7 results on '"Patel, Riyaz S"'
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2. Hiding in plain sight: supporting primary care to find familial hypercholesterolaemia and save lives
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Qureshi, Nadeem and Patel, Riyaz S
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Ldl cholesterol ,medicine.medical_specialty ,business.industry ,Genetic disorder ,High Cholesterol Levels ,Primary care ,Disease ,030204 cardiovascular system & hematology ,medicine.disease ,03 medical and health sciences ,Editorial ,0302 clinical medicine ,Premature atherosclerosis ,Electronic health record ,Medicine ,030212 general & internal medicine ,hyperlipidaemias ,Cardiology and Cardiovascular Medicine ,business ,Intensive care medicine ,Lipid clinic - Abstract
Familial hypercholesterolaemia (FH) is a relatively common genetic disorder, with affected individuals exhibiting a lifelong elevation of plasma low-density lipoprotein (LDL) cholesterol and a marked tendency to premature atherosclerosis and early-onset cardiovascular disease (CVD). However, unlike most genetic disorders, FH is wholly treatable, especially following the widespread availability of potent lipid-lowering agents such as statins. Indeed, early and sustained therapy to lower LDL cholesterol can normalise this risk and prevent premature CVD. With such enormous potential to prevent premature CVD, it is surprising then that only 7% of patients with FH are believed to have been identified in the UK. The picture is similar in many countries. In England, the NHS Long Term Plan has recently prioritised finding more of these undiagnosed patients and offering them treatment.1 Yet, the task of finding these people and their families, many of whom may be otherwise well, is enormously challenging for a multitude of reasons, one of which is lack of awareness of the diagnosis. The situation could be improved by supporting primary care to identify those with high cholesterol levels and clinical features of FH, offering them an evaluation to confirm diagnosis before moving on to find their relatives, half of whom may carry the same mutation. Brett et al in their study have shown that by simply using the current infrastructure of general practice, those affected by this condition can be successfully identified and treated.2 The primary care electronic health record (EHR) is of course the key game changer, enabling swift identification of people in whom the diagnosis may be likely. Several variations to the approach of using EHR to identify FH cases have been described as shown in figure 1. Options include systematically searching the records using established diagnostic criteria, such as Dutch Lipid Clinic Network (DLCN) …
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- 2021
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3. Genome-wide analysis identifies novel susceptibility loci for myocardial infarction
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Hartiala, Jaana A, Han, Yi, Jia, Qiong, Hilser, James R, Huang, Pin, Gukasyan, Janet, Schwartzman, William S, Cai, Zhiheng, Biswas, Subarna, Trégouët, David-Alexandre, Smith, Nicholas L, INVENT Consortium, CHARGE Consortium Hemostasis Working Group, GENIUS-CHD Consortium, Seldin, Marcus, Pan, Calvin, Mehrabian, Margarete, Lusis, Aldons J, Bazeley, Peter, Sun, Yan V, Liu, Chang, Quyyumi, Arshed A, Scholz, Markus, Thiery, Joachim, Delgado, Graciela E, Kleber, Marcus E, März, Winfried, Howe, Laurence J, Asselbergs, Folkert W, van Vugt, Marion, Vlachojannis, Georgios J, Patel, Riyaz S, Lyytikäinen, Leo-Pekka, Kähönen, Mika, Lehtimäki, Terho, Nieminen, Tuomo VM, Kuukasjärvi, Pekka, Laurikka, Jari O, Chang, Xuling, Heng, Chew-Kiat, Jiang, Rong, Kraus, William E, Hauser, Elizabeth R, Ferguson, Jane F, Reilly, Muredach P, Ito, Kaoru, Koyama, Satoshi, Kamatani, Yoichiro, Komuro, Issei, Biobank Japan, Stolze, Lindsey K, Romanoski, Casey E, Khan, Mohammad Daud, Turner, Adam W, Miller, Clint L, Aherrahrou, Redouane, Civelek, Mete, Ma, Lijiang, Björkegren, Johan LM, Kumar, S Ram, Tang, WH Wilson, Hazen, Stanley L, and Allayee, Hooman
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Genome-wide association study ,Aging ,Genetic factors ,SLC44A3 ,Clinical Sciences ,Myocardial Infarction ,INVENT Consortium ,Coronary Artery Disease ,Cardiorespiratory Medicine and Haematology ,Cardiovascular ,Japan ,Risk Factors ,Clinical Research ,Genetics ,Humans ,2.1 Biological and endogenous factors ,Genetic Predisposition to Disease ,CHARGE Consortium Hemostasis Working Group ,Polymorphism ,Aetiology ,Heart Disease - Coronary Heart Disease ,Human Genome ,Endothelial Cells ,Single Nucleotide ,Atherosclerosis ,Biobank Japan ,Meta-analysis ,Heart Disease ,GENIUS-CHD Consortium ,Cardiovascular System & Hematology - Abstract
AimsWhile most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation.Methods and resultsWe carried out a genome-wide association study for MI in the UK Biobank (n∼472000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165000) and 16 independent angiography-based cohorts (n∼27000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1β (vs. vehicle), and associated with smooth muscle cell migration in vitro.ConclusionsA large-scale analysis comprising ∼831000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.
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- 2021
4. Evaluation of cardiovascular risk in a lung cancer screening cohort
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Ruparel, Mamta, Quaife, Samantha L, Dickson, Jennifer L, Horst, Carolyn, Burke, Stephen, Taylor, Magali, Ahmed, Asia, Shaw, Penny, Soo, May-Jan, Nair, Arjun, Devaraj, Anand, O'Dowd, Emma Louise, Bhowmik, Angshu, Navani, Neal, Sennett, Karen, Duffy, Stephen W, Baldwin, David R, Sofat, Reecha, Patel, Riyaz S, Hingorani, Aroon, and Janes, Sam M
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Male ,Lung Neoplasms ,Lung Cancer ,Coronary Disease ,Middle Aged ,Radiation Dosage ,Risk Assessment ,Drug Utilization ,Cohort Studies ,Primary Prevention ,Cross-Sectional Studies ,Risk Factors ,Cardiovascular Diseases ,Humans ,Mass Screening ,Female ,cardiovascular diseases ,Prospective Studies ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,Tomography, X-Ray Computed ,Vascular Calcification ,Early Detection of Cancer ,Aged - Abstract
Introduction Lung cancer screening (LCS) by low-dose computed tomography (LDCT) offers an opportunity to impact both lung cancer and coronary heart disease mortality through detection of coronary artery calcification (CAC). Here, we explore the value of CAC and cardiovascular disease (CVD) risk assessment in LCS participants in the Lung Screen Uptake Trial (LSUT). Methods In this cross-sectional study, current and ex-smokers aged 60–75 were invited to a ‘lung health check’. Data collection included a CVD risk assessment enabling estimation of 10 year CVD risk using the QRISK2 score. Participants meeting the required lung cancer risk underwent an ungated, non-contrast LDCT. Descriptive data, bivariate associations and a multivariate analysis of predictors of statin use are presented. Results Of 1005 individuals enrolled, 680 were included in the final analysis. 421 (61.9%) had CAC present and in 49 (7.2%), this was heavy. 668 (98%) of participants had a QRISK2≥10% and QRISK2 was positively associated with increasing CAC grade (OR 4.29 (CI 0.93 to 19.88) for QRISK2=10%–20% and 12.29 (CI 2.68 to 56.1) for QRISK2≥20% respectively). Of those who qualified for statin primary prevention (QRISK2≥10%), 56.8% did not report a history of statin use. In the multivariate analysis statin use was associated with age, body mass index and history of hypertension and diabetes. Conclusions LCS offers an important opportunity for instituting CVD risk assessment in all LCS participants irrespective of the presence of LDCT-detected CAC. Further studies are needed to determine whether CAC could enhance uptake and adherence to primary preventative strategies.
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- 2018
5. Genome-wide association study identifies a sequence variant within the DAB2IP gene conferring susceptibility to abdominal aortic aneurysm
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Gretarsdottir, Solveig, Baas, Annette F., Thorleifsson, Gudmar, Holm, Hilma, den Heijer, Martin, de Vries, Jean-Paul P. M., Kranendonk, Steef E., Zeebregts, Clark J. A. M., van Sterkenburg, Steven M., Geelkerken, Robert H., van Rij, Andre M., Williams, Michael J. A., Boll, Albert P. M., Kostic, Jelena P., Jonasdottir, Adalbjorg, Jonasdottir, Aslaug, Walters, G. Bragi, Masson, Gisli, Sulem, Patrick, Saemundsdottir, Jona, Mouy, Magali, Magnusson, Kristinn P., Tromp, Gerard, Elmore, James R., Sakalihasan, Natzi, Limet, Raymond, Defraigne, Jean-Olivier, Ferrell, Robert E., Ronkainen, Antti, Ruigrok, Ynte M., Wijmenga, Cisca, Grobbee, Diederick E., Shah, Svati H., Granger, Christopher B., Quyyumi, Arshed A., Vaccarino, Viola, Patel, Riyaz S., Zafari, A. Maziar, Levey, Allan I., Austin, Harland, Girelli, Domenico, Pignatti, Pier Franco, Olivieri, Oliviero, Martinelli, Nicola, Malerba, Giovanni, Trabetti, Elisabetta, Becker, Lewis C., Becker, Diane M., Reilly, Muredach P., Rader, Daniel J., Mueller, Thomas, Dieplinger, Benjamin, Haltmayer, Meinhard, Urbonavicius, Sigitas, Lindblad, Bengt, Gottsater, Anders, Gaetani, Eleonora, Pola, Roberto, Wells, Philip, Rodger, Marc, Forgie, Melissa, Langlois, Nicole, Corral, Javier, Vicente, Vicente, Fontcuberta, Jordi, Espana, Francisco, Grarup, Niels, Jorgensen, Torben, Witte, Daniel R., Hansen, Torben, Pedersen, Oluf, Aben, Katja K., de Graaf, Jacqueline, Holewijn, Suzanne, Folkersen, Lasse, Franco-Cereceda, Anders, Eriksson, Per, Collier, David A., Stefansson, Hreinn, Steinthorsdottir, Valgerdur, Rafnar, Thorunn, Valdimarsson, Einar M., Magnadottir, Hulda B., Sveinbjornsdottir, Sigurlaug, Olafsson, Isleifur, Magnusson, Magnus Karl, Palmason, Robert, Haraldsdottir, Vilhelmina, Andersen, Karl, Onundarson, Pall T., Thorgeirsson, Gudmundur, Kiemeney, Lambertus A., Powell, Janet T., Carey, David J., Kuivaniemi, Helena, Lindholt, Jes S., Jones, Gregory T., Kong, Augustine, Blankensteijn, Jan D., Matthiasson, Stefan E., Thorsteinsdottir, Unnur, and Stefansson, Kari
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- 2010
6. Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9
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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.
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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.
7. Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9
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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
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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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