Literature DB >> 27940953

Genetic invalidation of Lp-PLA2 as a therapeutic target: Large-scale study of five functional Lp-PLA2-lowering alleles.

John M Gregson1, Daniel F Freitag1, Praveen Surendran1, Nathan O Stitziel2, Rajiv Chowdhury1, Stephen Burgess1, Stephen Kaptoge1, Pei Gao1, James R Staley1, Peter Willeit3,4, Sune F Nielsen5, Muriel Caslake6, Stella Trompet7, Linda M Polfus8, Kari Kuulasmaa9, Jukka Kontto9, Markus Perola10,11, Stefan Blankenberg12,13, Giovanni Veronesi14, Francesco Gianfagna14,15, Satu Männistö9, Akinori Kimura16, Honghuang Lin17,18, Dermot F Reilly19, Mathias Gorski20,21, Vladan Mijatovic22, Patricia B Munroe23,24, Georg B Ehret25,26,27, Alex Thompson28, Maria Uria-Nickelsen29, Anders Malarstig30, Abbas Dehghan31, Thomas F Vogt32,33, Taishi Sasaoka16, Fumihiko Takeuchi34, Norihiro Kato34, Yoshiji Yamada35, Frank Kee36, Martina Müller-Nurasyid37,38,39,40, Jean Ferrières41, Dominique Arveiler42, Philippe Amouyel43, Veikko Salomaa9, Eric Boerwinkle44, Simon G Thompson1, Ian Ford6, J Wouter Jukema7, Naveed Sattar6, Chris J Packard6, Abdulla Al Shafi Majumder45, Dewan S Alam46, Panos Deloukas47, Heribert Schunkert39,48, Nilesh J Samani49, Sekar Kathiresan50, Børge G Nordestgaard5, Danish Saleheen51, Joanna Mm Howson1, Emanuele Di Angelantonio1, Adam S Butterworth1, John Danesh1,52,53,54.   

Abstract

Aims Darapladib, a potent inhibitor of lipoprotein-associated phospholipase A2 (Lp-PLA2), has not reduced risk of cardiovascular disease outcomes in recent randomized trials. We aimed to test whether Lp-PLA2 enzyme activity is causally relevant to coronary heart disease. Methods In 72,657 patients with coronary heart disease and 110,218 controls in 23 epidemiological studies, we genotyped five functional variants: four rare loss-of-function mutations (c.109+2T > C (rs142974898), Arg82His (rs144983904), Val279Phe (rs76863441), Gln287Ter (rs140020965)) and one common modest-impact variant (Val379Ala (rs1051931)) in PLA2G7, the gene encoding Lp-PLA2. We supplemented de-novo genotyping with information on a further 45,823 coronary heart disease patients and 88,680 controls in publicly available databases and other previous studies. We conducted a systematic review of randomized trials to compare effects of darapladib treatment on soluble Lp-PLA2 activity, conventional cardiovascular risk factors, and coronary heart disease risk with corresponding effects of Lp-PLA2-lowering alleles. Results Lp-PLA2 activity was decreased by 64% ( p = 2.4 × 10-25) with carriage of any of the four loss-of-function variants, by 45% ( p < 10-300) for every allele inherited at Val279Phe, and by 2.7% ( p = 1.9 × 10-12) for every allele inherited at Val379Ala. Darapladib 160 mg once-daily reduced Lp-PLA2 activity by 65% ( p < 10-300). Causal risk ratios for coronary heart disease per 65% lower Lp-PLA2 activity were: 0.95 (0.88-1.03) with Val279Phe; 0.92 (0.74-1.16) with carriage of any loss-of-function variant; 1.01 (0.68-1.51) with Val379Ala; and 0.95 (0.89-1.02) with darapladib treatment. Conclusions In a large-scale human genetic study, none of a series of Lp-PLA2-lowering alleles was related to coronary heart disease risk, suggesting that Lp-PLA2 is unlikely to be a causal risk factor.

Entities:  

Keywords:  Human genetics; coronary heart disease; darapladib; lipoprotein-associated phospholipase A2; target validation

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Substances:

Year:  2016        PMID: 27940953      PMCID: PMC5460752          DOI: 10.1177/2047487316682186

Source DB:  PubMed          Journal:  Eur J Prev Cardiol        ISSN: 2047-4873            Impact factor:   7.804


Introduction

Lipoprotein-associated phospholipase A2 (Lp-PLA2), an enzyme expressed by inflammatory cells in atherosclerotic plaques, is carried in the circulation bound predominantly to low-density lipoprotein (LDL).[1,2] Lp-PLA2 (also called platelet-activating factor acetyl hydrolase) hydrolyses oxidized phospholipids to yield pro-inflammatory products implicated in endothelial dysfunction, plaque inflammation and formation of necrotic core in plaque.[1] Observational[3] and experimental studies in humans and animals have suggested that Lp-PLA2 could be a valid therapeutic target, postulating this enzyme to link oxidative modification of LDL and development of inflammatory responses to arterial intima.[1] Previous studies have investigated genetic variants altering Lp-PLA2 function in relation to coronary heart disease (CHD) risk.[4,5] However, these studies have generally yielded inconclusive, or conflicting results,[4,5] perhaps due to limited statistical power and due to limited knowledge about variants altering Lp-PLA2 function (e.g. previous studies have been able to consider only one loss-of-function variant in PLA2G7, the gene encoding Lp-PLA2). However, two phase 3 randomized trials of darapladib, a potent inhibitor of Lp-PLA2 activity, have not shown reductions in cardiovascular risk.[6,7] These results could, at least in part, have been due to features of the trials. One of the phase 3 trials was restricted to patients recently hospitalized with acute coronary syndromes,[6] yet many cardiovascular events occurring early after acute coronary syndromes may relate to thrombotic mechanisms and not be modifiable through Lp-PLA2 inhibition. Trials used statins as background therapy, so any Lp-PLA2 inhibition achieved with statins could have reduced any incremental benefits of darapladib. Trials could not assess the effects of prolonged Lp-PLA2 inhibition because they recorded only about 3–4 years of median follow-up.[6,7] An alternative explanation is that darapladib did not reduce cardiovascular risk because Lp-PLA2 is not a causal risk factor in cardiovascular disease. We tested this possibility by investigating natural loss of Lp-PLA2 activity. Studies of Lp-PLA2-lowering alleles should complement randomized trials of darapladib because genotypes are fixed at conception, avoiding potential distorting effects of pre-existing disease and medication usage. Furthermore, Lp-PLA2-lowering alleles should produce lifelong, rather than shorter-term, Lp-PLA2 inhibition. In over 260,000 participants of European, South Asian, or East Asian ancestries, we studied five functional variants in PLA2G7. We compared effects of Lp-PLA2-lowering alleles on soluble Lp-PLA2 activity, conventional cardiovascular risk factors and CHD risk with corresponding effects of darapladib, using results from randomized trials.

Methods

Study design

Figure 1 summarizes the study approach. Table 1 provides definitions and sources of data used. First, we identified four loss-of-function mutations and one missense variant in PLA2G7 suggested by previous experimental and bioinformatics studies, thereby developing an allelic series for Lp-PLA2 activity. Second, we assessed associations of these variants – both singly and in combination – with soluble Lp-PLA2 activity, conventional cardiovascular risk factors and CHD risk in people of European, South Asian or East Asian ancestries. Third, we compared associations of Lp-PLA2-lowering alleles with the aforementioned traits and CHD risk with the effects of darapladib treatment through a systematic review of randomized trials.
Figure 1.

Summary of study design. (a) Flow chart of study design. (b) Exonic structure of the PLA2G7 gene and location of variants used in this study. ExAc: Exome Aggregation consortium; NHLBI ESP: National Heart Lung and Blood Institute Exome Sequencing Project; Lp-PLA2: lipoprotein-associated phospholipase A2; RCT: randomized controlled trial; UniProt/Swissprot: manually annotated and reviewed section of the Universal Protein resource database.

Table 1.

Definitions and source of contributing data for the main study outcome.

Lp-PLA2 assessment tool Val279Phe, loss-of-function variant common in East Asians Four loss-of-function variants[a], rare in Europeans and South Asians Val379Ala, modest impact variant Darapladib
Data sources
Systematic review: up to 12 East Asian studies
De-novo genotyping and participant-level data: up to eight European or South Asian ancestry studies from the CHD Exome+ consortium[19-26] De-novo genotyping and study-level data: up to 15 European ancestry studies from the MICAD Exome consortium[38] and three European ancestry studies from the CHARGE Consortium[17,29] Plus publicly available consortium data
Systematic review: up to five randomized clinical trials[6,7,39-41] from a systematic review
Endpoint
Number of studies and unique individuals contributing to analyses; n total or cases/controls
Coronary heart disease [b] Seven East Asian studies[c]Eight European or South Asian ancestry studies from the CHD Exome+ consortium[19-26] [d]15 European ancestry studies from the MICAD Exome consortium[38] [c]Eight European or South Asian ancestry studies from the CHD Exome+ consortium[19-26] [d]Eight European ancestry studies from the MICAD Exome consortium[38] [c]14 European ancestry studies from the CARDIoGRAM consortium[27] [e]Four European or South Asian ancestry studies from the C4D consortium[28] [e]Two phase 3 randomized clinical trials of darapladib[6,7] [c]
10,088 cases 15,199 controls35,829 cases 44,948 controls35,533 cases 64,130 controls32,196 cases 41,464 controls14,976 cases 32,084 controls20,315 cases 58,419 controls15,420 cases 15,062 controls3364 cases 25,490 non-cases
Lp-PLA2 activity [f] 12 East Asian studies[c]One European ancestry study from the CHD Exome+ consortium[25] [d]One European ancestry study from the CHARGE consortium[29] [c]Two European ancestry studies from the CHD Exome+ consortium[22,23,25] [d]Three European ancestry studies from the CHARGE consortium[17] [c]Three phase 2 randomized clinical trials[39-41] [c]
846812408564217311,662854
Summary of study design. (a) Flow chart of study design. (b) Exonic structure of the PLA2G7 gene and location of variants used in this study. ExAc: Exome Aggregation consortium; NHLBI ESP: National Heart Lung and Blood Institute Exome Sequencing Project; Lp-PLA2: lipoprotein-associated phospholipase A2; RCT: randomized controlled trial; UniProt/Swissprot: manually annotated and reviewed section of the Universal Protein resource database. Definitions and source of contributing data for the main study outcome.

Genetic variants

We defined loss-of-function variants as non-synonymous variants with in vitro or in vivo evidence demonstrating complete lack of Lp-PLA2 activity or sequence changes expected to abolish Lp-PLA2 function (e.g. nonsense variants or mutations in essential splice sites). We selected variants through a systematic search for loss-of-function variants using the UniProt database,[8] the Exome Aggregation Consortium database (Cambridge, MA, USA; URL: http://exac.broadinstitute.org (accessed November 2014)),[9] studies of site-directed mutagenesis[10-12] and results from targeted gene sequencing.[13] Among the full set of variants identified (Supplementary Material online Table 1), we selected the following variants that could be detected in the 1000 Genomes[14] or the NHLBI Exome Sequencing Project[15] projects (and, hence, potentially studied at the population level): the splice site mutation 109+2T>C (rs142974898); two non-synonymous variants – Arg82His (rs144983904) and Val279Phe (rs76863441); and the nonsense variant Gln287Ter (rs140020965). These loss-of-function variants are rare in European and South Asian ancestry populations, whereas carriage of 279Phe is common in East Asian ancestry populations and abolition of Lp-PLA2 activity is well documented.[16] Additionally, we studied Val379Ala (rs1051931), a functional variant common in European ancestry populations, which lowers Lp-PLA2 activity only modestly,[10,17] in contrast with the much stronger Lp-PLA2-lowering achieved by the loss-of-function variants described above.

Samples and data for genetic studies

We aimed to maximize study power and comprehensiveness by using the following complementary approaches to generate new data on, as well as to collate systematically existing relevant information about, the PLA2G7 variants mentioned above: (1) we conducted de-novo genotyping for 72,657 CHD patients and 110,218 controls (the majority of whom also had information available on some cardiovascular risk factors); (2) we accessed non-overlapping summary-level data from the only known global genetics consortium of CHD,[18] yielding information on a further 35,735 CHD patients and 73,481 controls; (3) we conducted a systematic review (supplemented by provision of tabular data from each study investigator) of published East Asian CHD studies of Val279Phe because these studies were not represented in the global CHD consortium, yielding information on a further 10,088 CHD cases and 15,199 controls; (4) we accessed summary-level data from the largest available global genetics consortium on each of several relevant cardiovascular risk factors (e.g. Lp-PLA2 activity, conventional lipids, blood pressure), yielding information on 489,045 participants. Each of these sources of information is summarized below and in Table 1, with a key in Table 1’s legend denoting the level of data detail available for each source (e.g. individual-participant data versus tabular study-level results).

Coronary heart disease outcomes

For CHD outcomes, we had access to data for a total of 92,995 patients and 162,228 controls. For 182,875 of these participants (72,657 CHD patients, 110,218 controls), we did de-novo genotyping of the four loss-of-function variants (c.109 + 2T > C, Arg82His, Val279Phe, Gln287Ter) and Val379Ala using customized Exome arrays (Illumina, CA, USA) by technicians masked to the phenotypic status of the participants’ samples. For 35,829 CHD cases, 44,948 controls in eight studies, we had access to individual-participant data. The eight studies were: the Bangladesh Risk of Acute Vascular Events Study,[19] Copenhagen City Heart Study,[20] Copenhagen Ischemic Heart Disease/Copenhagen General Population Study,[20] European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study (EPIC-CVD),[21] MONICA Risk, Genetics, Archiving, and Monograph (MORGAM) study,[22,23] Pakistan Risk of Myocardial Infarction Study,[24] Pravastatin in elderly individuals at risk of vascular disease (PROSPER) trial[25] and the West of Scotland Coronary Prevention Study[26] (these eight studies are collectively called the ‘CHD Exome+ consortium’). For 15 additional studies (collectively called the ‘MICAD consortium’) we used similar genotyping methods to those described above but did not genotype c.109+2T>C and had access only to study-level data. We supplemented de-novo data on Val379Ala with non-overlapping consortium-level results from a further 35,735 CHD patients and 73,481 controls in the transatlantic Coronary Artery Disease Genome-wide Replication and Meta-analysis[27] and Coronary Artery Disease Genetics[28] consortia (Table 1). We obtained tabular data on Val279Phe from seven East Asian studies involving a total of 10,088 CHD cases and 15,199 controls, identified through systematic review (text and Table 5 in Supplementary Material online). About 90% of CHD patients in our genetic analysis had myocardial infarction or other major acute coronary events; the remainder had angiographic evidence alone (e.g. >50% coronary stenosis; Supplementary Tables 2 and 5).

Lp-PLA2 activity

For 13,835 participants, we had information on functional variants in PLA2G7 and Lp-PLA2 activity, using data from de-novo genotyping in MORGAM[22,23] and PROSPER,[25] supplemented by published data from the CHARGE Consortium (i.e. from the Atherosclerosis Risk in Communities study,[29] Cardiovascular Health Study,[17] Framingham Heart Study[17] and Rotterdam study,[17] and from 12 East Asian studies identified through the systematic review described above (Table 1; Supplementary Material text, Figure 1 and Tables 2 and 3).

Conventional cardiovascular risk factors

For 177,343 participants, we had information on functional variants in PLA2G7 and conventional cardiovascular risk factors and several other traits, including circulating concentrations of LDL-cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides, glucose, insulin and C-reactive protein, and values of systolic and diastolic blood pressure, body-mass index and estimated glomerular filtration rate. Again, we supplemented data from our de-novo genotyping, with information from existing global genetics consortia (Table 1; Supplementary Tables 2 to 4).

Randomized trials of darapladib

To compare genetic associations with effects of pharmacological Lp-PLA2 inhibition, we conducted a systematic review to identify randomized placebo-controlled trials of darapladib that had reported on Lp-PLA2 activity, conventional risk factors and/or CHD events (Supplementary Material). CHD events in the trials were defined as fatal CHD, myocardial infarction or urgent revascularization, as recorded in STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) and in SOLID-TIMI 52 (Stabilization of Plaque Using Darapladib-Thrombolysis in Myocardial Infarction 52).[6,7] We pooled results across trials by fixed-effect inverse-variance weighted meta-analysis (Supplementary Figures 2 and 3; see Supplementary text for details of the methods used).

Statistical methods

We defined effect alleles as those associated with lower Lp-PLA2 activity and assumed an additive model. For participant-level data, we assessed associations of Lp-PLA2-lowering alleles with CHD using the genome-wide efficient mixed model analysis, an approach that models each genetic variant as a fixed-effect, but includes both fixed-effect and random-effects of genetic inheritance[30] to account for population stratification and relatedness among participants (Supplementary Material). The four rare loss-of-function variants were tested jointly within each study by counting the number of loss-of-function alleles carried by each participant. Log odds ratios and standard errors were meta-analysed across studies using fixed-effect meta-analysis. For studies contributing only study-level data, we performed a similar test by conducting a combined burden test across studies using the R package seqMeta v1.2 (http://cran.r-project.org/web/packages/seqMeta/). We calculated associations of Lp-PLA2-lowering alleles with soluble Lp-PLA2 activity and conventional risk factors using linear regression within each study, and then combined the regression coefficients using fixed-effect meta-analysis. When data were missing, we used information on rs1805018 as a proxy for Val279Phe and information on rs7756935 or rs3799277 as proxies for Val379Ala (Supplementary Material). To account for population stratification, we adjusted for the first principal component of ancestry (Supplementary Material). We calculated risk ratios for CHD with decrements in Lp-PLA2 activity, dividing the log transformed risk ratio and confidence interval (CI) by the effect on Lp-PLA2 activity of the instrument (i.e. the genetic variant).[31] We investigated heterogeneity using the I2 statistic. We used Stata 13.1.

Results

Of the 261,950 total participants in this analysis, we studied 195,715 individuals of European ancestry, 34,221 individuals of South Asian ancestry and 32,014 individuals of East Asian ancestry. In people of European or South Asian ancestry without CHD, the frequency of alleles in PLA2G7 that lower Lp-PLA2 activity was 0.005% at c.109 + 2T > C, 0.04% at Arg82His, 0.04% at Val279Phe and 0.025% at Gln287Ter (i.e. in aggregate, 0.2% of the European or South Asian participants in the current study carried one of these loss-of-function alleles, although no one carried more than one of these variants), and about 80% at Val379Ala. In people of East Asian ancestry without CHD, the frequency of Val279Phe was about 15% and about 2% of the individuals were homozygous carriers of the 279Phe allele.

Soluble Lp-PLA2 activity

Compared with non-carriers, homozygote carriers of the 279Phe allele had 94% lower Lp-PLA2 activity (p < 10–300). For each 279Phe allele inherited, Lp-PLA2 activity decreased by 45% (1.59 SD, 95% CI: 1.61–1.57; p < 10–300). In Europeans who inherited any one of the four rare Lp-PLA2 loss-of-function alleles, Lp-PLA2 activity decreased by 64% (2.25 SD, 2.68–1.83; p = 1.6 × 10–25). For each 379Ala allele inherited, Lp-PLA2 activity decreased by 2.7% (0.096 SD, 0.122–0.069; p = 1.9 × 10–12). By comparison, 160 mg once-daily darapladib reduced Lp-PLA2 activity by 65% (2.26 SD, 2.31–2.21; p < 10–300). Study-level estimates are provided in Supplementary Figure 2.

Cardiovascular risk factors

None of the Lp-PLA2-related variants we studied was significantly associated with values of LDL-cholesterol, HDL-cholesterol, triglycerides, systolic or diastolic blood pressure, body-mass index, estimated glomerular filtration rate, glucose, insulin and C-reactive protein (Figure 2). By comparison, in previous randomized placebo-controlled trials, darapladib did not significantly affect concentrations of LDL-cholesterol or log triglycerides, but could have slightly increased systolic blood pressure and HDL-cholesterol values and slightly decreased C-reactive protein concentration (Figure 2).
Figure 2.

Mean per allele differences in Lp-PLA2 activity and cardiovascular risk factor levels by Lp-PLA2-lowering alleles or with darapladib 160 mg daily. To enable comparison of the magnitude of associations across several different markers, analyses were undertaken with standardized units of measurement for each marker. Associations are presented as per allele change in the biomarker expressed as standard deviations. Numbers of participants are provided in Table 1. Details of contributing studies are provided in Supplementary Material Tables 2 and 3 online.

*Carriage of any of the four loss-of-function variants c.109+2T>C, Arg82His, Val279Phe, Gln287Ter.

BMI: body-mass index; CI: confidence interval; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; HDL-c: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; LoF: loss-of-function; Lp-PLA2: lipoprotein associated phospholipase A2; SBP: systolic blood pressure

Mean per allele differences in Lp-PLA2 activity and cardiovascular risk factor levels by Lp-PLA2-lowering alleles or with darapladib 160 mg daily. To enable comparison of the magnitude of associations across several different markers, analyses were undertaken with standardized units of measurement for each marker. Associations are presented as per allele change in the biomarker expressed as standard deviations. Numbers of participants are provided in Table 1. Details of contributing studies are provided in Supplementary Material Tables 2 and 3 online. *Carriage of any of the four loss-of-function variants c.109+2T>C, Arg82His, Val279Phe, Gln287Ter. BMI: body-mass index; CI: confidence interval; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; HDL-c: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; LoF: loss-of-function; Lp-PLA2: lipoprotein associated phospholipase A2; SBP: systolic blood pressure

Clinical CHD outcomes

Compared with non-carriers, the odds ratio for CHD was 0.99 (0.95–1.03) in 279Phe heterozygotes, and 0.93 (0.82–1.05) in 279Phe homozygotes (i.e. nearly complete loss of Lp-PLA2 function: Figure 3). For each loss-of-function (279Phe) allele inherited, the odds ratio for CHD was 0.97 (0.91–1.02; I2 = 30%; pHeterogeneity = 0.2). In Europeans and South Asians who inherited one of the four rare Lp-PLA2-loss-of-function alleles, the odds ratio for CHD was 0.92 (0.74–1.16; I2 = 0%; pHeterogeneity = 0.8; Figure 3). For each 379Ala allele inherited, the odds ratio for CHD was 1.00 (0.98–1.02; I2 = 0.0%; pHeterogeneity = 0.5; Figure 3). Study-level results are provided in Supplementary Figure 3. In sensitivity analyses, odds ratios with each loss-of-function variant were similar to the odds ratio that combined information across the four loss-of-function variants we studied. There was no evidence of heterogeneity in odds ratios between European and South Asian ancestry populations (Supplementary Figure 4).
Figure 3.

Association of Lp-PLA2-lowering alleles with Lp-PLA2 activity and CHD risk. Spectrum of functional alleles in PLA2G7 and effects on Lp-PLA2 activity (red estimates) and coronary heart disease risk (black estimates); *Carriage of any of the four loss-of-function variants c.109+2T>C, Arg82His, Val279Phe, Gln287Ter. †One study did not provide tabular data to enable calculation of CHD odds ratios in heterozygotes or homozygotes. Hence, numbers are less than those presented for the per allele analysis in Table 2. CHD: coronary heart disease; CI: confidence interval; LoF: loss-of-function; Lp-PLA2: lipoprotein associated phospholipase A2.

Association of Lp-PLA2-lowering alleles with Lp-PLA2 activity and CHD risk. Spectrum of functional alleles in PLA2G7 and effects on Lp-PLA2 activity (red estimates) and coronary heart disease risk (black estimates); *Carriage of any of the four loss-of-function variants c.109+2T>C, Arg82His, Val279Phe, Gln287Ter. †One study did not provide tabular data to enable calculation of CHD odds ratios in heterozygotes or homozygotes. Hence, numbers are less than those presented for the per allele analysis in Table 2. CHD: coronary heart disease; CI: confidence interval; LoF: loss-of-function; Lp-PLA2: lipoprotein associated phospholipase A2. Genetic risk ratios for CHD per 65% lower Lp-PLA2 activity (i.e. the reduction achievable with darapladib treatment) were: 0.95 (0.88–1.03) with Val279Phe in East Asians; and 0.92 (0.74–1.16) with carriage of any one of the four rare variants studied in Europeans and South Asians; and 1.01 (0.68–1.51) with Val379Ala (Table 2). By comparison, the risk ratio for CHD with darapladib treatment (i.e. also per 65% lower Lp-PLA2 activity) was 0.95 (0.89–1.02; Table 2).
Table 2.

Comparison on a common scale of human genetic and randomized trial evidence for Lp-PLA2 lowering and CHD.

CHD patientsControlsRisk ratio for CHD per 65% lower Lp-PLA2 activity (95% CI)
Genetically lowered Lp-PLA2
 Val279Phe (East Asian LoF variant)10,08815,1990.95 (0.88–1.03)
 Four loss-of-function variants[a]71,362109,0780.92 (0.74–1.16)
 Val379Ala82,907147,0291.01 (0.68–1.51)
Pharmacologically lowered Lp-PLA2
 Darapladib336425,4900.95 (0.89–1.02)

Further detail on the individual studies is provided in Supplementary Tables 2 and 3 online.

rs142974898 (c.109+2T>C), rs144983904 (Arg82His), rs76863441 (Val279Phe), rs140020965 (Gln287Ter); see also Figure 1(b) for further variant details.

In genetic analysis, CHD was defined as myocardial infarction and other major coronary events (∼90% of cases) or angiographic stenosis only (∼10% of cases); see Supplementary Tables 2 and 3 for details. In the darapladib analysis CHD was defined as fatal coronary disease, non-fatal myocardial infarction or urgent revascularization for myocardial ischaemia.

Summary/tabular data available (by study).

Participant-level data available.

Meta-analysis data available.

See Supplementary Tables 2 and 3 for details on risk factor measurements.

BMI: body-mass index; C4D: Coronary Artery Disease Genetics consortium; CARDIoGRAM: Coronary ARtery DIsease Genome wide Replication and Meta-analysis; CHARGE: Cohorts for Heart and Aging Research in Genomic Epidemiology; CHD: coronary heart disease; CKDGen: Chronic Kidney Disease Genetics consortium; eGFR: estimated glomerular filtration rate; GIANT: Genetic Investigation of ANthropometric Traits consortium; GLGC: Global Lipids Genetics Consortium; ICBP: International Consortium for Blood Pressure; Lp-PLA2: lipoprotein associated phospholipase A2; MAGIC: Meta-Analyses of Glucose and Insulin-related traits Consortium; NA: data not available

Comparison on a common scale of human genetic and randomized trial evidence for Lp-PLA2 lowering and CHD. Further detail on the individual studies is provided in Supplementary Tables 2 and 3 online. rs142974898 (c.109+2T>C), rs144983904 (Arg82His), rs76863441 (Val279Phe), rs140020965 (Gln287Ter); see also Figure 1(b) for further variant details. In genetic analysis, CHD was defined as myocardial infarction and other major coronary events (∼90% of cases) or angiographic stenosis only (∼10% of cases); see Supplementary Tables 2 and 3 for details. In the darapladib analysis CHD was defined as fatal coronary disease, non-fatal myocardial infarction or urgent revascularization for myocardial ischaemia. Summary/tabular data available (by study). Participant-level data available. Meta-analysis data available. See Supplementary Tables 2 and 3 for details on risk factor measurements. BMI: body-mass index; C4D: Coronary Artery Disease Genetics consortium; CARDIoGRAM: Coronary ARtery DIsease Genome wide Replication and Meta-analysis; CHARGE: Cohorts for Heart and Aging Research in Genomic Epidemiology; CHD: coronary heart disease; CKDGen: Chronic Kidney Disease Genetics consortium; eGFR: estimated glomerular filtration rate; GIANT: Genetic Investigation of ANthropometric Traits consortium; GLGC: Global Lipids Genetics Consortium; ICBP: International Consortium for Blood Pressure; Lp-PLA2: lipoprotein associated phospholipase A2; MAGIC: Meta-Analyses of Glucose and Insulin-related traits Consortium; NA: data not available

Discussion

In a large-scale analysis of human genetic data, we tested whether Lp-PLA2 enzyme activity is causally relevant to CHD by studying five functional alleles that produce widely differing (i.e. small, moderate or large) degrees of reduction in Lp-PLA2 activity. We found that none was related to CHD risk, suggesting that Lp-PLA2 enzyme activity is unlikely to be causally relevant to CHD, a conclusion concordant with results from two phase 3 trials of a pharmacological Lp-PLA2 enzyme inhibitor. Three features of our study merit comment. First, we studied almost 20 times more CHD patients than the previous largest study of loss-of-function PLA2G7 alleles, thereby providing the first robust genetic evaluation of effect sizes of Lp-PLA2 inhibition relevant to phase 3 trials such as relative risk reductions for CHD of 20%. For example, for the Val279Phe variant we had >99% power to detect a 20% risk reduction in CHD for a 65% genetic reduction in Lp-PLA2 activity (i.e. an effect on Lp-PLA2 activity similar to that achieved by darapladib). Second, our study has provided the first investigation in CHD of a series of functional alleles that each reduce Lp-PLA2 function via different molecular mechanisms. Specifically, we studied five different Lp-PLA2-lowering alleles: three of the alleles were coding variants that produced different amino acid substitutions; two of the alleles produced protein truncations (one due to a nonsense mutation; the other due to a splice-site mutation). Because we observed null and broadly concordant findings for CHD risk across these alleles that each changed the enzyme in a different way (and to a different extent), we can more confidently conclude there is no material cause-and-effect relationship. By contrast, when the initial phase 3 trial of darapladib was launched in 2008, only two of the five alleles we studied had yet been identified: data on Val379Ala, a weak effect missense variant, were inconclusive because CHD studies were under-powered;[32] data on Val279Phe, a loss-of-function variant, and CHD risk were sparse and restricted to East Asian populations. A third feature was our study’s analysis of large-scale data from three different major ethnic groups: Europeans, South Asians and East Asians. This ethnic diversity enhanced the generalizability of our results. Our study had potential limitations. To maximize comparability of CHD endpoints used in clinical trials with those used in human genetic studies, we restricted analysis of phase 3 darapladib trials to ‘major coronary events’ and principally focused in human genetic studies on the cognate endpoints of myocardial infarction or other major acute coronary events (which constituted ∼90% of the outcomes). Nevertheless, although the CHD definitions used in trials and genetic studies were similar, they were not identical. It could be that cardioprotective benefits of Lp-PLA2 inhibition were obscured by pleiotropic effects of PLA2G7 variants; for example, 279Phe is known to produce a misfolded version of Lp-PLA2 not secreted by cells, prompting suggestions that its carriage could produce ‘off-target’ effects such as increased cell death.[33,34] However, because we found null associations between four other functional alleles in PLA2G7 and CHD, each of which operates via a different molecular mechanism, it argues against this explanation. On the other hand, it is possible that darapladib may have additional effects beyond Lp-PLA2 inhibition. For example, darapladib may have had slight effects on CRP levels and systolic blood pressure, which we did not observe with the genetic variants. Lifelong genetic reductions in Lp-PLA2 could result in compensatory responses that increase CHD risk. However, this explanation seems unlikely because it would require any such compensation to apply similarly across alleles that produce widely differing degrees of reduction in Lp-PLA2 activity. Furthermore, any such compensation could not operate through known cardiovascular mechanisms because we observed no associations between Lp-PLA2-lowering alleles and several established and emerging cardiovascular risk factors. Soluble enzyme activity could be an imperfect indicator of the relevance of Lp-PLA2 to atherosclerotic plaques. However, for homozygote carriers of 279Phe, Lp-PLA2 activity should be almost abolished across all tissues. Finally, we studied life-long genetic reductions in Lp-PLA2 activity in relation to first-onset CHD outcomes rather than recurrent CHD, whereas darapladib trials studied recurrent coronary events in patients with stable or acute coronary disease. The current data underscore the growing importance of human genetic approaches to enhance the efficiency of development of medicines by validating (or invalidating) novel drug targets.[35-38] Specifically, despite beneficial effects of darapladib on surrogate markers (e.g. intravascular imaging) of coronary atherosclerosis in pre-clinical and clinical studies,[39-41] these effects did not translate into reduced outcomes in the large phase 3 studies. Hence, human genetic studies may be useful in influencing prioritization of clinical outcome trials in the future. Our results also illustrate how human genetic evidence can assist interpretation of observational epidemiological data. For example, we found that functional alleles in PLA2G7 do not alter levels of pro-atherogenic lipids (e.g. LDL-cholesterol), suggesting that such pro-atherogenic lipids do not mediate associations between Lp-PLA2 activity and CHD and supporting the need to adjust epidemiological associations of Lp-PLA2 activity with CHD risk for pro-atherogenic lipids (an approach which yields results consistent with non-causality).[3] In summary, we found that none of a series of Lp-PLA2–lowering alleles was related to CHD risk, suggesting that Lp-PLA2 is unlikely to be a causal risk factor in CHD.
  47 in total

1.  Effect of darapladib on plasma lipoprotein-associated phospholipase A2 activity in Japanese dyslipidemic patients, with exploratory analysis of a PLA2G7 gene polymorphism of Val279Phe.

Authors:  Hiroyuki Daida; Takayuki Iwase; Shigeru Yagi; Hidekazu Ando; Hiromu Nakajima
Journal:  Circ J       Date:  2013-02-23       Impact factor: 2.993

2.  Coronary heart disease and genetic variants with low phospholipase A2 activity.

Authors:  Linda M Polfus; Richard A Gibbs; Eric Boerwinkle
Journal:  N Engl J Med       Date:  2015-01-15       Impact factor: 91.245

Review 3.  Inflammation modulation and cardiovascular disease prevention.

Authors:  Zuhier Awan; Jacques Genest
Journal:  Eur J Prev Cardiol       Date:  2014-04-07       Impact factor: 7.804

4.  Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. West of Scotland Coronary Prevention Study Group.

Authors:  J Shepherd; S M Cobbe; I Ford; C G Isles; A R Lorimer; P W MacFarlane; J H McKillop; C J Packard
Journal:  N Engl J Med       Date:  1995-11-16       Impact factor: 91.245

5.  Case-cohort design in practice - experiences from the MORGAM Project.

Authors:  Sangita Kulathinal; Juha Karvanen; Olli Saarela; Kari Kuulasmaa
Journal:  Epidemiol Perspect Innov       Date:  2007-12-04

Review 6.  The mammalian unfolded protein response.

Authors:  Martin Schröder; Randal J Kaufman
Journal:  Annu Rev Biochem       Date:  2005       Impact factor: 23.643

7.  The Pakistan Risk of Myocardial Infarction Study: a resource for the study of genetic, lifestyle and other determinants of myocardial infarction in South Asia.

Authors:  Danish Saleheen; Moazzam Zaidi; Asif Rasheed; Usman Ahmad; Abdul Hakeem; Muhammed Murtaza; Waleed Kayani; Azhar Faruqui; Assadullah Kundi; Khan Shah Zaman; Zia Yaqoob; Liaquat Ali Cheema; Abdus Samad; Syed Zahed Rasheed; Nadeem Hayat Mallick; Muhammad Azhar; Rashid Jooma; Ali Raza Gardezi; Nazir Memon; Abdul Ghaffar; Nadir Khan; Nabi Shah; Asad Ali Shah; Maria Samuel; Farina Hanif; Madiha Yameen; Sobia Naz; Aisha Sultana; Aisha Nazir; Shehzad Raza; Muhammad Shazad; Sana Nasim; Muhammad Ahsan Javed; Syed Saadat Ali; Mehmood Jafree; Muhammad Imran Nisar; Muhammad Salman Daood; Altaf Hussain; Nadeem Sarwar; Ayeesha Kamal; Panos Deloukas; Muhammad Ishaq; Philippe Frossard; John Danesh
Journal:  Eur J Epidemiol       Date:  2009-04-30       Impact factor: 8.082

8.  An integrated map of genetic variation from 1,092 human genomes.

Authors:  Goncalo R Abecasis; Adam Auton; Lisa D Brooks; Mark A DePristo; Richard M Durbin; Robert E Handsaker; Hyun Min Kang; Gabor T Marth; Gil A McVean
Journal:  Nature       Date:  2012-11-01       Impact factor: 49.962

9.  A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease.

Authors:  Majid Nikpay; Anuj Goel; Hong-Hee Won; Leanne M Hall; Christina Willenborg; Stavroula Kanoni; Danish Saleheen; Theodosios Kyriakou; Christopher P Nelson; Jemma C Hopewell; Thomas R Webb; Lingyao Zeng; Abbas Dehghan; Maris Alver; Sebastian M Armasu; Kirsi Auro; Andrew Bjonnes; Daniel I Chasman; Shufeng Chen; Ian Ford; Nora Franceschini; Christian Gieger; Christopher Grace; Stefan Gustafsson; Jie Huang; Shih-Jen Hwang; Yun Kyoung Kim; Marcus E Kleber; King Wai Lau; Xiangfeng Lu; Yingchang Lu; Leo-Pekka Lyytikäinen; Evelin Mihailov; Alanna C Morrison; Natalia Pervjakova; Liming Qu; Lynda M Rose; Elias Salfati; Richa Saxena; Markus Scholz; Albert V Smith; Emmi Tikkanen; Andre Uitterlinden; Xueli Yang; Weihua Zhang; Wei Zhao; Mariza de Andrade; Paul S de Vries; Natalie R van Zuydam; Sonia S Anand; Lars Bertram; Frank Beutner; George Dedoussis; Philippe Frossard; Dominique Gauguier; Alison H Goodall; Omri Gottesman; Marc Haber; Bok-Ghee Han; Jianfeng Huang; Shapour Jalilzadeh; Thorsten Kessler; Inke R König; Lars Lannfelt; Wolfgang Lieb; Lars Lind; Cecilia M Lindgren; Marja-Liisa Lokki; Patrik K Magnusson; Nadeem H Mallick; Narinder Mehra; Thomas Meitinger; Fazal-Ur-Rehman Memon; Andrew P Morris; Markku S Nieminen; Nancy L Pedersen; Annette Peters; Loukianos S Rallidis; Asif Rasheed; Maria Samuel; Svati H Shah; Juha Sinisalo; Kathleen E Stirrups; Stella Trompet; Laiyuan Wang; Khan S Zaman; Diego Ardissino; Eric Boerwinkle; Ingrid B Borecki; Erwin P Bottinger; Julie E Buring; John C Chambers; Rory Collins; L Adrienne Cupples; John Danesh; Ilja Demuth; Roberto Elosua; Stephen E Epstein; Tõnu Esko; Mary F Feitosa; Oscar H Franco; Maria Grazia Franzosi; Christopher B Granger; Dongfeng Gu; Vilmundur Gudnason; Alistair S Hall; Anders Hamsten; Tamara B Harris; Stanley L Hazen; Christian Hengstenberg; Albert Hofman; Erik Ingelsson; Carlos Iribarren; J Wouter Jukema; Pekka J Karhunen; Bong-Jo Kim; Jaspal S Kooner; Iftikhar J Kullo; Terho Lehtimäki; Ruth J F Loos; Olle Melander; Andres Metspalu; Winfried März; Colin N Palmer; Markus Perola; Thomas Quertermous; Daniel J Rader; Paul M Ridker; Samuli Ripatti; Robert Roberts; Veikko Salomaa; Dharambir K Sanghera; Stephen M Schwartz; Udo Seedorf; Alexandre F Stewart; David J Stott; Joachim Thiery; Pierre A Zalloua; Christopher J O'Donnell; Muredach P Reilly; Themistocles L Assimes; John R Thompson; Jeanette Erdmann; Robert Clarke; Hugh Watkins; Sekar Kathiresan; Ruth McPherson; Panos Deloukas; Heribert Schunkert; Nilesh J Samani; Martin Farrall
Journal:  Nat Genet       Date:  2015-09-07       Impact factor: 38.330

10.  Discovery and refinement of loci associated with lipid levels.

Authors:  Cristen J Willer; Ellen M Schmidt; Sebanti Sengupta; Michael Boehnke; Panos Deloukas; Sekar Kathiresan; Karen L Mohlke; Erik Ingelsson; Gonçalo R Abecasis; Gina M Peloso; Stefan Gustafsson; Stavroula Kanoni; Andrea Ganna; Jin Chen; Martin L Buchkovich; Samia Mora; Jacques S Beckmann; Jennifer L Bragg-Gresham; Hsing-Yi Chang; Ayşe Demirkan; Heleen M Den Hertog; Ron Do; Louise A Donnelly; Georg B Ehret; Tõnu Esko; Mary F Feitosa; Teresa Ferreira; Krista Fischer; Pierre Fontanillas; Ross M Fraser; Daniel F Freitag; Deepti Gurdasani; Kauko Heikkilä; Elina Hyppönen; Aaron Isaacs; Anne U Jackson; Åsa Johansson; Toby Johnson; Marika Kaakinen; Johannes Kettunen; Marcus E Kleber; Xiaohui Li; Jian'an Luan; Leo-Pekka Lyytikäinen; Patrik K E Magnusson; Massimo Mangino; Evelin Mihailov; May E Montasser; Martina Müller-Nurasyid; Ilja M Nolte; Jeffrey R O'Connell; Cameron D Palmer; Markus Perola; Ann-Kristin Petersen; Serena Sanna; Richa Saxena; Susan K Service; Sonia Shah; Dmitry Shungin; Carlo Sidore; Ci Song; Rona J Strawbridge; Ida Surakka; Toshiko Tanaka; Tanya M Teslovich; Gudmar Thorleifsson; Evita G Van den Herik; Benjamin F Voight; Kelly A Volcik; Lindsay L Waite; Andrew Wong; Ying Wu; Weihua Zhang; Devin Absher; Gershim Asiki; Inês Barroso; Latonya F Been; Jennifer L Bolton; Lori L Bonnycastle; Paolo Brambilla; Mary S Burnett; Giancarlo Cesana; Maria Dimitriou; Alex S F Doney; Angela Döring; Paul Elliott; Stephen E Epstein; Gudmundur Ingi Eyjolfsson; Bruna Gigante; Mark O Goodarzi; Harald Grallert; Martha L Gravito; Christopher J Groves; Göran Hallmans; Anna-Liisa Hartikainen; Caroline Hayward; Dena Hernandez; Andrew A Hicks; Hilma Holm; Yi-Jen Hung; Thomas Illig; Michelle R Jones; Pontiano Kaleebu; John J P Kastelein; Kay-Tee Khaw; Eric Kim; Norman Klopp; Pirjo Komulainen; Meena Kumari; Claudia Langenberg; Terho Lehtimäki; Shih-Yi Lin; Jaana Lindström; Ruth J F Loos; François Mach; Wendy L McArdle; Christa Meisinger; Braxton D Mitchell; Gabrielle Müller; Ramaiah Nagaraja; Narisu Narisu; Tuomo V M Nieminen; Rebecca N Nsubuga; Isleifur Olafsson; Ken K Ong; Aarno Palotie; Theodore Papamarkou; Cristina Pomilla; Anneli Pouta; Daniel J Rader; Muredach P Reilly; Paul M Ridker; Fernando Rivadeneira; Igor Rudan; Aimo Ruokonen; Nilesh Samani; Hubert Scharnagl; Janet Seeley; Kaisa Silander; Alena Stančáková; Kathleen Stirrups; Amy J Swift; Laurence Tiret; Andre G Uitterlinden; L Joost van Pelt; Sailaja Vedantam; Nicholas Wainwright; Cisca Wijmenga; Sarah H Wild; Gonneke Willemsen; Tom Wilsgaard; James F Wilson; Elizabeth H Young; Jing Hua Zhao; Linda S Adair; Dominique Arveiler; Themistocles L Assimes; Stefania Bandinelli; Franklyn Bennett; Murielle Bochud; Bernhard O Boehm; Dorret I Boomsma; Ingrid B Borecki; Stefan R Bornstein; Pascal Bovet; Michel Burnier; Harry Campbell; Aravinda Chakravarti; John C Chambers; Yii-Der Ida Chen; Francis S Collins; Richard S Cooper; John Danesh; George Dedoussis; Ulf de Faire; Alan B Feranil; Jean Ferrières; Luigi Ferrucci; Nelson B Freimer; Christian Gieger; Leif C Groop; Vilmundur Gudnason; Ulf Gyllensten; Anders Hamsten; Tamara B Harris; Aroon Hingorani; Joel N Hirschhorn; Albert Hofman; G Kees Hovingh; Chao Agnes Hsiung; Steve E Humphries; Steven C Hunt; Kristian Hveem; Carlos Iribarren; Marjo-Riitta Järvelin; Antti Jula; Mika Kähönen; Jaakko Kaprio; Antero Kesäniemi; Mika Kivimaki; Jaspal S Kooner; Peter J Koudstaal; Ronald M Krauss; Diana Kuh; Johanna Kuusisto; Kirsten O Kyvik; Markku Laakso; Timo A Lakka; Lars Lind; Cecilia M Lindgren; Nicholas G Martin; Winfried März; Mark I McCarthy; Colin A McKenzie; Pierre Meneton; Andres Metspalu; Leena Moilanen; Andrew D Morris; Patricia B Munroe; Inger Njølstad; Nancy L Pedersen; Chris Power; Peter P Pramstaller; Jackie F Price; Bruce M Psaty; Thomas Quertermous; Rainer Rauramaa; Danish Saleheen; Veikko Salomaa; Dharambir K Sanghera; Jouko Saramies; Peter E H Schwarz; Wayne H-H Sheu; Alan R Shuldiner; Agneta Siegbahn; Tim D Spector; Kari Stefansson; David P Strachan; Bamidele O Tayo; Elena Tremoli; Jaakko Tuomilehto; Matti Uusitupa; Cornelia M van Duijn; Peter Vollenweider; Lars Wallentin; Nicholas J Wareham; John B Whitfield; Bruce H R Wolffenbuttel; Jose M Ordovas; Eric Boerwinkle; Colin N A Palmer; Unnur Thorsteinsdottir; Daniel I Chasman; Jerome I Rotter; Paul W Franks; Samuli Ripatti; L Adrienne Cupples; Manjinder S Sandhu; Stephen S Rich
Journal:  Nat Genet       Date:  2013-10-06       Impact factor: 38.330

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  9 in total

Review 1.  Lipoprotein-associated phospholipase A2: The story continues.

Authors:  Fubao Huang; Kai Wang; Jianhua Shen
Journal:  Med Res Rev       Date:  2019-05-29       Impact factor: 12.944

2.  Tag-SNPs in Phospholipase-Related Genes Modify the Susceptibility to Nephrosclerosis and its Associated Cardiovascular Risk.

Authors:  Luz M González; Nicolás R Robles; Sonia Mota-Zamorano; José C Arévalo-Lorido; José Manuel Valdivielso; Juan López-Gómez; Guillermo Gervasini
Journal:  Front Pharmacol       Date:  2022-05-02       Impact factor: 5.988

3.  Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity.

Authors:  Danish Saleheen; Pradeep Natarajan; Irina M Armean; Wei Zhao; Asif Rasheed; Sumeet A Khetarpal; Hong-Hee Won; Konrad J Karczewski; Anne H O'Donnell-Luria; Kaitlin E Samocha; Benjamin Weisburd; Namrata Gupta; Mozzam Zaidi; Maria Samuel; Atif Imran; Shahid Abbas; Faisal Majeed; Madiha Ishaq; Saba Akhtar; Kevin Trindade; Megan Mucksavage; Nadeem Qamar; Khan Shah Zaman; Zia Yaqoob; Tahir Saghir; Syed Nadeem Hasan Rizvi; Anis Memon; Nadeem Hayyat Mallick; Mohammad Ishaq; Syed Zahed Rasheed; Fazal-Ur-Rehman Memon; Khalid Mahmood; Naveeduddin Ahmed; Ron Do; Ronald M Krauss; Daniel G MacArthur; Stacey Gabriel; Eric S Lander; Mark J Daly; Philippe Frossard; John Danesh; Daniel J Rader; Sekar Kathiresan
Journal:  Nature       Date:  2017-04-12       Impact factor: 49.962

4.  Pharmacogenetic meta-analysis of baseline risk factors, pharmacodynamic, efficacy and tolerability endpoints from two large global cardiovascular outcomes trials for darapladib.

Authors:  Astrid Yeo; Li Li; Liling Warren; Jennifer Aponte; Dana Fraser; Karen King; Kelley Johansson; Allison Barnes; Colin MacPhee; Richard Davies; Stephanie Chissoe; Elizabeth Tarka; Michelle L O'Donoghue; Harvey D White; Lars Wallentin; Dawn Waterworth
Journal:  PLoS One       Date:  2017-07-28       Impact factor: 3.240

5.  Disconnect Between Genes Associated With Ischemic Heart Disease and Targets of Ischemic Heart Disease Treatments.

Authors:  C M Schooling; J V Huang; J V Zhao; M K Kwok; S L Au Yeung; S L Lin
Journal:  EBioMedicine       Date:  2018-01-31       Impact factor: 8.143

6.  Re-thinking Alzheimer's disease therapeutic targets using gene-based tests.

Authors:  Man Ki Kwok; Shi Lin Lin; C Mary Schooling
Journal:  EBioMedicine       Date:  2018-10-09       Impact factor: 8.143

Review 7.  Red Blood Cells and Hemoglobin in Human Atherosclerosis and Related Arterial Diseases.

Authors:  Jean-Baptiste Michel; José Luis Martin-Ventura
Journal:  Int J Mol Sci       Date:  2020-09-15       Impact factor: 5.923

8.  Integrated Human Evaluation of the Lysophosphatidic Acid Pathway as a Novel Therapeutic Target in Atherosclerosis.

Authors:  Silvia Aldi; Ljubica Perisic Matic; Gregory Hamm; Daniëlle van Keulen; Dennie Tempel; Kim Holmstrøm; Agnieszka Szwajda; Boye Schnack Nielsen; Valur Emilsson; Rima Ait-Belkacem; Mariette Lengquist; Gabrielle Paulsson-Berne; Per Eriksson; Jan H N Lindeman; Alain J Gool; Jonathan Stauber; Ulf Hedin; Eva Hurt-Camejo
Journal:  Mol Ther Methods Clin Dev       Date:  2018-06-27       Impact factor: 6.698

9.  On the present and future role of Lp-PLA2 in atherosclerosis-related cardiovascular risk prediction and management.

Authors:  Zlatko Fras; Jure Tršan; Maciej Banach
Journal:  Arch Med Sci       Date:  2020-08-20       Impact factor: 3.318

  9 in total

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