12 results on '"Hansson, Markus"'
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2. Additional file 1: of Eosinophils in anti-neutrophil cytoplasmic antibody associated vasculitis
- Author
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Hellmark, Thomas, Ohlsson, Sophie, Ă Sa Pettersson, Hansson, Markus, and Ă Sa Johansson
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respiratory system - Abstract
Production of reactive oxygen species (ROS) in eosinophils. Cell aggregates were excluded based on forward scatter height and area properties, then granulocytes were gated based on their forward and side scatter. Eosinophils (in red) were defined as Siglec-8+ granulocytes. It was possible to select eosinophils also by their forward and side scatter characteristics. Intracellular production of ROS was measured as the geometric median fluorescence intensity in eosinophils (red) as a comparison typical graphs of ROS production in neutrophils are shown to the left (green). The two top histograms show unstimulated (PBS) cells and the bottom two histograms show cells activated with phorbol-12-myristate-13-acetate (PMA). (PDF 141 kb)
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- 2019
- Full Text
- View/download PDF
3. Additional file 3: of Eosinophils in anti-neutrophil cytoplasmic antibody associated vasculitis
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Hellmark, Thomas, Ohlsson, Sophie, Pettersson, Åsa, Hansson, Markus, and Johansson, Åsa
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parasitic diseases ,hemic and immune systems - Abstract
The percentage of eosinophils of polymorphonuclear leukocytes (PMN) and basophils of the leukocytes populations is shown when the patients are divided into active and inactive (A and B) or into GPA or MPA (C and D). Patients with active disease had lower levels of both eosinophils and basophils but no difference were seen comparing GPA and MPA. Kruskal-Wallis test and Dunn’s multiple comparisons test was used to calculate the level of significance between the three groups. Values are reported as median ± IQR. (PDF 86 kb)
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- 2019
- Full Text
- View/download PDF
4. Additional file 2: of Eosinophils in anti-neutrophil cytoplasmic antibody associated vasculitis
- Author
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Hellmark, Thomas, Ohlsson, Sophie, Pettersson, Åsa, Hansson, Markus, and Johansson, Åsa
- Subjects
respiratory system - Abstract
Cytospin preparations of purified neutrophils and eosinophils stained with May-Grünwald Giemsa. In the first set of experiment neutrophils and eosinophils were isolated using Histopaque 1119 (Sigma) followed by Percoll (GE Healthcare) and thereafter the eosinophils were separated from the granulocytes using MACS Eosinophil Isolation Kit (Miltenyi Biotech). The cells that were removed from during the eosinophil purification step were regarded as neutrophils (A) and the ones that remained as eosinophils (B). In the second part of the experiment eosinophils were purified using the MACSXpress® Eosinophil Isolation kit (Miltenyi Biotech) (C). (PDF 199 kb)
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- 2019
- Full Text
- View/download PDF
5. Additional file 5: of Eosinophils in anti-neutrophil cytoplasmic antibody associated vasculitis
- Author
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Hellmark, Thomas, Ohlsson, Sophie, Pettersson, Åsa, Hansson, Markus, and Johansson, Åsa
- Abstract
Light microscopy picture of two eosinophils that has formed EETs after incubation with PMA for 3 h at 37 °C and 5%CO2. The white arrow indicates the web formed by the DNA and the black arrows indicate the intact granules that remains around the plasma membrane remnants. (PDF 263 kb)
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- 2019
- Full Text
- View/download PDF
6. Additional file 4: of Eosinophils in anti-neutrophil cytoplasmic antibody associated vasculitis
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Hellmark, Thomas, Ohlsson, Sophie, Pettersson, Åsa, Hansson, Markus, and Johansson, Åsa
- Abstract
The level of surface expression on eosinophils of A CD16, B CD64, C CD35, D CD193, E CD62L, F CD88, G Siglec-8, H CD11b and I CD11c was measured in healthy blood donors (HBD) and compared to anti-neutrophil cytoplasmic antibodies associated vasculitides (AAV) patients, divided into GPA and MPA patients, using flow cytometry and reported as geometric mean fluorescence intensity (MFI). Kruskal-Wallis test and Dunn’s multiple comparisons test was used to calculate the level of significance between the three groups. Values are reported as median ± IQR. No difference was seen between the GPA and MPA groups. (PDF 95 kb)
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- 2019
- Full Text
- View/download PDF
7. Additional file 2: of Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9
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Schmidt, Amand, Holmes, Michael, Preiss, David, Swerdlow, Daniel, Denaxas, Spiros, Ghazaleh Fatemifar, Faraway, Rupert, Finan, Chris, Valentine, Dennis, Zammy Fairhurst-Hunter, Hartwig, Fernando, Horta, Bernardo, Hypponen, Elina, Power, Christine, Moldovan, Max, Iperen, Erik, Hovingh, Kees, Demuth, Ilja, Norman, Kristina, Steinhagen-Thiessen, Elisabeth, Demuth, Juri, Bertram, Lars, Lill, Christina, Coassin, Stefan, Willeit, Johann, Kiechl, Stefan, Willeit, Karin, Mason, Dan, Wright, John, Morris, Richard, Goya Wanamethee, Whincup, Peter, Ben-Shlomo, Yoav, McLachlan, Stela, Price, Jackie, Kivimaki, Mika, Welch, Catherine, Sanchez-Galvez, Adelaida, Marques-Vidal, Pedro, Nicolaides, Andrew, Andrie Panayiotou, N. Onland-Moret, Schouw, Yvonne, Matullo, Giuseppe, Fiorito, Giovanni, Guarrera, Simonetta, Sacerdote, Carlotta, Wareham, Nicholas, Langenberg, Claudia, Scott, Robert, JianâAn Luan, Bobak, Martin, Malyutina, Sofia, K, Andrzej PajÄ, Ruzena Kubinova, Abdonas Tamosiunas, Pikhart, Hynek, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Jess, Tine, Cooper, Jackie, Humphries, Steve, Brilliant, Murray, Kitchner, Terrie, Hakon Hakonarson, Carrell, David, McCarty, Catherine, Kirchner Lester, Larson, Eric, Crosslin, David, Mariza Andrade, Roden, Dan, Denny, Joshua, Carty, Cara, Hancock, Stephen, Attia, John, Holliday, Elizabeth, Scott, Rodney, Schofield, Peter, OâDonnell, Martin, Yusuf, Salim, Chong, Michael, Pare, Guillaume, Harst, Pim, M. Said, Eppinga, Ruben, Verweij, Niek, Snieder, Harold, Christen, Tim, D. Mook-Kanamori, Gustafsson, Stefan, Lind, Lars, Ingelsson, Erik, Raha Pazoki, Franco, Oscar, Hofman, Albert, Uitterlinden, Andre, Dehghan, Abbas, Teumer, Alexander, Baumeister, Sebastian, DĂśrr, Marcus, Lerch, Markus, VĂślker, Uwe, VĂślzke, Henry, Ward, Joey, Pell, Jill, Meade, Tom, Christophersen, Ingrid, Zee, Anke Maitland-Van Der, Baranova, Ekaterina, Young, Robin, Ford, Ian, Campbell, Archie, Sandosh Padmanabhan, Bots, Michiel, Grobbee, Diederick, Froguel, Philippe, DorothĂŠe Thuillier, Roussel, Ronan, AmĂŠlie Bonnefond, Cariou, Bertrand, Smart, Melissa, Yanchun Bao, Kumari, Meena, Anubha Mahajan, Hopewell, Jemma, Seshadri, Sudha, Dale, Caroline, Costa, Rui, Ridker, Paul, Chasman, Daniel, Reiner, Alex, Ritchie, Marylyn, Lange, Leslie, Cornish, Alex, Dobbins, Sara, Hemminki, Kari, Kinnersley, Ben, Sanson, Marc, Labreche, Karim, Simon, Matthias, Bondy, Melissa, Law, Philip, Speedy, Helen, Allan, James, Li, Ni, Went, Molly, Weinhold, Niels, Morgan, Gareth, Sonneveld, Pieter, BjĂśrn Nilsson, Goldschmidt, Hartmut, Sud, Amit, Engert, Andreas, Hansson, Markus, Hemingway, Harry, Asselbergs, Folkert, Riyaz Patel, Keating, Brendan, Sattar, Naveed, Houlston, Richard, Casas, Juan, and Aroon Hingorani
- Abstract
Supplemental figures and study acknowledgments. (PDF 154 kb)
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- 2019
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8. Additional file 1: of Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
- Author
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Went, Molly, Kinnersley, Ben, Sud, Amit, Johnson, David, Weinhold, Niels, FĂśrsti, Asta, Duin, Mark, Orlando, Giulia, Mitchell, Jonathan, Kuiper, Rowan, Walker, Brian, Gregory, Walter, Hoffmann, Per, Jackson, Graham, NĂśthen, Markus, Filho, Miguel Silva, Thomsen, Hauke, Broyl, Annemiek, Davies, Faith, Thorsteinsdottir, Unnur, Hansson, Markus, Kaiser, Martin, Sonneveld, Pieter, Goldschmidt, Hartmut, Stefansson, Kari, Hemminki, Kari, BjĂśrn Nilsson, Morgan, Gareth, and Houlston, Richard
- Abstract
Table S1. Genes significantly associated with risk of multiple myeloma. Table S2. New and previously implicated1-5 genes at each genome wide significant multiple myeloma locus. Table S3. Quality control filters applied to samples from the seven published GWAS. Table S4. Quality control filters applied to SNPs from each GWAS. Table S5. MM GWAS risk SNPs. Figure S1. Quantile-Quantile Plots of â log10(P-value) associations. Figure S2. TWAS power plot in EBV-transformed lymphocytes. (DOCX 1515 kb)
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- 2019
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9. Genetic correlation between multiple myeloma and chronic lymphocytic leukaemia provides evidence for shared aetiology
- Author
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Went, Molly, Sud, Amit, Speedy, Helen, Sunter, Nicola J., Försti, Asta, Law, Philip J., Johnson, David C., Mirabella, Fabio, Holroyd, Amy, Li, Ni, Orlando, Giulia, Weinhold, Niels, van Duin, Mark, Chen, Bowang, Mitchell, Jonathan S., Mansouri, Larry, Juliusson, Gunnar, Smedby, Karin E, Jayne, Sandrine, Majid, Aneela, Dearden, Claire, Allsup, David J., Bailey, James R., Pratt, Guy, Pepper, Chris, Fegan, Chris, Rosenquist, Richard, Kuiper, Rowan, Stephens, Owen W., Bertsch, Uta, Broderick, Peter, Einsele, Hermann, Gregory, Walter M., Hillengass, Jens, Hoffmann, Per, Jackson, Graham H., Jöckel, Karl-Heinz, Nickel, Jolanta, Nöthen, Markus M., da Silva Filho, Miguel Inacio, Thomsen, Hauke, Walker, Brian A., Broyl, Annemiek, Davies, Faith E., Hansson, Markus, Goldschmidt, Hartmut, Dyer, Martin J. S., Kaiser, Martin, Sonneveld, Pieter, Morgan, Gareth J., Hemminki, Kari, Nilsson, Björn, Catovsky, Daniel, Allan, James M., Houlston, Richard S., and Hematology
- Subjects
Cancer och onkologi ,Genetic Linkage ,Quantitative Trait Loci ,Medizin ,Hematology ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,lcsh:RC254-282 ,Leukemia, Lymphocytic, Chronic, B-Cell ,Polymorphism, Single Nucleotide ,Article ,Linkage Disequilibrium ,Organ Specificity ,Cancer and Oncology ,hemic and lymphatic diseases ,Case-Control Studies ,Databases, Genetic ,Humans ,Genetic Predisposition to Disease ,Hematologi ,Multiple Myeloma ,Alleles ,Genetic Association Studies ,Genome-Wide Association Study - Abstract
The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (R g = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies.
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- 2018
10. Additional file 1: of Impaired phagocytosis and reactive oxygen species production in phagocytes is associated with systemic vasculitis
- Author
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Ă Sa Johansson, Ohlsson, Sophie, Ă Sa Pettersson, Bengtsson, Anders, Selga, Daina, Hansson, Markus, and Hellmark, Thomas
- Abstract
Gating strategies. (DOCX 188 kb)
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- 2016
- Full Text
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11. Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9
- Author
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Schmidt, Amand F., Holmes, Michael V., Preiss, David, Swerdlow, Daniel I., Denaxas, Spiros, Fatemifar, Ghazaleh, Faraway, Rupert, Finan, Chris, Valentine, Dennis, Fairhurst-Hunter, Zammy, Hartwig, Fernando Pires, Horta, Bernardo Lessa, Hypponen, Elina, Power, Christine, Moldovan, Max, Van Iperen, Erik, Hovingh, Kees, Demuth, Ilja, Norman, Kristina, Steinhagen-Thiessen, Elisabeth, Demuth, Juri, Bertram, Lars, Lill, Christina M., Coassin, Stefan, Willeit, Johann, Kiechl, Stefan, Willeit, Karin, Mason, Dan, Wright, John, Morris, Richard, Wanamethee, Goya, Whincup, Peter, Ben-Shlomo, Yoav, McLachlan, Stela, Price, Jackie F., Kivimaki, Mika, Welch, Catherine, Sanchez-Galvez, Adelaida, Marques-Vidal, Pedro, Nicolaides, Andrew, Panayiotou, Andrie G., Onland-Moret, N. Charlotte, Van Der Schouw, Yvonne T., Matullo, Giuseppe, Fiorito, Giovanni, Guarrera, Simonetta, Sacerdote, Carlotta, Wareham, Nicholas J., Langenberg, Claudia, Scott, Robert A., Luan, Jian’an, Bobak, Martin, Malyutina, Sofia, Pająk, Andrzej, Kubinova, Ruzena, Tamosiunas, Abdonas, Pikhart, Hynek, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Jess, Tine, Cooper, Jackie, Humphries, Steve E., Brilliant, Murray, Kitchner, Terrie, Hakonarson, Hakon, Carrell, David S., McCarty, Catherine A., Lester, Kirchner H., Larson, Eric B., Crosslin, David R., De Andrade, Mariza, Roden, Dan M., Denny, Joshua C., Carty, Cara, Hancock, Stephen, Attia, John, Holliday, Elizabeth, Scott, Rodney, Schofield, Peter, O’Donnell, Martin, Yusuf, Salim, Chong, Michael, Pare, Guillaume, Van Der Harst, Pim, Said, M. Abdullah, Eppinga, Ruben N., Verweij, Niek, Snieder, Harold, Christen, Tim, Mook-Kanamori, D. O., Gustafsson, Stefan, Lind, Lars, Ingelsson, Erik, Pazoki, Raha, Franco, Oscar, Hofman, Albert, Uitterlinden, Andre, Dehghan, Abbas, Teumer, Alexander, Baumeister, Sebastian, Dörr, Marcus, Lerch, Markus M., Völker, Uwe, Völzke, Henry, Ward, Joey, Pell, Jill P., Meade, Tom, Christophersen, Ingrid E., Maitland-Van Der Zee, Anke H., Baranova, Ekaterina V., Young, Robin, Ford, Ian, Campbell, Archie, Padmanabhan, Sandosh, Bots, Michiel L., Grobbee, Diederick E., Froguel, Philippe, Thuillier, Dorothée, Roussel, Ronan, Bonnefond, Amélie, Cariou, Bertrand, Smart, Melissa, Bao, Yanchun, Kumari, Meena, Mahajan, Anubha, Hopewell, Jemma C., Seshadri, Sudha, Dale, Caroline, Costa, Rui Providencia E., Ridker, Paul M., Chasman, Daniel I., Reiner, Alex P., Ritchie, Marylyn D., Lange, Leslie A., Cornish, Alex J., Dobbins, Sara E., Hemminki, Kari, Kinnersley, Ben, Sanson, Marc, Labreche, Karim, Simon, Matthias, Bondy, Melissa, Law, Philip, Speedy, Helen, Allan, James, Li, Ni, Went, Molly, Weinhold, Niels, Morgan, Gareth, Sonneveld, Pieter, Nilsson, Björn, Goldschmidt, Hartmut, Sud, Amit, Engert, Andreas, Hansson, Markus, Hemingway, Harry, Asselbergs, Folkert W., Patel, Riyaz S., Keating, Brendan J., Sattar, Naveed, Houlston, Richard, Casas, Juan P., and Hingorani, Aroon D.
- Subjects
Genetic association studies ,LDL-cholesterol ,Phenome-wide association scan ,Mendelian randomisation ,Coronary artery disease ,3. Good health ,Research Article - Abstract
Background: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. Methods: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. Results: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer’s disease – outcomes for which large-scale trial data were unavailable. Conclusions: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.
12. Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9
- Author
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Schmidt, Amand F, Holmes, Michael V, Preiss, David, Swerdlow, Daniel I, Denaxas, Spiros, Fatemifar, Ghazaleh, Faraway, Rupert, Finan, Chris, Valentine, Dennis, Fairhurst-Hunter, Zammy, Hartwig, Fernando Pires, Horta, Bernardo Lessa, Hypponen, Elina, Power, Christine, Moldovan, Max, Van Iperen, Erik, Hovingh, Kees, Demuth, Ilja, Norman, Kristina, Steinhagen-Thiessen, Elisabeth, Demuth, Juri, Bertram, Lars, Lill, Christina M, Coassin, Stefan, Willeit, Johann, Kiechl, Stefan, Willeit, Karin, Mason, Dan, Wright, John, Morris, Richard, Wanamethee, Goya, Whincup, Peter, Ben-Shlomo, Yoav, McLachlan, Stela, Price, Jackie F, Kivimaki, Mika, Welch, Catherine, Sanchez-Galvez, Adelaida, Marques-Vidal, Pedro, Nicolaides, Andrew, Panayiotou, Andrie G, Onland-Moret, N Charlotte, Van Der Schouw, Yvonne T, Matullo, Giuseppe, Fiorito, Giovanni, Guarrera, Simonetta, Sacerdote, Carlotta, Wareham, Nicholas J, Langenberg, Claudia, Scott, Robert A, Luan, Jian'an, Bobak, Martin, Malyutina, Sofia, Pająk, Andrzej, Kubinova, Ruzena, Tamosiunas, Abdonas, Pikhart, Hynek, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Jess, Tine, Cooper, Jackie, Humphries, Steve E, Brilliant, Murray, Kitchner, Terrie, Hakonarson, Hakon, Carrell, David S, McCarty, Catherine A, Lester, Kirchner H, Larson, Eric B, Crosslin, David R, De Andrade, Mariza, Roden, Dan M, Denny, Joshua C, Carty, Cara, Hancock, Stephen, Attia, John, Holliday, Elizabeth, Scott, Rodney, Schofield, Peter, O'Donnell, Martin, Yusuf, Salim, Chong, Michael, Pare, Guillaume, Van Der Harst, Pim, Said, M Abdullah, Eppinga, Ruben N, Verweij, Niek, Snieder, Harold, Lifelines Cohort Authors, Christen, Tim, Mook-Kanamori, DO, ICBP Consortium, Gustafsson, Stefan, Lind, Lars, Ingelsson, Erik, Pazoki, Raha, Franco, Oscar, Hofman, Albert, Uitterlinden, Andre, Dehghan, Abbas, Teumer, Alexander, Baumeister, Sebastian, Dörr, Marcus, Lerch, Markus M, Völker, Uwe, Völzke, Henry, Ward, Joey, Pell, Jill P, Meade, Tom, Christophersen, Ingrid E, Maitland-Van Der Zee, Anke H, Baranova, Ekaterina V, Young, Robin, Ford, Ian, Campbell, Archie, Padmanabhan, Sandosh, Bots, Michiel L, Grobbee, Diederick E, Froguel, Philippe, Thuillier, Dorothée, Roussel, Ronan, Bonnefond, Amélie, Cariou, Bertrand, Smart, Melissa, Bao, Yanchun, Kumari, Meena, Mahajan, Anubha, Hopewell, Jemma C, Seshadri, Sudha, METASTROKE Consortium Of The ISGC, Dale, Caroline, Costa, Rui Providencia E, Ridker, Paul M, Chasman, Daniel I, Reiner, Alex P, Ritchie, Marylyn D, Lange, Leslie A, Cornish, Alex J, Dobbins, Sara E, Hemminki, Kari, Kinnersley, Ben, Sanson, Marc, Labreche, Karim, Simon, Matthias, Bondy, Melissa, Law, Philip, Speedy, Helen, Allan, James, Li, Ni, Went, Molly, Weinhold, Niels, Morgan, Gareth, Sonneveld, Pieter, Nilsson, Björn, Goldschmidt, Hartmut, Sud, Amit, Engert, Andreas, Hansson, Markus, Hemingway, Harry, Asselbergs, Folkert W, Patel, Riyaz S, Keating, Brendan J, Sattar, Naveed, Houlston, Richard, Casas, Juan P, and Hingorani, Aroon D
- Subjects
Genetic association studies ,Serine Proteinase Inhibitors ,Anticholesteremic Agents ,PCSK9 Inhibitors ,Myocardial Infarction ,Down-Regulation ,Cholesterol, LDL ,Polymorphism, Single Nucleotide ,Risk Assessment ,3. Good health ,Brain Ischemia ,Stroke ,Treatment Outcome ,Risk Factors ,LDL-cholesterol ,Humans ,Phenome-wide association scan ,Proprotein Convertase 9 ,Mendelian randomisation ,Biomarkers ,Dyslipidemias ,Genome-Wide Association Study ,Randomized Controlled Trials as Topic - Abstract
BACKGROUND: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. METHODS: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. RESULTS: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable. CONCLUSIONS: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.
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