQjVAR_YB_gMASFy67OHbsJD1UqqoClYq4wNma2JOui9cOdrJV_xM_Eu9Hq22FOHnsefPmvfEcFwc-eCyKtyWdl7wuP92GKXpw82GJZl5SyqlkL4qjUlTtrJS1PNiLD4vjlG4pZS1t6avikDNGeU4eFX8uV-AmGK2_IeMCSUSXL8GnhR1Ih-MdoifaRj25LcjZIQwxjGj9OrYmEfCGwBD2Monc2XFBok2_SOiJDjF4iPdkgRBHYmxCSHhKzslycqNdQbTQOSTf0Bt0FjyJmTMsbdpoyQ3A3SebXhcve3AJ3-zOk-Ln58sfF19n19-_XF2cX8-0YHKcga6FrjRK0ZqOt6Vkveh11zaGc9rKBnXVmLrsse8ZBWM6xkvTtqI32PRSVPykeL_lHVxIajfopFglad3ypm4y4mqLMAFu1RDtMttTAazaPIR4o7JTqx0qKoxg0EMFmlddJ6BjAphgXPfamBoy19mu29Tlv9ToxwjuCenTjLcLdRNWqqZNWzGWCT7uCGL4PWEaVZ6cRufAY5iybt4wKaQsaYZ-eAb9t7t3-4oepTysTQZUW4COIaWI_SOkpGq9nQ-0ar2dareduez0WZm24-aLsy_r_l_8F_F09Y4 |
| CitedBy_id | crossref_primary_10_1016_j_ihj_2023_12_001 crossref_primary_10_1007_s00394_021_02578_0 crossref_primary_10_1016_j_jfma_2022_05_010 crossref_primary_10_1002_ame2_12373 crossref_primary_10_1038_s41598_024_56467_7 crossref_primary_10_1111_ene_15810 crossref_primary_10_1186_s13098_025_01701_z crossref_primary_10_1097_MOL_0000000000000906 crossref_primary_10_1038_s41467_021_23084_1 crossref_primary_10_1097_MOL_0000000000000905 crossref_primary_10_1097_MD_0000000000044244 crossref_primary_10_3389_fendo_2024_1434145 crossref_primary_10_1038_s41467_022_30098_w crossref_primary_10_1097_MD_0000000000044482 crossref_primary_10_1186_s12891_024_07674_w crossref_primary_10_1016_j_clnu_2025_03_020 crossref_primary_10_1016_j_ajhg_2021_11_005 crossref_primary_10_1016_j_biopsych_2025_02_887 crossref_primary_10_1007_s11886_022_01829_8 crossref_primary_10_1038_s42003_022_03702_4 crossref_primary_10_3390_ijms23010310 crossref_primary_10_1186_s13073_021_00994_9 crossref_primary_10_3390_nu16213588 crossref_primary_10_1002_j_2040_4603_2022_tb00197_x crossref_primary_10_1093_eurheartj_ehaf207 crossref_primary_10_3389_fimmu_2023_1174998 crossref_primary_10_1016_j_numecd_2025_104198 crossref_primary_10_1186_s12933_024_02321_z crossref_primary_10_1097_MD_0000000000044495 crossref_primary_10_3389_fnut_2021_712600 crossref_primary_10_1093_mutage_geae012 crossref_primary_10_1186_s12933_022_01714_2 crossref_primary_10_1186_s12944_024_02026_y crossref_primary_10_1007_s11033_023_09128_3 crossref_primary_10_3389_fneur_2023_1185986 crossref_primary_10_1016_j_ajcnut_2024_01_002 crossref_primary_10_3390_cells12172143 crossref_primary_10_1007_s11239_023_02871_1 crossref_primary_10_1039_D4FO04514A crossref_primary_10_1007_s00432_020_03508_z crossref_primary_10_1007_s00223_023_01160_6 crossref_primary_10_1016_j_diabres_2023_110561 crossref_primary_10_1186_s10020_022_00542_0 crossref_primary_10_1177_00220345241264749 crossref_primary_10_1007_s13755_024_00323_5 crossref_primary_10_1016_j_jacl_2021_04_001 crossref_primary_10_1186_s12885_024_12434_z crossref_primary_10_1111_jth_15657 crossref_primary_10_1155_2024_5324127 crossref_primary_10_1161_STROKEAHA_124_046544 crossref_primary_10_1016_j_ajpc_2020_100003 crossref_primary_10_1186_s13098_023_01218_3 crossref_primary_10_1186_s13059_023_02993_y crossref_primary_10_1016_j_rce_2022_11_001 crossref_primary_10_1097_MD_0000000000044351 crossref_primary_10_1186_s13075_023_03122_7 crossref_primary_10_1371_journal_pbio_3001547 crossref_primary_10_1016_j_ophtha_2023_08_023 crossref_primary_10_1038_s41598_022_15230_6 crossref_primary_10_3390_ijms241914857 crossref_primary_10_1186_s13098_023_01174_y crossref_primary_10_3390_nu14204434 crossref_primary_10_3390_biomedicines12122828 crossref_primary_10_1016_j_spinee_2023_10_021 crossref_primary_10_1038_s41598_024_71734_3 crossref_primary_10_1016_j_semarthrit_2022_152058 crossref_primary_10_1007_s00192_024_05807_2 crossref_primary_10_1038_s41588_021_01011_w crossref_primary_10_3390_nu13051489 crossref_primary_10_3390_ijms24031814 crossref_primary_10_15829_1728_8800_2023_3871 crossref_primary_10_1017_S000711452100369X crossref_primary_10_1007_s00403_024_03600_1 crossref_primary_10_1016_j_nefroe_2023_08_002 crossref_primary_10_1371_journal_pgen_1009814 crossref_primary_10_1016_j_phrs_2023_106873 crossref_primary_10_3390_metabo13020273 crossref_primary_10_1109_ACCESS_2024_3435948 crossref_primary_10_1186_s12944_023_01963_4 crossref_primary_10_3389_fgene_2022_962449 crossref_primary_10_1093_cvr_cvaf078 crossref_primary_10_3390_genes14061265 crossref_primary_10_1371_journal_pone_0278375 crossref_primary_10_1186_s12944_022_01733_8 crossref_primary_10_1007_s00394_023_03281_y crossref_primary_10_1186_s12885_024_12366_8 crossref_primary_10_3389_fnut_2023_1225376 crossref_primary_10_1093_molbev_msad054 crossref_primary_10_26508_lsa_202301962 crossref_primary_10_1186_s13073_022_01135_6 crossref_primary_10_1111_1346_8138_16910 crossref_primary_10_1093_hmg_ddab177 crossref_primary_10_1038_s41588_021_00969_x crossref_primary_10_3389_fendo_2023_1189473 crossref_primary_10_1007_s00018_025_05784_9 crossref_primary_10_1186_s12966_022_01244_w crossref_primary_10_3390_genes15010132 crossref_primary_10_3390_genes16050564 crossref_primary_10_7554_eLife_58361 crossref_primary_10_1038_s41598_024_61440_5 crossref_primary_10_3389_fimmu_2023_1160312 crossref_primary_10_1016_j_dld_2024_01_211 crossref_primary_10_1186_s13643_023_02442_8 crossref_primary_10_3389_fgene_2023_1140400 crossref_primary_10_1016_j_jlr_2024_100662 crossref_primary_10_1038_s41398_020_01047_2 crossref_primary_10_1002_cpt_2260 crossref_primary_10_1016_j_clnu_2021_03_040 crossref_primary_10_1016_j_xgen_2025_100810 crossref_primary_10_1038_s41401_025_01561_3 crossref_primary_10_1016_j_jhep_2024_06_030 crossref_primary_10_3389_fpsyt_2023_1275834 crossref_primary_10_1007_s11357_024_01348_0 crossref_primary_10_1016_j_cca_2022_07_014 crossref_primary_10_1186_s12944_024_02133_w crossref_primary_10_3389_fmicb_2023_1259579 crossref_primary_10_1002_brb3_3543 crossref_primary_10_1016_j_ajhg_2021_12_013 crossref_primary_10_3389_fcvm_2022_964743 crossref_primary_10_1186_s13098_024_01520_8 crossref_primary_10_1016_j_compbiolchem_2025_108422 crossref_primary_10_1136_heartjnl_2022_321347 crossref_primary_10_1016_j_canep_2025_102849 crossref_primary_10_3390_metabo13010027 crossref_primary_10_1016_j_clinthera_2024_07_008 crossref_primary_10_1007_s00392_024_02420_7 crossref_primary_10_1038_s41598_024_51523_8 crossref_primary_10_1016_j_atherosclerosis_2025_119136 crossref_primary_10_1093_ije_dyaa216 crossref_primary_10_3390_biomedicines13010013 crossref_primary_10_7554_eLife_75244 crossref_primary_10_1016_j_atherosclerosis_2025_119139 crossref_primary_10_26599_1671_5411_2025_03_008 crossref_primary_10_3389_fendo_2024_1363018 crossref_primary_10_1186_s40246_025_00789_8 crossref_primary_10_1016_j_cell_2023_08_012 crossref_primary_10_1016_j_molmet_2020_101092 crossref_primary_10_1016_j_heliyon_2024_e28154 crossref_primary_10_3389_fgene_2021_787545 crossref_primary_10_1186_s12920_022_01180_5 crossref_primary_10_1002_cam4_70698 crossref_primary_10_1016_j_heliyon_2024_e32781 crossref_primary_10_1161_JAHA_122_025644 crossref_primary_10_1186_s12916_023_02903_w crossref_primary_10_1097_CRD_0000000000001006 crossref_primary_10_2337_db24_0923 crossref_primary_10_1177_23969873241265019 crossref_primary_10_1515_med_2024_0994 crossref_primary_10_1007_s12672_025_02760_4 crossref_primary_10_1136_egastro_2023_100034 crossref_primary_10_1016_j_atherosclerosis_2024_119083 crossref_primary_10_1007_s00415_023_11604_6 crossref_primary_10_1161_CIR_0000000000001123 crossref_primary_10_1210_jendso_bvaf108 crossref_primary_10_1097_MD_0000000000044097 crossref_primary_10_1097_MED_0000000000000596 crossref_primary_10_3389_fmed_2023_1289026 crossref_primary_10_1152_physiolgenomics_00019_2024 crossref_primary_10_1002_ana_25916 crossref_primary_10_3389_fneur_2020_00675 crossref_primary_10_1016_j_atherosclerosis_2020_09_020 crossref_primary_10_1038_s41416_024_02900_7 crossref_primary_10_1161_CIRCRESAHA_123_323284 crossref_primary_10_1038_s41598_022_24100_0 crossref_primary_10_1161_CIRCULATIONAHA_123_064296 crossref_primary_10_7554_eLife_58567 crossref_primary_10_3389_fmicb_2022_1018322 crossref_primary_10_1016_j_ebiom_2021_103228 crossref_primary_10_1155_2024_2991243 crossref_primary_10_3390_genes16050523 crossref_primary_10_1007_s12035_024_04007_9 crossref_primary_10_1016_j_biopha_2024_116305 crossref_primary_10_1186_s12967_022_03822_9 crossref_primary_10_3389_fnut_2022_862942 crossref_primary_10_1038_s41598_025_86859_2 crossref_primary_10_1186_s13098_024_01448_z crossref_primary_10_1038_s42003_022_03248_5 crossref_primary_10_1080_14767058_2024_2397722 crossref_primary_10_1093_hmg_ddae098 crossref_primary_10_1016_j_ajcnut_2024_03_009 crossref_primary_10_1038_s41380_025_03242_3 crossref_primary_10_1155_humu_5536318 crossref_primary_10_1186_s12876_024_03383_9 crossref_primary_10_1007_s00431_023_05033_w crossref_primary_10_3389_fnut_2024_1288886 crossref_primary_10_3389_fendo_2024_1362499 crossref_primary_10_3390_nu13082550 crossref_primary_10_1093_ije_dyaa243 crossref_primary_10_1007_s00125_024_06324_z crossref_primary_10_1038_s41398_024_02932_w crossref_primary_10_1002_sim_70143 crossref_primary_10_1111_ijpo_70017 crossref_primary_10_1515_jtim_2024_0017 crossref_primary_10_4103_apc_apc_30_23 crossref_primary_10_1093_bjd_ljae089 crossref_primary_10_1111_dom_15910 crossref_primary_10_3390_metabo12121175 crossref_primary_10_1161_JAHA_122_025858 crossref_primary_10_1016_j_jad_2025_120057 crossref_primary_10_1007_s12672_025_03261_0 crossref_primary_10_1093_eurjpc_zwac219 crossref_primary_10_1016_j_metabol_2023_155616 crossref_primary_10_1016_j_jacl_2021_09_046 crossref_primary_10_1007_s00431_023_05350_0 crossref_primary_10_1038_s41569_020_00493_1 crossref_primary_10_3390_nu13072215 crossref_primary_10_1080_02770903_2024_2394143 crossref_primary_10_1016_j_ajhg_2023_06_005 crossref_primary_10_1038_s41467_024_46102_4 crossref_primary_10_3389_fendo_2024_1414585 crossref_primary_10_1210_endocr_bqae146 crossref_primary_10_1186_s12920_021_01127_2 crossref_primary_10_1161_CIR_0000000000001209 crossref_primary_10_1212_WNL_0000000000201657 crossref_primary_10_3389_fgene_2021_669215 crossref_primary_10_1016_j_endien_2023_05_012 crossref_primary_10_1038_s41390_022_02243_0 crossref_primary_10_1038_s41598_024_67800_5 crossref_primary_10_1042_BSR20241165 crossref_primary_10_1080_0886022X_2024_2420841 crossref_primary_10_1038_s41598_024_69737_1 crossref_primary_10_1093_hmg_ddaf018 crossref_primary_10_1186_s12933_025_02790_w crossref_primary_10_3389_fnut_2022_956900 crossref_primary_10_1186_s12894_023_01332_4 crossref_primary_10_1002_med4_70009 crossref_primary_10_3390_nu14071327 crossref_primary_10_3389_fendo_2024_1404747 crossref_primary_10_3389_fgene_2021_738265 crossref_primary_10_3390_ijms22094547 crossref_primary_10_1093_clinchem_hvaa290 crossref_primary_10_1161_CIRCGEN_122_003710 crossref_primary_10_1371_journal_pgen_1011159 crossref_primary_10_1002_gepi_22392 crossref_primary_10_3390_metabo13090972 crossref_primary_10_1038_s41598_023_39936_3 crossref_primary_10_3389_fendo_2023_1278273 crossref_primary_10_1136_bmjmed_2022_000277 crossref_primary_10_3389_fgene_2021_771044 crossref_primary_10_1016_j_intimp_2025_114736 crossref_primary_10_1001_jamanetworkopen_2023_52572 crossref_primary_10_5114_aoms_193708 crossref_primary_10_1093_ije_dyab014 crossref_primary_10_1161_CIR_0000000000001303 crossref_primary_10_1038_s43856_022_00208_2 crossref_primary_10_1016_j_metabol_2022_155329 crossref_primary_10_1093_ije_dyab016 crossref_primary_10_1080_14737140_2025_2548488 crossref_primary_10_1111_jnc_16056 crossref_primary_10_1111_acel_13868 crossref_primary_10_1016_j_endinu_2023_02_002 crossref_primary_10_3390_genes13081366 crossref_primary_10_3389_fcvm_2023_1234271 crossref_primary_10_3390_genes13071201 crossref_primary_10_3390_nu16213674 crossref_primary_10_2147_NSS_S423331 crossref_primary_10_1002_hsr2_70875 crossref_primary_10_1016_j_xgen_2025_100784 crossref_primary_10_1016_j_jtha_2023_08_004 crossref_primary_10_1017_S0007114524001594 crossref_primary_10_1111_bjh_19229 crossref_primary_10_2217_epi_2020_0329 crossref_primary_10_1016_j_heliyon_2024_e41539 crossref_primary_10_1007_s11468_025_02785_z crossref_primary_10_1016_j_metabol_2024_155817 crossref_primary_10_1016_j_numecd_2025_103898 crossref_primary_10_1016_j_numecd_2021_12_004 crossref_primary_10_3390_metabo11100691 crossref_primary_10_1080_0886022X_2025_2476051 crossref_primary_10_1093_eurjpc_zwac261 crossref_primary_10_1002_dmrr_70005 crossref_primary_10_1038_s41598_021_88256_x crossref_primary_10_1038_s41598_025_12369_w crossref_primary_10_1177_1934578X241291396 crossref_primary_10_3390_nu14061218 crossref_primary_10_1002_alz_13140 crossref_primary_10_1016_j_ajpc_2022_100342 crossref_primary_10_1016_j_ebiom_2023_104964 crossref_primary_10_1016_j_neuroimage_2022_119632 crossref_primary_10_1111_joim_13479 crossref_primary_10_1093_aje_kwae445 crossref_primary_10_3390_jcm11020313 crossref_primary_10_1093_eurjpc_zwac253 crossref_primary_10_1093_eurjpc_zwac252 crossref_primary_10_1093_ije_dyab152 crossref_primary_10_7554_eLife_80560 crossref_primary_10_3389_fnut_2023_1158810 crossref_primary_10_3390_nu15133002 crossref_primary_10_2337_dc21_1284 crossref_primary_10_1186_s12929_023_00905_7 crossref_primary_10_3390_ijms25137376 crossref_primary_10_1096_fj_202500032RRR crossref_primary_10_1093_eurheartj_ehad736 crossref_primary_10_1097_HJH_0000000000003664 crossref_primary_10_1186_s12944_024_02085_1 crossref_primary_10_1161_ATVBAHA_120_315639 crossref_primary_10_1111_exd_15157 crossref_primary_10_1016_j_ihj_2023_08_003 crossref_primary_10_1186_s12920_023_01761_y crossref_primary_10_1155_2022_5165203 crossref_primary_10_12688_wellcomeopenres_16928_2 crossref_primary_10_12688_wellcomeopenres_16928_1 crossref_primary_10_1186_s12920_024_01844_4 crossref_primary_10_1016_j_eprac_2022_08_002 crossref_primary_10_3389_fendo_2023_1166740 crossref_primary_10_3389_fendo_2024_1446719 crossref_primary_10_1186_s12967_024_05097_8 crossref_primary_10_3389_fnut_2023_1078963 crossref_primary_10_1016_S2215_0366_21_00286_8 crossref_primary_10_1039_D3FO05024F crossref_primary_10_1371_journal_pone_0301811 crossref_primary_10_1016_j_ebiom_2023_104503 crossref_primary_10_1038_s41598_021_85503_z crossref_primary_10_1093_eurheartj_ehad845 crossref_primary_10_1186_s13148_021_01113_6 crossref_primary_10_1016_j_bjorl_2023_101306 crossref_primary_10_3389_fgene_2023_1077438 crossref_primary_10_1093_ije_dyab051 crossref_primary_10_1016_j_jacl_2023_05_093 crossref_primary_10_1161_JAHA_123_029552 crossref_primary_10_1212_WNL_0000000000207777 crossref_primary_10_3389_fendo_2024_1359015 crossref_primary_10_1093_brain_awab351 crossref_primary_10_1177_09622802241313294 crossref_primary_10_3389_fendo_2024_1338698 crossref_primary_10_1038_s41588_022_01286_7 crossref_primary_10_1016_j_jlr_2022_100313 crossref_primary_10_1016_j_tjnut_2023_12_035 crossref_primary_10_3390_nu15214497 crossref_primary_10_1016_j_atherosclerosis_2021_04_013 crossref_primary_10_3390_genes11111326 crossref_primary_10_1093_cvr_cvab164 crossref_primary_10_1186_s13059_022_02837_1 crossref_primary_10_3389_fcell_2020_621144 crossref_primary_10_1186_s13098_023_01189_5 crossref_primary_10_1016_j_atherosclerosis_2023_117394 crossref_primary_10_1210_clinem_dgac562 crossref_primary_10_1093_toxsci_kfac103 crossref_primary_10_1016_j_atherosclerosis_2023_02_001 crossref_primary_10_1186_s12967_022_03407_6 crossref_primary_10_1007_s11010_024_04931_3 crossref_primary_10_1016_j_rceng_2023_06_001 crossref_primary_10_1016_j_atherosclerosis_2024_117558 crossref_primary_10_1080_21678421_2023_2255622 crossref_primary_10_3389_fendo_2023_1221228 crossref_primary_10_1186_s12991_024_00495_0 crossref_primary_10_1186_s12876_025_04162_w crossref_primary_10_1016_j_ebiom_2023_104884 crossref_primary_10_3389_fphar_2023_1091976 crossref_primary_10_1007_s00018_020_03715_4 crossref_primary_10_1016_j_atherosclerosis_2021_04_021 crossref_primary_10_1038_s41398_021_01759_z crossref_primary_10_1080_03630242_2025_2539819 crossref_primary_10_1186_s13073_023_01255_7 crossref_primary_10_1111_gbb_12834 crossref_primary_10_3390_nu15204445 crossref_primary_10_1161_CIR_0000000000001052 crossref_primary_10_1186_s12933_023_02045_6 crossref_primary_10_1371_journal_pgen_1010596 crossref_primary_10_1007_s00011_024_01850_3 crossref_primary_10_1111_ene_15471 crossref_primary_10_1016_j_molmet_2024_102033 crossref_primary_10_1038_s41588_022_01121_z crossref_primary_10_1038_s41746_025_01850_5 crossref_primary_10_7554_eLife_73951 crossref_primary_10_1093_eurjpc_zwac290 crossref_primary_10_3390_nu14010181 crossref_primary_10_1161_ATVBAHA_120_315355 crossref_primary_10_1681_ASN_0000000000000238 crossref_primary_10_3390_ph17030289 crossref_primary_10_3233_JAD_230863 crossref_primary_10_1093_cvr_cvab060 crossref_primary_10_3233_JAD_230623 crossref_primary_10_3390_ijms25042182 crossref_primary_10_1002_cpt_2934 crossref_primary_10_1093_eurheartj_ehac605 crossref_primary_10_1093_pnasnexus_pgae033 crossref_primary_10_3390_genes13091553 crossref_primary_10_1038_s42003_022_03291_2 crossref_primary_10_1038_s42003_025_07860_z crossref_primary_10_1161_ATVBAHA_124_321165 crossref_primary_10_1186_s12872_024_03803_4 crossref_primary_10_1681_ASN_2020121760 crossref_primary_10_1038_s41588_022_01199_5 crossref_primary_10_1016_j_artere_2025_500816 crossref_primary_10_1016_j_arteri_2025_500816 crossref_primary_10_1016_j_artere_2023_05_001 crossref_primary_10_1038_s41525_021_00189_6 crossref_primary_10_3390_jcdd12070256 crossref_primary_10_1093_postmj_qgae011 crossref_primary_10_1161_JAHA_123_032409 crossref_primary_10_1186_s12014_024_09465_w crossref_primary_10_3389_fimmu_2024_1328297 crossref_primary_10_1161_STROKEAHA_120_032617 crossref_primary_10_1186_s12944_024_02096_y crossref_primary_10_1038_s41598_022_16488_6 crossref_primary_10_1038_s41398_021_01736_6 crossref_primary_10_1038_s41598_022_07465_0 crossref_primary_10_1093_eurjpc_zwae009 crossref_primary_10_1371_journal_pone_0304280 crossref_primary_10_1007_s12012_024_09930_w crossref_primary_10_1371_journal_pmed_1003636 crossref_primary_10_1016_j_ejogrb_2023_10_020 crossref_primary_10_1016_j_ajpc_2022_100371 crossref_primary_10_1111_1753_0407_70056 crossref_primary_10_1016_j_ebiom_2025_105671 crossref_primary_10_1093_hmg_ddad212 crossref_primary_10_1001_jamanetworkopen_2023_13734 crossref_primary_10_1016_j_jacl_2022_05_068 crossref_primary_10_1007_s11033_023_08894_4 crossref_primary_10_3390_healthcare12222275 crossref_primary_10_1093_ije_dyad048 crossref_primary_10_1161_CIRCGEN_123_004232 crossref_primary_10_1016_j_jlr_2022_100193 crossref_primary_10_1097_MOL_0000000000000866 crossref_primary_10_7554_eLife_65554 crossref_primary_10_1186_s12872_024_03804_3 crossref_primary_10_3389_fendo_2024_1325417 crossref_primary_10_3389_fcvm_2022_841032 crossref_primary_10_1016_j_athplu_2025_04_003 crossref_primary_10_1038_s41598_024_51701_8 crossref_primary_10_3390_biomedicines12040818 crossref_primary_10_1111_1753_0407_13260 crossref_primary_10_3390_v16071161 crossref_primary_10_1016_j_jlr_2024_100528 crossref_primary_10_1007_s40618_023_02028_0 crossref_primary_10_1093_eurheartj_ehaf606 crossref_primary_10_1186_s12916_023_03184_z crossref_primary_10_1093_hmg_ddac016 crossref_primary_10_1097_MOL_0000000000000973 crossref_primary_10_3389_fnut_2025_1644496 crossref_primary_10_3390_ijms26104817 crossref_primary_10_1038_s41569_020_00477_1 crossref_primary_10_1007_s10557_021_07158_2 crossref_primary_10_1007_s11883_023_01153_8 crossref_primary_10_1097_MOL_0000000000000737 crossref_primary_10_3390_life15091459 crossref_primary_10_1016_j_jlr_2023_100471 crossref_primary_10_1038_s41467_024_54078_4 crossref_primary_10_1161_ATVBAHA_120_315391 crossref_primary_10_1002_ijc_34026 crossref_primary_10_1038_s41598_025_88375_9 crossref_primary_10_1161_HYPERTENSIONAHA_122_19510 crossref_primary_10_1016_j_jacl_2024_07_004 crossref_primary_10_1186_s12916_025_04329_y crossref_primary_10_1371_journal_pmed_1003410 crossref_primary_10_3389_fendo_2024_1335489 crossref_primary_10_1080_02770903_2025_2493177 crossref_primary_10_1097_MOL_0000000000000721 crossref_primary_10_1111_eci_13893 crossref_primary_10_2337_db21_0655 crossref_primary_10_1155_ije_6664846 crossref_primary_10_1186_s12931_023_02661_6 crossref_primary_10_1093_eurjpc_zwaf037 crossref_primary_10_1007_s12011_023_03726_9 crossref_primary_10_1016_j_numecd_2025_104128 crossref_primary_10_1136_thorax_2023_220789 crossref_primary_10_1016_j_numecd_2022_01_002 crossref_primary_10_1002_ijc_34032 crossref_primary_10_1016_j_clnu_2025_01_034 crossref_primary_10_1016_j_phrs_2023_106936 crossref_primary_10_1210_clinem_dgae843 crossref_primary_10_1111_liv_16150 crossref_primary_10_1186_s12916_023_03003_5 crossref_primary_10_1073_pnas_2121133119 crossref_primary_10_1007_s40261_022_01208_9 crossref_primary_10_1371_journal_pone_0298610 crossref_primary_10_3390_ijms23169417 crossref_primary_10_1161_ATVBAHA_121_316650 crossref_primary_10_1038_s41467_023_38125_0 crossref_primary_10_1016_j_jlr_2024_100625 crossref_primary_10_1007_s00403_024_03100_2 crossref_primary_10_1016_j_atherosclerosis_2024_117482 crossref_primary_10_3389_fcvm_2024_1446610 crossref_primary_10_3389_fgene_2024_1383646 crossref_primary_10_1016_j_atherosclerosis_2024_117489 crossref_primary_10_1093_hmg_ddab263 crossref_primary_10_1016_j_asjsur_2024_12_070 crossref_primary_10_1016_j_jpsychires_2024_04_027 crossref_primary_10_3389_fnut_2022_910690 crossref_primary_10_1093_eurheartj_ehae655 crossref_primary_10_1038_s41598_023_41130_4 crossref_primary_10_3389_fendo_2024_1345267 crossref_primary_10_1016_j_bbalip_2021_159063 crossref_primary_10_1161_JAHA_124_034364 crossref_primary_10_1038_s41598_024_61628_9 crossref_primary_10_1097_HCO_0000000000000839 crossref_primary_10_3390_ijms22041593 crossref_primary_10_1002_sim_9699 crossref_primary_10_1161_JAHA_123_034180 crossref_primary_10_2147_COPD_S476833 crossref_primary_10_3389_fevo_2022_1059477 crossref_primary_10_1038_s41598_022_26572_6 crossref_primary_10_3389_fphys_2021_768411 crossref_primary_10_1177_0271678X231169838 crossref_primary_10_2147_IJWH_S496268 crossref_primary_10_1210_clinem_dgab633 crossref_primary_10_1016_j_jacl_2025_01_003 crossref_primary_10_1161_JAHA_124_035365 crossref_primary_10_1093_ije_dyaf020 crossref_primary_10_1016_j_hrthm_2023_10_024 crossref_primary_10_1016_j_ajpc_2021_100149 crossref_primary_10_1038_s42003_024_05887_2 crossref_primary_10_1016_j_tjfa_2025_100013 crossref_primary_10_1108_DAT_09_2020_0059 crossref_primary_10_1007_s10557_021_07156_4 crossref_primary_10_1093_nutrit_nuad102 crossref_primary_10_1161_CIRCGEN_124_004933 crossref_primary_10_1186_s12944_023_01872_6 crossref_primary_10_1038_s41598_024_79260_y crossref_primary_10_1007_s12011_024_04237_x crossref_primary_10_1186_s12944_022_01667_1 crossref_primary_10_1016_j_jacc_2024_12_033 crossref_primary_10_1002_ana_26426 crossref_primary_10_1016_j_hipert_2022_12_002 crossref_primary_10_1002_fsn3_70965 crossref_primary_10_1038_s43856_022_00234_0 crossref_primary_10_1038_s41366_024_01458_x crossref_primary_10_2147_CLEP_S439642 crossref_primary_10_1016_j_biopha_2021_111802 crossref_primary_10_1016_j_atherosclerosis_2025_120507 crossref_primary_10_1016_j_jacl_2024_08_013 crossref_primary_10_1007_s12020_025_04427_0 crossref_primary_10_1002_sim_9368 crossref_primary_10_1371_journal_pgen_1009754 crossref_primary_10_1186_s12872_024_04132_2 crossref_primary_10_1016_j_jacc_2024_03_423 crossref_primary_10_1186_s12963_025_00396_8 crossref_primary_10_3389_fendo_2022_938891 crossref_primary_10_1038_s41467_022_29932_y crossref_primary_10_7554_eLife_75624 crossref_primary_10_1161_CIRCULATIONAHA_123_065866 crossref_primary_10_1161_JAHA_122_029103 crossref_primary_10_1097_MOL_0000000000000754 crossref_primary_10_1002_brb3_70396 crossref_primary_10_1016_j_jhep_2022_04_010 crossref_primary_10_2147_IJWH_S468733 crossref_primary_10_1002_ajpa_24620 crossref_primary_10_1007_s12265_024_10578_8 crossref_primary_10_1016_j_ymgme_2020_07_009 crossref_primary_10_1002_sim_9133 crossref_primary_10_1186_s13040_025_00484_3 crossref_primary_10_1249_MSS_0000000000003601 |
| Cites_doi | 10.1136/bmj.322.7280.226 10.18637/jss.v036.i03 10.1093/ije/dyy262 10.1016/0895-4356(91)90155-3 10.1093/hmg/ddu328 10.1093/ije/dyg070 10.1001/jama.2017.11467 10.1038/s41467-017-02317-2 10.1016/S0140-6736(19)32519-X 10.1016/j.cell.2015.01.036 10.1016/S0140-6736(12)60367-5 10.1001/jama.2018.20045 10.1161/CIRCOUTCOMES.110.959247 10.1038/s41569-019-0157-6 10.1038/ng.3396 10.1093/ije/dym276 10.1002/gepi.21965 10.7554/eLife.34408 10.1056/NEJMoa1002926 10.1093/ije/dyx102 10.1161/01.ATV.15.5.551 10.1016/S0140-6736(10)61350-5 10.1056/NEJMoa1701329 10.1001/jamacardio.2019.3780 10.1038/ng.2797 10.1097/MOL.0000000000000330 10.1056/NEJMoa1510926 10.1016/j.jacc.2012.09.017 10.12688/wellcomeopenres.15555.1 10.1161/CIRCULATIONAHA.108.777334 10.1038/s41588-018-0144-6 10.1038/ncomms11122 10.1093/ije/dyz068 10.1161/CIRCULATIONAHA.119.041149 10.1056/NEJMoa1706444 10.1001/jama.2016.13985 10.1038/s41572-019-0106-z 10.1093/eurheartj/ehz455 10.1002/sim.7492 10.1016/S0140-6736(16)31357-5 10.1186/s13742-015-0047-8 10.1161/CIRCRESAHA.119.315019 10.1161/CIRCULATIONAHA.114.013116 10.1136/bmj.k601 10.1093/hmg/ddy163 10.1001/jamacardio.2016.1884 10.1016/j.jacc.2015.02.020 10.1056/NEJMoa1604304 10.1016/j.jacc.2012.08.1026 10.1002/sim.7221 10.1093/ije/dyv080 10.1161/CIRCULATIONAHA.119.042134 10.1056/NEJMe1901565 10.1016/S0140-6736(14)61368-4 10.1038/nprot.2010.116 10.1001/jamacardio.2018.2168 10.1038/ng.3190 10.1038/nrg2481 10.1038/ng.2795 10.1093/eurheartj/eht571 10.1038/nature11632 10.1038/s41586-018-0579-z 10.1038/nrcardio.2017.78 10.1371/journal.pmed.1001779 10.1038/d41586-019-00857-9 10.1001/jama.2009.1619 |
| ContentType | Journal Article |
| Copyright | 2020 Richardson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2020 Richardson et al 2020 Richardson et al |
| Copyright_xml | – notice: 2020 Richardson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2020 Richardson et al 2020 Richardson et al |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7TK 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR CCPQU DWQXO FYUFA GHDGH K9. M0S M1P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM DOA CZK |
| DOI | 10.1371/journal.pmed.1003062 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Neurosciences Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials - QC ProQuest Central ProQuest One ProQuest Central Korea Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Health & Medical Complete (Alumni) ProQuest Health & Medical Collection Medical Database ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals PLoS Medicine |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China ProQuest Central ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Neurosciences Abstracts ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic Publicly Available Content Database MEDLINE |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: ProQuest Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| DocumentTitleAlternate | Lipoprotein lipids, apolipoproteins, and risk of CHD: Findings from multivariable Mendelian randomization |
| EISSN | 1549-1676 |
| ExternalDocumentID | 2460793878 oai_doaj_org_article_05d52afa4ac34bb5ab25a2523cfcdd7a PMC7089422 32203549 10_1371_journal_pmed_1003062 |
| Genre | Research Support, Non-U.S. Gov't Journal Article |
| GeographicLocations | Melbourne Victoria Australia United Kingdom--UK Australia Finland |
| GeographicLocations_xml | – name: Finland – name: United Kingdom--UK – name: Melbourne Victoria Australia – name: Australia |
| GrantInformation_xml | – fundername: British Heart Foundation grantid: CH/1996001/9454 – fundername: Medical Research Council grantid: MR/S003886/1 – fundername: Department of Health – fundername: Medical Research Council grantid: MC_UU_00011/1 – fundername: Medical Research Council grantid: MC_PC_17228 – fundername: Medical Research Council grantid: MC_UU-00011/2 – fundername: British Heart Foundation grantid: FS/18/23/33512 – fundername: Medical Research Council grantid: MC_QA137853 – fundername: Medical Research Council grantid: MC_UU_00011/2 – fundername: ; – fundername: ; grantid: MC_UU_00011/1 and MC_UU-00011/2 – fundername: ; grantid: MRC PHRU Oxford – fundername: ; grantid: Obesity theme – fundername: ; grantid: APP1158958 – fundername: ; grantid: MR/S003886/1 – fundername: ; grantid: FS/18/23/33512 |
| GroupedDBID | --- 123 29O 2WC 53G 5VS 7X7 88E 8FI 8FJ AAFWJ AAUCC AAWOE AAWTL AAYXX ABDBF ABUWG ACCTH ACGFO ACIHN ACPRK ACUHS ADBBV AEAQA AENEX AFFHD AFKRA AFPKN AFRAH AFXKF AHMBA AKRSQ ALMA_UNASSIGNED_HOLDINGS AOIJS B0M BAIFH BAWUL BBTPI BCNDV BENPR BPHCQ BVXVI BWKFM CCPQU CITATION CS3 DIK DU5 E3Z EAP EAS EBD EBS EJD EMK EMOBN ESX F5P FPL FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR IHW INH INR IOF IOV IPO ISN ISR ITC KQ8 M1P M48 MK0 O5R O5S OK1 OVT P2P PHGZM PHGZT PIMPY PJZUB PPXIY PQQKQ PROAC PSQYO PV9 RNS RPM RZL SV3 TR2 TUS UKHRP WOW XSB YZZ ~8M ADRAZ ADXHL ALIPV CGR CUY CVF ECM EIF H13 IPNFZ NPM RIG WOQ 3V. 7TK 7XB 8FK AZQEC DWQXO K9. PKEHL PQEST PQUKI PRINS 7X8 PUEGO 5PM - AAPBV ABPTK ADACO BBAFP BCGST CZK ICW M~E |
| ID | FETCH-LOGICAL-c526t-ac75c4ce659db39162f5fcb98d330968ec48d71feff20addb231d995fde8f6543 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 585 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000558139500021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1549-1676 1549-1277 |
| IngestDate | Sun May 01 00:11:09 EDT 2022 Fri Oct 03 12:53:26 EDT 2025 Tue Nov 04 02:00:32 EST 2025 Fri Sep 05 07:08:29 EDT 2025 Sat Nov 29 14:27:52 EST 2025 Mon Jul 21 06:05:16 EDT 2025 Sat Nov 29 05:16:41 EST 2025 Tue Nov 18 21:38:25 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| License | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Creative Commons Attribution License |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c526t-ac75c4ce659db39162f5fcb98d330968ec48d71feff20addb231d995fde8f6543 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 I have read the journal's policy and the authors of this manuscript have the following competing interests: BAF reports receiving grants from Amgen, Merck & Co., Novartis, and Esperion Therapeutics; consulting or advisory board fees from Amgen, Regeneron, Sanofi, Merck & Co., Pfizer, CiVi BioPhama, and KrKA Pharmaceuticals; and grants from Merck & Co., Amgen, Novartis, Novo Nordisk, Regeneron, Sanofi, Pfizer, Eli Lilly, Mylan, Ionis, dalCOR, Silence Therapeutics, Integral Therapeutics, CiVi Pharma, KrKa Phamaceuticals, American College of Cardiology, European Atherosclerosis Society, and European Society of Cardiology. MVH has collaborated with Boehringer Ingelheim in research, and in accordance with the policy of the The Clinical Trial Service Unit and Epidemiological Studies Unit (University of Oxford), did not accept any personal payment. GDS is an Academic Editor on PLOS Medicine's editorial board. All other authors report no potential conflicts of interest. These authors are joint senior authors on this work. |
| ORCID | 0000-0001-5188-5775 0000-0003-4655-4511 0000-0002-7918-2040 0000-0001-5905-1206 0000-0001-6617-0879 0000-0002-1407-8314 |
| OpenAccessLink | https://doaj.org/article/05d52afa4ac34bb5ab25a2523cfcdd7a |
| PMID | 32203549 |
| PQID | 2460793878 |
| PQPubID | 1436338 |
| ParticipantIDs | plos_journals_2460793878 doaj_primary_oai_doaj_org_article_05d52afa4ac34bb5ab25a2523cfcdd7a pubmedcentral_primary_oai_pubmedcentral_nih_gov_7089422 proquest_miscellaneous_2382656610 proquest_journals_2460793878 pubmed_primary_32203549 crossref_primary_10_1371_journal_pmed_1003062 crossref_citationtrail_10_1371_journal_pmed_1003062 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-03-01 |
| PublicationDateYYYYMMDD | 2020-03-01 |
| PublicationDate_xml | – month: 03 year: 2020 text: 2020-03-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: San Francisco – name: San Francisco, CA USA |
| PublicationTitle | PLoS medicine |
| PublicationTitleAlternate | PLoS Med |
| PublicationYear | 2020 |
| Publisher | Public Library of Science Public Library of Science (PLoS) |
| Publisher_xml | – name: Public Library of Science – name: Public Library of Science (PLoS) |
| References | J White (pmed.1003062.ref013) 2016; 1 R Mitchell (pmed.1003062.ref036) 2019 HPS3/TIMI55-REVEAL Collaborative Group (pmed.1003062.ref066) 2017; 377 AD Sniderman (pmed.1003062.ref012) 2019; 124 AD Sniderman (pmed.1003062.ref019) 2011; 4 C Welsh (pmed.1003062.ref022) 2019; 140 Global Lipids Genetics Consortium (pmed.1003062.ref040) 2013; 45 E Sanderson (pmed.1003062.ref028) 2019; 48 W. Viechtbauer (pmed.1003062.ref048) 2010; 36 E Sanderson (pmed.1003062.ref045) 2020 G Hemani (pmed.1003062.ref046) 2018; 7 S Mora (pmed.1003062.ref023) 2019; 140 J Boren (pmed.1003062.ref060) 2016; 27 C Sudlow (pmed.1003062.ref030) 2015; 12 G Davey Smith (pmed.1003062.ref043) 2014; 23 DJ Rader (pmed.1003062.ref068) 2018; 3 MV Holmes (pmed.1003062.ref067) 2019; 380 P Libby (pmed.1003062.ref072) 2019; 5 BA Ference (pmed.1003062.ref006) 2016; 375 Z Zhu (pmed.1003062.ref070) 2018; 9 J Bowden (pmed.1003062.ref069) 2017; 36 AN Phillips (pmed.1003062.ref017) 1991; 44 Cholesterol Treatment Trialists' Collaborators (pmed.1003062.ref002) 2010; 376 J Kettunen (pmed.1003062.ref041) 2016; 7 Emerging Risk Factors Collaboration (pmed.1003062.ref059) 2009; 302 G Davey Smith (pmed.1003062.ref018) 2020 FJ Brunner (pmed.1003062.ref021) 2019; 394 M. Ala-Korpela (pmed.1003062.ref061) 2019; 48 P Wurtz (pmed.1003062.ref074) 2015; 131 BA Ference (pmed.1003062.ref026) 2019; 321 MJ Graham (pmed.1003062.ref064) 2017; 377 Cholesterol Treatment Trialists' Collaborators (pmed.1003062.ref003) 2012; 380 J Bowden (pmed.1003062.ref055) 2015; 44 S Mora (pmed.1003062.ref058) 2008; 118 C Bycroft (pmed.1003062.ref037) 2018; 562 Cholesterol Treatment Trialist's Collaborators (pmed.1003062.ref001) 2015; 385 S Burgess (pmed.1003062.ref051) 2019; 4 AD Sniderman (pmed.1003062.ref011) 2019; 4 A Varbo (pmed.1003062.ref016) 2013; 61 CC Chang (pmed.1003062.ref038) 2015; 4 JA Sterne (pmed.1003062.ref050) 2001; 322 MG Silverman (pmed.1003062.ref004) 2016; 316 CA Anderson (pmed.1003062.ref033) 2010; 5 M Nikpay (pmed.1003062.ref029) 2015; 47 JMB Rees (pmed.1003062.ref056) 2017; 36 RA Hegele (pmed.1003062.ref073) 2009; 10 R Collins (pmed.1003062.ref005) 2016; 388 KJ Williams (pmed.1003062.ref062) 1995; 15 1000 Genomes Project Consortium (pmed.1003062.ref039) 2012; 491 BA Ference (pmed.1003062.ref007) 2015; 65 MV Holmes (pmed.1003062.ref009) 2015; 36 SM Grundy (pmed.1003062.ref024) 2018; 139 FP Hartwig (pmed.1003062.ref054) 2017; 46 PR Loh (pmed.1003062.ref035) 2018; 50 MV Holmes (pmed.1003062.ref010) 2019; 16 Emerging Risk Factors Collaboration (pmed.1003062.ref020) 2012; 307 H. Wickham (pmed.1003062.ref047) 2016 BA Ference (pmed.1003062.ref015) 2017; 318 J Bowden (pmed.1003062.ref044) 2016; 45 PR Loh (pmed.1003062.ref034) 2015; 47 D Fry (pmed.1003062.ref032) 2019 J Bowden (pmed.1003062.ref053) 2016; 40 P Elliott (pmed.1003062.ref031) 2008; 37 F Mach (pmed.1003062.ref025) 2020; 41 MV Holmes (pmed.1003062.ref052) 2017; 14 JL Goldstein (pmed.1003062.ref071) 2015; 161 FE Dewey (pmed.1003062.ref063) 2016; 374 G Hemani (pmed.1003062.ref057) 2018; 27 BA Ference (pmed.1003062.ref008) 2012; 60 K Musunuru (pmed.1003062.ref065) 2010; 363 G Davey Smith (pmed.1003062.ref027) 2003; 32 V Amrhein (pmed.1003062.ref049) 2019; 567 R Do (pmed.1003062.ref014) 2013; 45 NM Davies (pmed.1003062.ref042) 2018; 362 |
| References_xml | – volume: 322 start-page: 226 issue: 7280 year: 2001 ident: pmed.1003062.ref050 article-title: Sifting the evidence-what's wrong with significance tests? publication-title: BMJ doi: 10.1136/bmj.322.7280.226 – year: 2019 ident: pmed.1003062.ref032 article-title: Companion Document to Accompany Serum Biomarker Data publication-title: UK Biobank Biomarker Project – volume: 36 start-page: 48 issue: 3 year: 2010 ident: pmed.1003062.ref048 article-title: Conducting Meta-Analyses in R with the metafor Package publication-title: Journal of Statistical Software doi: 10.18637/jss.v036.i03 – volume: 48 start-page: 713 issue: 3 year: 2019 ident: pmed.1003062.ref028 article-title: An examination of multivariable Mendelian randomization in the single sample and two-sample summary data settings publication-title: Int J Epidemiol doi: 10.1093/ije/dyy262 – volume: 44 start-page: 1223 issue: 11 year: 1991 ident: pmed.1003062.ref017 article-title: How independent are "independent" effects? Relative risk estimation when correlated exposures are measured imprecisely publication-title: J Clin Epidemiol doi: 10.1016/0895-4356(91)90155-3 – volume: 23 start-page: R89 issue: R1 year: 2014 ident: pmed.1003062.ref043 article-title: Mendelian randomization: genetic anchors for causal inference in epidemiological studies publication-title: Hum Mol Genet doi: 10.1093/hmg/ddu328 – volume: 32 start-page: 1 issue: 1 year: 2003 ident: pmed.1003062.ref027 article-title: 'Mendelian randomization': Can genetic epidemiology contribute to understanding environmental determinants of disease? publication-title: Int J Epidemiology doi: 10.1093/ije/dyg070 – volume: 318 start-page: 947 issue: 10 year: 2017 ident: pmed.1003062.ref015 article-title: Association of Genetic Variants Related to CETP Inhibitors and Statins With Lipoprotein Levels and Cardiovascular Risk publication-title: Jama doi: 10.1001/jama.2017.11467 – volume: 9 start-page: 224 issue: 1 year: 2018 ident: pmed.1003062.ref070 article-title: Causal associations between risk factors and common diseases inferred from GWAS summary data publication-title: Nat Commun doi: 10.1038/s41467-017-02317-2 – year: 2020 ident: pmed.1003062.ref045 article-title: Testing and Correcting for Weak Instruments in Two-sample Summary Data Multivariable Mendelian Randomisation publication-title: bioRxiv – volume: 394 start-page: 2173 issue: 10215 year: 2019 ident: pmed.1003062.ref021 article-title: Application of non-HDL cholesterol for population-based cardiovascular risk stratification: results from the Multinational Cardiovascular Risk Consortium publication-title: Lancet doi: 10.1016/S0140-6736(19)32519-X – volume: 161 start-page: 161 issue: 1 year: 2015 ident: pmed.1003062.ref071 article-title: A century of cholesterol and coronaries: from plaques to genes to statins publication-title: Cell doi: 10.1016/j.cell.2015.01.036 – volume: 380 start-page: 581 issue: 9841 year: 2012 ident: pmed.1003062.ref003 article-title: The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: meta-analysis of individual data from 27 randomised trials publication-title: Lancet doi: 10.1016/S0140-6736(12)60367-5 – volume: 321 start-page: 364 issue: 4 year: 2019 ident: pmed.1003062.ref026 article-title: Association of Triglyceride-Lowering LPL Variants and LDL-C-Lowering LDLR Variants With Risk of Coronary Heart Disease publication-title: Jama doi: 10.1001/jama.2018.20045 – volume: 4 start-page: 337 issue: 3 year: 2011 ident: pmed.1003062.ref019 article-title: A meta-analysis of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B as markers of cardiovascular risk publication-title: Circ Cardiovasc Qual Outcomes doi: 10.1161/CIRCOUTCOMES.110.959247 – volume: 16 start-page: 197 issue: 4 year: 2019 ident: pmed.1003062.ref010 article-title: What is 'LDL cholesterol'? publication-title: Nat Rev Cardiol doi: 10.1038/s41569-019-0157-6 – year: 2019 ident: pmed.1003062.ref036 article-title: MRC IEU UK Biobank GWAS pipeline version 2 publication-title: University of Bristol – volume: 47 start-page: 1121 issue: 10 year: 2015 ident: pmed.1003062.ref029 article-title: A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease publication-title: Nat Genet doi: 10.1038/ng.3396 – volume: 37 start-page: 234 issue: 2 year: 2008 ident: pmed.1003062.ref031 article-title: The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine publication-title: Int J Epidemiol doi: 10.1093/ije/dym276 – volume: 40 start-page: 304 issue: 4 year: 2016 ident: pmed.1003062.ref053 article-title: Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator publication-title: Genetic Epidemiology doi: 10.1002/gepi.21965 – volume: 7 start-page: e34408 year: 2018 ident: pmed.1003062.ref046 article-title: The MR-Base platform supports systematic causal inference across the human phenome publication-title: Elife doi: 10.7554/eLife.34408 – volume: 363 start-page: 2220 issue: 23 year: 2010 ident: pmed.1003062.ref065 article-title: Exome sequencing, ANGPTL3 mutations, and familial combined hypolipidemia publication-title: N Engl J Med doi: 10.1056/NEJMoa1002926 – volume: 46 start-page: 1985 issue: 6 year: 2017 ident: pmed.1003062.ref054 article-title: Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption publication-title: Int J Epidemiol doi: 10.1093/ije/dyx102 – volume: 45 start-page: 1961 issue: 6 year: 2016 ident: pmed.1003062.ref044 article-title: Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic publication-title: Int J Epidemiol – volume: 15 start-page: 551 issue: 5 year: 1995 ident: pmed.1003062.ref062 article-title: The response-to-retention hypothesis of early atherogenesis publication-title: Arterioscler Thromb Vasc Biol doi: 10.1161/01.ATV.15.5.551 – volume: 376 start-page: 1670 issue: 9753 year: 2010 ident: pmed.1003062.ref002 article-title: Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials publication-title: Lancet doi: 10.1016/S0140-6736(10)61350-5 – volume: 377 start-page: 222 issue: 3 year: 2017 ident: pmed.1003062.ref064 article-title: Cardiovascular and Metabolic Effects of ANGPTL3 Antisense Oligonucleotides publication-title: N Engl J Med doi: 10.1056/NEJMoa1701329 – volume: 4 start-page: 1287 issue: 12 year: 2019 ident: pmed.1003062.ref011 article-title: Apolipoprotein B Particles and Cardiovascular Disease: A Narrative Review publication-title: JAMA Cardiol doi: 10.1001/jamacardio.2019.3780 – volume: 45 start-page: 1274 issue: 11 year: 2013 ident: pmed.1003062.ref040 article-title: Discovery and refinement of loci associated with lipid levels publication-title: Nat Genet doi: 10.1038/ng.2797 – volume: 27 start-page: 473 issue: 5 year: 2016 ident: pmed.1003062.ref060 article-title: The central role of arterial retention of cholesterol-rich apolipoprotein-B-containing lipoproteins in the pathogenesis of atherosclerosis: a triumph of simplicity publication-title: Curr Opin Lipidol doi: 10.1097/MOL.0000000000000330 – volume: 374 start-page: 1123 issue: 12 year: 2016 ident: pmed.1003062.ref063 article-title: Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease publication-title: N Engl J Med doi: 10.1056/NEJMoa1510926 – volume: 60 start-page: 2631 issue: 25 year: 2012 ident: pmed.1003062.ref008 article-title: Effect of Long-Term Exposure to Lower Low-Density Lipoprotein Cholesterol Beginning Early in Life on the Risk of Coronary Heart Disease A Mendelian Randomization Analysis publication-title: Journal of the American College of Cardiology doi: 10.1016/j.jacc.2012.09.017 – volume: 4 start-page: 186 year: 2019 ident: pmed.1003062.ref051 article-title: Guidelines for performing Mendelian randomization investigations [version 1; peer review: awaiting peer review] publication-title: Wellcome Open Res doi: 10.12688/wellcomeopenres.15555.1 – volume: 118 start-page: 993 issue: 10 year: 2008 ident: pmed.1003062.ref058 article-title: Fasting compared with nonfasting lipids and apolipoproteins for predicting incident cardiovascular events publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.108.777334 – volume: 50 start-page: 906 issue: 7 year: 2018 ident: pmed.1003062.ref035 article-title: Mixed-model association for biobank-scale datasets publication-title: Nat Genet doi: 10.1038/s41588-018-0144-6 – volume: 7 start-page: 11122 year: 2016 ident: pmed.1003062.ref041 article-title: Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA publication-title: Nat Commun doi: 10.1038/ncomms11122 – volume: 48 start-page: 1389 issue: 5 year: 2019 ident: pmed.1003062.ref061 article-title: The culprit is the carrier, not the loads: cholesterol, triglycerides and apolipoprotein B in atherosclerosis and coronary heart disease publication-title: Int J Epidemiol doi: 10.1093/ije/dyz068 – volume: 140 start-page: 542 issue: 7 year: 2019 ident: pmed.1003062.ref022 article-title: Comparison of Conventional Lipoprotein Tests and Apolipoproteins in the Prediction of Cardiovascular Disease publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.119.041149 – volume: 377 start-page: 1217 issue: 13 year: 2017 ident: pmed.1003062.ref066 article-title: Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease publication-title: N Engl J Med doi: 10.1056/NEJMoa1706444 – year: 2020 ident: pmed.1003062.ref018 article-title: Correlation without a cause: an epidemiological odyssey publication-title: Int J Epidemiol. Forthcoming – volume: 316 start-page: 1289 issue: 12 year: 2016 ident: pmed.1003062.ref004 article-title: Association Between Lowering LDL-C and Cardiovascular Risk Reduction Among Different Therapeutic Interventions: A Systematic Review and Meta-analysis publication-title: Jama doi: 10.1001/jama.2016.13985 – volume: 5 start-page: 56 issue: 1 year: 2019 ident: pmed.1003062.ref072 article-title: Atherosclerosis publication-title: Nat Rev Dis Primers doi: 10.1038/s41572-019-0106-z – volume: 139 start-page: e1082 issue: 25 year: 2018 ident: pmed.1003062.ref024 article-title: AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines publication-title: Circulation – volume: 41 start-page: 111 issue: 1 year: 2020 ident: pmed.1003062.ref025 article-title: 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk publication-title: Eur Heart J doi: 10.1093/eurheartj/ehz455 – volume: 36 start-page: 4705 issue: 29 year: 2017 ident: pmed.1003062.ref056 article-title: Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy publication-title: Stat Med doi: 10.1002/sim.7492 – volume: 388 start-page: 2532 issue: 10059 year: 2016 ident: pmed.1003062.ref005 article-title: Interpretation of the evidence for the efficacy and safety of statin therapy publication-title: The Lancet doi: 10.1016/S0140-6736(16)31357-5 – volume: 4 start-page: 7 year: 2015 ident: pmed.1003062.ref038 article-title: Second-generation PLINK: rising to the challenge of larger and richer datasets publication-title: Gigascience doi: 10.1186/s13742-015-0047-8 – volume: 124 start-page: 1425 issue: 10 year: 2019 ident: pmed.1003062.ref012 article-title: ApoB publication-title: Circ Res doi: 10.1161/CIRCRESAHA.119.315019 – volume: 131 start-page: 774 issue: 9 year: 2015 ident: pmed.1003062.ref074 article-title: Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.114.013116 – volume: 362 start-page: k601 year: 2018 ident: pmed.1003062.ref042 article-title: Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians publication-title: BMJ doi: 10.1136/bmj.k601 – volume: 27 start-page: R195 issue: R2 year: 2018 ident: pmed.1003062.ref057 article-title: Evaluating the potential role of pleiotropy in Mendelian randomization studies publication-title: Hum Mol Genet doi: 10.1093/hmg/ddy163 – volume: 1 start-page: 692 issue: 6 year: 2016 ident: pmed.1003062.ref013 article-title: Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes publication-title: JAMA Cardiol doi: 10.1001/jamacardio.2016.1884 – volume: 307 start-page: 2499 issue: 23 year: 2012 ident: pmed.1003062.ref020 article-title: Lipid-related markers and cardiovascular disease prediction publication-title: Jama – volume: 65 start-page: 1552 issue: 15 year: 2015 ident: pmed.1003062.ref007 article-title: Effect of Naturally Random Allocation to Lower Low-Density Lipoprotein Cholesterol on the Risk of Coronary Heart Disease Mediated by Polymorphisms in NPC1L1, HMGCR, or Both publication-title: Journal of the American College of Cardiology doi: 10.1016/j.jacc.2015.02.020 – volume: 375 start-page: 2144 issue: 22 year: 2016 ident: pmed.1003062.ref006 article-title: Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes publication-title: New England Journal of Medicine doi: 10.1056/NEJMoa1604304 – volume: 61 start-page: 427 issue: 4 year: 2013 ident: pmed.1003062.ref016 article-title: Remnant cholesterol as a causal risk factor for ischemic heart disease publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2012.08.1026 – volume: 36 start-page: 1783 issue: 11 year: 2017 ident: pmed.1003062.ref069 article-title: A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization publication-title: Stat Med doi: 10.1002/sim.7221 – volume: 44 start-page: 512 issue: 2 year: 2015 ident: pmed.1003062.ref055 article-title: Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression publication-title: Int J Epidemiol doi: 10.1093/ije/dyv080 – volume-title: ggplot2 –Elegant Graphics for Data Analysis year: 2016 ident: pmed.1003062.ref047 – volume: 140 start-page: 553 issue: 7 year: 2019 ident: pmed.1003062.ref023 article-title: Cholesterol Insights and Controversies From the UK Biobank Study publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.119.042134 – volume: 380 start-page: 1076 year: 2019 ident: pmed.1003062.ref067 article-title: Human genetics and drug development publication-title: N Engl J Med doi: 10.1056/NEJMe1901565 – volume: 385 start-page: 1397 issue: 9976 year: 2015 ident: pmed.1003062.ref001 article-title: Efficacy and safety of LDL-lowering therapy among men and women: meta-analysis of individual data from 174,000 participants in 27 randomised trials publication-title: Lancet doi: 10.1016/S0140-6736(14)61368-4 – volume: 5 start-page: 1564 issue: 9 year: 2010 ident: pmed.1003062.ref033 article-title: Data quality control in genetic case-control association studies publication-title: Nat Protoc doi: 10.1038/nprot.2010.116 – volume: 3 start-page: 799 issue: 9 year: 2018 ident: pmed.1003062.ref068 article-title: Apolipoprotein A-I Infusion Therapies for Coronary Disease: Two Outs in the Ninth Inning and Swinging for the Fences publication-title: JAMA Cardiol doi: 10.1001/jamacardio.2018.2168 – volume: 47 start-page: 284 issue: 3 year: 2015 ident: pmed.1003062.ref034 article-title: Efficient Bayesian mixed-model analysis increases association power in large cohorts publication-title: Nat Genet doi: 10.1038/ng.3190 – volume: 10 start-page: 109 issue: 2 year: 2009 ident: pmed.1003062.ref073 article-title: Plasma lipoproteins: genetic influences and clinical implications publication-title: Nat Rev Genet doi: 10.1038/nrg2481 – volume: 45 start-page: 1345 issue: 11 year: 2013 ident: pmed.1003062.ref014 article-title: Common variants associated with plasma triglycerides and risk for coronary artery disease publication-title: Nat Genet doi: 10.1038/ng.2795 – volume: 36 start-page: 539 issue: 9 year: 2015 ident: pmed.1003062.ref009 article-title: Mendelian randomization of blood lipids for coronary heart disease publication-title: Eur Heart J doi: 10.1093/eurheartj/eht571 – volume: 491 start-page: 56 issue: 7422 year: 2012 ident: pmed.1003062.ref039 article-title: An integrated map of genetic variation from 1,092 human genomes publication-title: Nature doi: 10.1038/nature11632 – volume: 562 start-page: 203 issue: 7726 year: 2018 ident: pmed.1003062.ref037 article-title: The UK Biobank resource with deep phenotyping and genomic data publication-title: Nature doi: 10.1038/s41586-018-0579-z – volume: 14 start-page: 577 issue: 10 year: 2017 ident: pmed.1003062.ref052 article-title: Mendelian randomization in cardiometabolic disease: challenges in evaluating causality publication-title: Nat Rev Cardiol doi: 10.1038/nrcardio.2017.78 – volume: 12 start-page: e1001779 issue: 3 year: 2015 ident: pmed.1003062.ref030 article-title: UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age publication-title: PLoS Med doi: 10.1371/journal.pmed.1001779 – volume: 567 start-page: 305 issue: 7748 year: 2019 ident: pmed.1003062.ref049 article-title: Scientists rise up against statistical significance publication-title: Nature doi: 10.1038/d41586-019-00857-9 – volume: 302 start-page: 1993 issue: 18 year: 2009 ident: pmed.1003062.ref059 article-title: Major lipids, apolipoproteins, and risk of vascular disease publication-title: Jama doi: 10.1001/jama.2009.1619 |
| SSID | ssj0029090 |
| Score | 2.7172267 |
| Snippet | Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for... Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities... BackgroundCirculating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities... Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities... |
| SourceID | plos doaj pubmedcentral proquest pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | e1003062 |
| SubjectTerms | Adult Aged Apolipoprotein A Apolipoprotein A-I Apolipoprotein A-I - blood Apolipoprotein A-I - genetics Apolipoprotein B Apolipoprotein B-100 - blood Apolipoprotein B-100 - genetics Apolipoproteins Biology and Life Sciences Biomarkers - blood Cardiovascular disease Cholesterol Cholesterol, HDL - blood Cholesterol, HDL - genetics Cholesterol, LDL - blood Cholesterol, LDL - genetics Coronary artery disease Coronary Disease - blood Coronary Disease - diagnosis Coronary Disease - genetics Epidemiology Female Genetic Predisposition to Disease Genome-wide association studies Genome-Wide Association Study Genomes Heart diseases High density lipoprotein Humans Lipid metabolism Lipids Low density lipoprotein Male Medicine and Health Sciences Mendelian Randomization Analysis Middle Aged Multivariate Analysis Phenotype Polymorphism, Single Nucleotide Preventive medicine Risk Assessment Risk Factors Single-nucleotide polymorphism Standard deviation Triglycerides Triglycerides - blood |
| SummonAdditionalLinks | – databaseName: Publicly Available Content Database dbid: PIMPY link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Nb9MwGLagQ4gL32OBgYzENTSx4zjmggbaBIdOPYA0TpE_t0glKUk3if_Ej8Sv4waKJrhwq2pXSeon7_f7vAi9ElaWxFCessyWaUGVSZVUZSoEI5m10ishFYZN8NPT6uxMLGN79BDLKrcyMQjqke0Z6ra9EJ6bTkPEfE6KEpjdKl69XX9LYYYU5FrjQI2baA-It7IZ2lt-XCy_TA6YyELMBVjJ0pxwHlvpKM_n8eRer70OgsoBb0mTHVUVGP2BAXXVDddZo38WVf6mpU7u_d_nu4_uRmsVH43weoBu2PYhur2I-fhH6MdxJAtvz7G3JHG_La27aNY4loBh3fQ6DAnzm1bNugvUEE0LnxszYNkaLGFWxLQyYIgOY6h6x53DGkgWZP8dw_DtDY4ppTf4CIdqyCvv7UP_F15ANB-iNtjrX9N9jYVK_gIj78pj9Pnk-NP7D2mc_5BqRspNKjVnutC2ZMIoaBAmjjmtRGUo9Z5XZXVRGZ476xzJvJxW3lY1HmTO2MpBz-w-mrVdaw8QzqnzdlSliROqcFkmueQeAZZVVlieiwTR7VHXOpKjw4yOVR0yftw7SeM_XgNA6giQBKXTr9YjOcg_9r8DFE17gdo7fNH153WUFHXGDCPSyUJqWijFpCJMEkaodtoYLhN0ABjcXmCof2ElQYdbbF2__HJa9mcAmSHZ2u7S76Hey_SGfZ4l6MkI4-kmvcTPqH9jEsR3AL7zFLsrbXMRiMp5VomCkKd_v61n6A6BIEYo7DtEs01_aZ-jW_pq0wz9i_gO_wTYBGAl priority: 102 providerName: ProQuest – databaseName: Public Library of Science (PLoS) Journals Open Access dbid: FPL link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwELZQQYgLb2igICNxDTh2HMfcCuqKA616AKm3yE8aaUlWm20l_hM_kpnEG9iqFeIWxbbieMaep78h5K0OpuJeqFyyUOWlsD63xla51pKzEAwIITsWm1AnJ_XZmT79YyheieALVbxPa_puBdIBY_qg48KRe5uLqsJSDYvTL7OBpZlm6XrcTSN3xM-I0o-opst-uE7DvJoo-ZfkWTz43zk_JPeTjkkPJ6Z4RG6F7jG5e5yi6E_Ir6ME8d19p6D_0fU2Ie68XdGUuEVdu3ZjaS_otGxX_Qjo0Hb43PqBms5TgxUe5paBok-XYq467SN1CI1g1j8plsze0BQI-kAP6ZjDeAk2Ot7aosfog0dfCwWp6fsfKb0IPjChpTwl3xZHXz99zlPVhtxJXm1y45R0pQuV1N7itV4eZXRW114IsJfq4MraqyKGGDmD09WChumBNaIPdcSbrs_IXtd3YZ_QQkTQfmrHo7ZlZMwoowqugqyDDqrQGRFbYjYuQZpjZY1lM8bpFJg204o3SIgmESIj-TxqNUF6_KP_R-STuS8Cco8vgOJN2t8Nk15yE01pnCitlcZyaThY-S4675XJyD5y2fYDQ8PLCrEJa1Vn5GDLedc3v5mbgQYYzzFd6C-gjwDbENTxgmXk-cSo8yThnGYCbP-MqB0W3vmL3ZauPR_hxRWrdcn5i5tn_JLc4-h2GFPxDsjeZn0RXpE77nLTDuvX4578DXESP1o priority: 102 providerName: Public Library of Science |
| Title | Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/32203549 https://www.proquest.com/docview/2460793878 https://www.proquest.com/docview/2382656610 https://pubmed.ncbi.nlm.nih.gov/PMC7089422 https://doaj.org/article/05d52afa4ac34bb5ab25a2523cfcdd7a http://dx.doi.org/10.1371/journal.pmed.1003062 |
| Volume | 17 |
| WOSCitedRecordID | wos000558139500021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1549-1676 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029090 issn: 1549-1676 databaseCode: DOA dateStart: 20040101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1549-1676 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029090 issn: 1549-1676 databaseCode: 7X7 dateStart: 20041001 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1549-1676 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029090 issn: 1549-1676 databaseCode: BENPR dateStart: 20041001 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Publicly Available Content Database customDbUrl: eissn: 1549-1676 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029090 issn: 1549-1676 databaseCode: PIMPY dateStart: 20041001 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVATS databaseName: Public Library of Science (PLoS) Journals Open Access customDbUrl: eissn: 1549-1676 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029090 issn: 1549-1676 databaseCode: FPL dateStart: 20040101 isFulltext: true titleUrlDefault: http://www.plos.org/publications/ providerName: Public Library of Science |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1bi9QwFA66ivgi3re6DhF8rZumTdP4tiszKDjDIArjU0lzcQtjO8zMLvif_JGek2aGHVnYF19KaVLa5Jz2XPLlO4S8U06X3OYyFcyVaZE3Nm10U6ZKCc6c02CEmlBsQs5m1WKh5tdKfSEmbKAHHibulAkruPa60CYvmkbohgvNIXwy3lgrg2vEpNoFUzHUUixkV5B_LM24lHHTXC6z0yij9yuwNogRAJ-ZHxilwN2PXKfLfnOT3_kvfPKaPZo8Jo-iI0nPhgE8IXdc95Q8mMal8mfkzzjyeHc_KTh5dL1DvV20KxrRWdS0axPqd0GnZbvqA2tD2-F5azdUd5ZqLOOwb9lQTNxSBKTT3lOD_Ad6_ZtiXewtjas9H-gZDUDFKwjEcWsWnWKiHRMqFEyj7X9FDBE8YKBEeU6-T8bfPn5KY2mG1AheblNtpDCFcaVQtsG9u9wLbxpV2TyHoKhypqiszLzznjP4hTbgRlqQv7eu8rid9QU56vrOHROa5R5cnMpwr5rCM6alliAyJyqnnMxUQvKdbGoTecuxfMayDotxEuKXYcZrlGgdJZqQdH_XauDtuKX_OYp93xdZt8MF0MU66mJ9my4m5BiVZveATc2LEgkIK1kl5GSnSDc3v903gwxw0UZ3rr-EPjkEgOBzZywhLwe9278k_IxZDiqeEHmgkQejOGzp2ovAIS5ZpQrOX_2PYb8mDzlmIQIy74QcbdeX7g25b6627WY9InflQoZjNSL3zsez-ddR-FjhOJl_gWvzz9P5j78NSEzd |
| linkProvider | Directory of Open Access Journals |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwELbKFgEX3tBAASPBMTRxHk6QECrQqqt2V3soUjkFx4820pIsybao_wnxG5lJnMCiCk49cIvW3sRxvnnZ428IeZFqETMVcDfydOyGQa7cXOSxm6YR87QWYITyttgEn06To6N0tkZ-9GdhMK2y14mtolaVxDXyLRbGyOWW8OTt4quLVaNwd7UvodHBYl-ff4OQrXkz_gDf9yVjuzuH7_dcW1XAlRGLl66QPJKh1HGUqhyPnTITGZmniYLQPo0TLcNEcd9oY5gH0p-DB6Rg6EbpxOBJTLjvFbIeAti9EVmfjSezT0OIl3rtqg7ynrk-49we1gu4v2Wx8WoBVg5zE8BXZyvGsK0ZgByr86q5yN_9M23zNzu4e-t_m8Hb5Kb1uOl2JyJ3yJou75JrE5tTcI9837GE5-UxBW-Y1n164EmxoDaNjcqilm2hM-g0LxZVS29RlHhdqIaKUlGB9S6GlobiCjfFzH1aGSqRKELU5xQLiC-p3RZ7Tbdpm9F5JkAP5HNNJ7gjgStPFHwIVX2xyVbwgI475j75eClz9YCMyqrUG4T6gQFfMJHMpHloPE9wwQFjOkp0qrmfOiTowZRJS_COdUbmWbtrySHQ62Y8QwhmFoIOcYd_LTqCk3_0f4c4HfoiPXn7Q1UfZ1bbZV6kIiaMCIUMwjyPRM4iwSIWSCOV4sIhG4jy_gFN9gubDtns0Xtx8_OhGb4B7m6JUlen0CeASBmCE99zyMNOUIZBgtXyApBJh_AVEVp5i9WWsjhpyda5l6QhY4_-Pqxn5Pre4eQgOxhP9x-TGwwXZdpExU0yWtan-gm5Ks-WRVM_tRqDks-XLWI_AYnos_k |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwELZKiyouvKGBAkaCY9jEeThBQqilu6IqXa0QSL2ljh9tpCVZkm1R_xO_gF_HTOIEFlVw6oFbFDsvZ2Y84_n8DSEvUi1ipgLuRp6O3TDIlZuLPHbTNGKe1gImobwtNsGn0-ToKJ2tkR_9XhiEVfY2sTXUqpK4Rj5iYYxcbglPRsbCImZ7k7eLry5WkMJMa19OoxORA33xDcK35s3-Hvzrl4xNxp_evXdthQFXRixeukLySIZSx1GqctyCykxkZJ4mCsL8NE60DBPFfaONYR5Yghy8IQWfYZRODO7KhPteIxscLoXAb2N3PJ19HMK91GtXeJADzfUZ53bjXsD9kZWTVwuY8RCnAH47W5kY2_oByLc6r5rLfN8_IZy_zYmTW__zaN4mN60nTnc61blD1nR5l2weWqzBPfJ9bInQyxMKXjKte9jgabGgFt5GZVHLtgAadJoXi6qlvShKPC5UQ0WpqMA6GENLQ3HlmyKin1aGSiSQEPUFxcLiS2rTZa_pDm2RnucC7EM-1_QQMxW4IkXBt1DVFwvCggd0nDL3yecrGasHZL2sSr1FqB8Y8BETyUyah8bzBBcc5E1HiU4191OHBL1gZdISv2P9kXnWZjM5BIDdiGcojpkVR4e4w1WLjvjkH_13UWaHvkhb3p6o6pPMWsHMi1TEhBGhkEGY55HIWSRYxAJppFJcOGQLJb5_QJP9klOHbPeSfHnz86EZ_gFmvUSpqzPoE0AEDUGL7znkYac0w0vCbOYFoJ8O4SvqtPIVqy1lcdqSsHMvSUPGHv39tZ6RTdCr7MP-9OAxucFwrabFL26T9WV9pp-Q6_J8WTT1U2s8KDm-ag37CQjFvJM |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Evaluating+the+relationship+between+circulating+lipoprotein+lipids+and+apolipoproteins+with+risk+of+coronary+heart+disease%3A+A+multivariable+Mendelian+randomisation+analysis&rft.jtitle=PLoS+medicine&rft.au=Richardson%2C+Tom+G.&rft.au=Sanderson%2C+Eleanor&rft.au=Palmer%2C+Tom+M.&rft.au=Ala-Korpela%2C+Mika&rft.date=2020-03-01&rft.issn=1549-1676&rft.eissn=1549-1676&rft.volume=17&rft.issue=3&rft.spage=e1003062&rft_id=info:doi/10.1371%2Fjournal.pmed.1003062&rft.externalDBID=n%2Fa&rft.externalDocID=10_1371_journal_pmed_1003062 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1549-1676&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1549-1676&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1549-1676&client=summon |