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The Multi-Ethnic New Zealand Study of Acute Coronary Syndromes (MENZACS): Design and Methodology

Authors:
  • Auckland City Hospital and University of Auckland

Abstract and Figures

Background. Each year, approximately 5000 New Zealanders are admitted to hospital with first-time acute coronary syndrome (ACS). The Multi-Ethnic New Zealand Study of Acute Coronary Syndromes (MENZACS) is a prospective longitudinal cohort study embedded within the All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry in six hospitals. The objective of MENZACS is to examine the relationship between clinical, genomic, and cardiometabolic markers in relation to presentation and outcomes post-ACS. Methods. Patients with first-time ACS are enrolled and study-specific research data is collected alongside the ANZACS-QI registry. The research blood samples are stored for future genetic/biomarker assays. Dietary information is collected with a food frequency questionnaire and information about physical activity, smoking, and stress is also collected via questionnaire. Detailed family history, ancestry, and ethnicity data are recorded on all participants. Results. During the period between 2015 and 2019, there were 2015 patients enrolled. The mean age was 61 years, with 60% of patients aged
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Study Protocol
The Multi-Ethnic New Zealand Study of Acute Coronary
Syndromes (MENZACS): Design and Methodology
Malcolm. E. Legget 1 ,2 ,*, Vicky. A. Cameron 3, Katrina. K. Poppe 1,4, Sara Aish 1, Nikki Earle 1,
Yeunhyang Choi 1,4, Kathryn. E. Bradbury 5, Clare Wall 6, Ralph Stewart 2, Andrew Kerr 4,7, Wil Harrison 7,
Gerry Devlin 8, Richard Troughton 3, A. Mark Richards 3, Graeme Porter 9, Patrick Gladding 10,
Anna Rolleston 1, 11 and Robert N. Doughty 1,2


Citation: Legget, M..E.; Cameron,
V..A.; Poppe, K..K.; Aish, S.; Earle, N.;
Choi, Y.; Bradbury, K..E.; Wall, C.;
Stewart, R.; Kerr, A.; et al. The
Multi-Ethnic New Zealand Study of
Acute Coronary Syndromes
(MENZACS): Design and
Methodology. Cardiogenetics 2021,11,
84–97. https://doi.org/10.3390/
cardiogenetics11020010
Academic Editor: George E. Louridas
Received: 8 February 2021
Accepted: 31 May 2021
Published: 8 June 2021
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This article is an open access article
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Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Heart Health Research Group, Faculty of Medical and Health Sciences, University of Auckland,
Auckland 1023, New Zealand; k.poppe@auckland.ac.nz (K.K.P.); s.aish@auckland.ac.nz (S.A.);
n.earle@auckland.ac.nz (N.E.); yeunhyang.choi@auckland.ac.nz (Y.C.); anna@thecentreforhealth.co.nz (A.R.);
r.doughty@auckland.ac.nz (R.N.D.)
2Greenlane Cardiovascular Service, Auckland City Hospital, Auckland 1023, New Zealand;
r.stewart@adhb.govt.nz
3Christchurch Heart Institute, University of Otago, Christchurch 8011, New Zealand;
vicky.cameron@otago.ac.nz (V.A.C.); richard.troughton@cdhb.health.nz (R.T.);
mark.richards@cdhb.health.nz (A.M.R.)
4Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences,
University of Auckland, Auckland 1023, New Zealand; andrew.kerr@middlemore.co.nz
5National Institute for Health Innovation, School of Population Health, University of Auckland,
Auckland 1023, New Zealand; k.bradbury@auckland.ac.nz
6Discipline of Nutrition, Faculty of Medical and Health Sciences, University of Auckland,
Auckland 1023, New Zealand; c.wall@auckland.ac.nz
7Middlemore Hospital, Counties Manukau District Health Board, Auckland 2025, New Zealand;
wil.harrison@middlemore.co.nz
8Gisborne Hospital, Tairawhiti District Health Board, Gisborne 4010, New Zealand;
g.devlin@heartfoundation.org.nz
9Tauranga Hospital, Bay of Plenty District Health Board, Tauranga 3112, New Zealand;
g.porter@bopdhb.govt.nz
10 North Shore Hospital, Waitemata District Health Board, Auckland 0620, New Zealand;
patrick.gladding@waitematadhb.govt.nz
11 Centre for Health, Tauranga 3112, New Zealand
*Correspondence: malcolm.legget@auckland.ac.nz
Abstract: Background
. Each year, approximately 5000 New Zealanders are admitted to hospital
with first-time acute coronary syndrome (ACS). The Multi-Ethnic New Zealand Study of Acute Coronary
Syndromes (MENZACS) is a prospective longitudinal cohort study embedded within the All New
Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry in six hospitals. The
objective of MENZACS is to examine the relationship between clinical, genomic, and cardiometabolic
markers in relation to presentation and outcomes post-ACS. Methods. Patients with first-time ACS
are enrolled and study-specific research data is collected alongside the ANZACS-QI registry. The
research blood samples are stored for future genetic/biomarker assays. Dietary information is
collected with a food frequency questionnaire and information about physical activity, smoking,
and stress is also collected via questionnaire. Detailed family history, ancestry, and ethnicity data
are recorded on all participants.
Results
. During the period between 2015 and 2019, there were
2015 patients enrolled. The mean age was 61 years, with 60% of patients aged <65 years and 21%
were female. Ethnicity and cardiovascular (CV) risk factor distribution was similar to ANZACS-QI:
13% M
¯
aori, 5% Pacific, 5% Indian, and 74% NZ European. In terms of CV risk factors, 56% were
ex-/current smokers, 42% had hypertension, and 19% had diabetes. ACS subtype was ST elevation
myocardial infarction (STEMI) in 41%, non-ST elevation myocardial infarction (NSTEM) in 54%,
and unstable angina in 5%. Ninety-nine percent of MENZACS participants underwent coronary
angiography and 90% had revascularization; there were high rates of prescription of secondary
prevention medications upon discharge from hospital.
Conclusion
. MENZACS represents a cohort
with optimal contemporary management and will be a significant epidemiological bioresource for
Cardiogenetics 2021,11, 84–97. https://doi.org/10.3390/cardiogenetics11020010 https://www.mdpi.com/journal/cardiogenetics
Cardiogenetics 2021,11 85
the study of environmental and genetic factors contributing to ACS in New Zealand’s multi-ethnic
environment. The study will utilise clinical, nutritional, lifestyle, genomic, and biomarker analyses to
explore factors influencing the progression of coronary disease and develop risk prediction models
for health outcomes.
Keywords: MENZACS; acute coronary syndrome; multi-ethnic; genomics; study design
1. Introduction
In New Zealand, 15% of all deaths annually are caused by ischaemic heart disease [
1
]
and one in four major coronary events are fatal [
2
]. Although age standardised mortal-
ity rates for ischaemic heart disease have fallen dramatically since the late 1960s, New
Zealand’s mortality rates are still higher than many other western countries with persistent
disparities based on ethnic group and social deprivation. M
¯
aori (the indigenous population
of New Zealand) and Pacific peoples typically present with disease at a younger age, have
higher readmission rates, and incur approximately double the European age-standardised
mortality rate [3,4].
Whilst there have been considerable advances in the management of acute coronary
syndromes (ACS), there are important knowledge and practice gaps in optimal risk stratifi-
cation, treatment, and long-term outcomes for patients with cardiovascular disease (CVD)
in New Zealand [
5
7
]. Recurrent event rates remain high, with a recent follow-up analysis
of patients admitted with a first-time ACS showing that 15% experienced a non-fatal car-
diovascular readmission and 16% had died within a year [
8
]. Identification of individuals
or groups at high residual risk of further events, despite contemporary therapies, could
lead to more targeted strategies to improve inequitable clinical outcomes. For patients
admitted with a first-time ACS in New Zealand, there is a high incidence of premature
disease with 25% being aged less than 55 years [
4
] and a very high burden of risk factors:
half are current smokers, half have a BMI > 30 kg/m
2
, and 16% have diabetes. Along with
established clinical risk factors [
9
], it is becoming widely accepted that CVD risk prediction
is improved by incorporating environmental and sociodemographic variables and their
interactions with genetic and other omics markers [10].
However, genetic risk markers identified in international genome-wide association
studies (GWAS) for risk assessment may not be ideal for translation to New Zealand’s
multi-ethnic population, since it is estimated that approximately 80% of all participants in
GWAS are of European ancestry despite this group representing only 16% of the global
population [
11
]. Population profiles of GWAS for coronary artery disease follow a similar
pattern and are also primarily of European descent [11]. The transferability of this knowl-
edge to other populations is now known to be problematic since populations vary in terms
of allele frequency, effect size of risk variants [
12
,
13
], and having unique ethnic-specific
genetic variants associated with disease risk. Moreover, genetic variants influence how dif-
ferent populations metabolise drugs [
14
16
] and this leads to disparate outcomes between
ethnic groups, even when under the same treatment regimes.
The primary aim of the Multi Ethnic New Zealand study of Acute Coronary Syn-
dromes (MENZACS) is to define the extent to which environmental and genetic factors
contribute to the overall burden of ACS in New Zealand’s ethnically diverse population
presenting with first-time ACS. The study will utilise clinical, nutritional, lifestyle, genomic,
and biomarker analyses to explore aetiological factors and to develop risk prediction
models for outcomes.
The broad themes of the proposed research are as follows: (1) to explore the role of
genetic variation in the progression of coronary disease in a contemporary cohort of New
Zealanders with ACS; (2) to refine screening strategies in certain high-risk populations to
enhance secondary risk prediction and early intervention using a combination of clinical
risk factors, genomics, and biomarkers; and (3) to define how the response to therapies
Cardiogenetics 2021,11 86
for ACS differs by ethnicity across New Zealand’s diverse ethnic population groups. The
protocol and structure of the study are reported along with a description of the initial cohort.
2. Methods
2.1. Study Design and Participants
MENZACS was established in 2015 in New Zealand by the Heart Health Research
Group, University of Auckland, in collaboration with the Christchurch Heart Institute,
University of Otago. The study received national ethics approval in April 2015 from the
Health and Disability Ethics Committee (Ref: 15/NTB/59), with each participant providing
written informed consent, and the protocol is registered at the Australian New Zealand
Clinical Trials Registry (ACTRN12615000676516).
MENZACS is a prospective longitudinal cohort study linked to the All New Zealand
Acute Coronary Syndrome Quality Improvement (ANZACS-QI) electronic registry by
using a common web-based platform, which records detailed clinical information and
routine laboratory test results on over 95% of patients admitted with suspected ACS un-
dergoing coronary angiography across hospitals in New Zealand [
17
]. The primary aim
of ANZACS-QI is to support evidence-based management of ACS regardless of age, sex,
ethnicity, socioeconomic status, or geographical domicile [
18
]. Anonymised linkage of reg-
istry data with national routinely collected data on hospitalisations, mortality, medication
dispensing, and other administrative health data will enable extensive phenotyping of this
patient cohort (Figure 1).
Cardiogenetics 2021, 11, FOR PEER REVIEW 3
enhance secondary risk prediction and early intervention using a combination of clinical
risk factors, genomics, and biomarkers; and (3) to define how the response to therapies for
ACS differs by ethnicity across New Zealand’s diverse ethnic population groups. The pro-
tocol and structure of the study are reported along with a description of the initial cohort.
2. Methods
2.1. Study Design and Participants
MENZACS was established in 2015 in New Zealand by the Heart Health Research
Group, University of Auckland, in collaboration with the Christchurch Heart Institute,
University of Otago. The study received national ethics approval in April 2015 from the
Health and Disability Ethics Committee (Ref: 15/NTB/59), with each participant providing
written informed consent, and the protocol is registered at the Australian New Zealand
Clinical Trials Registry (ACTRN12615000676516).
MENZACS is a prospective longitudinal cohort study linked to the All New Zealand
Acute Coronary Syndrome Quality Improvement (ANZACS-QI) electronic registry by us-
ing a common web-based platform, which records detailed clinical information and rou-
tine laboratory test results on over 95% of patients admitted with suspected ACS under-
going coronary angiography across hospitals in New Zealand [17]. The primary aim of
ANZACS-QI is to support evidence-based management of ACS regardless of age, sex,
ethnicity, socioeconomic status, or geographical domicile [18]. Anonymised linkage of
registry data with national routinely collected data on hospitalisations, mortality, medi-
cation dispensing, and other administrative health data will enable extensive phenotyping
of this patient cohort (Figure 1).
Figure 1. Schema showing the data platforms and linkages that result in the MENZACS cohort.
2.2. Study Infrastructure
A Māori Governance Group (MGG) was established at the beginning of this study.
The MGG interact regularly with the research team and are kaitiaki (custodians) for Māori
participants by providing advice and guidance using the principles of Te Mata Ira—Cul-
tural Guidelines for Biobanking & Genomic Research [19] to ensure best practice. The patient
information sheet and consent forms have been translated into Te Reo Māori, Tongan, and
Samoan to help increase recruitment and engagement with Māori and Pacific patients. In
addition, a kaupapa Māori information sheet is also available that more fully describes
Figure 1. Schema showing the data platforms and linkages that result in the MENZACS cohort.
2.2. Study Infrastructure
A M
¯
aori Governance Group (MGG) was established at the beginning of this study.
The MGG interact regularly with the research team and are kaitiaki (custodians) for M
¯
aori
participants by providing advice and guidance using the principles of Te Mata Ira—Cultural
Guidelines for Biobanking & Genomic Research [
19
] to ensure best practice. The patient
information sheet and consent forms have been translated into Te Reo M
¯
aori, Tongan, and
Samoan to help increase recruitment and engagement with M
¯
aori and Pacific patients. In
addition, a kaupapa M
¯
aori information sheet is also available that more fully describes
the cultural processes involved in the collection, storage, transportation, and destruction
of samples.
Cardiogenetics 2021,11 87
2.3. MENZACS Inclusion Criteria and Recruitment Pathway
Patients aged >18 years with a clinical diagnosis of ACS are identified during the index
hospital admission. Those fulfilling the criteria for a Type 1 myocardial infarction [
20
] or
unstable angina [
21
] are eligible for enrolment. Patients are excluded if there is an elevation
of troponin and/or if ECG changes are not thought to be due to an ACS, the patient has
end stage renal failure (eGFR < 15 mL/min/m
2
or is receiving or planned to receive renal
replacement therapy), is unable to give informed consent, or is not a New Zealand resident.
Patients admitted to the coronary care units of Auckland City, Middlemore, Christchurch,
Waikato, North Shore, and Tauranga Hospitals are screened for eligibility into the study by a
research nurse according to the criteria listed above. Eligible patients are invited to participate
and are given the appropriate participant information and consent forms.
2.4. MENZACS Research Data
The routine clinically available data relating to the acute admission is extracted from
the ANZACS-QI registry dataset and completed on all patients as part of the clinical work-
flow. These data include demographics, primary diagnosis, key cardiovascular risk factors,
past cardiovascular history and admission vital signs, blood results, ECG, echocardiogram,
in-hospital management, and coronary angiogram findings. MENZACS research-specific
data are captured using a purpose-built module linked to the web-based ANZACS-QI
platform, allowing efficient and standardised data collection at all participating sites. Data
on physical activity was collated using the World Health Organisation Global Physical
Activity Questionnaire [
22
] and information on stress and mood was gathered from a
previously validated questionnaire of patients with stable coronary disease [
23
]. Other risk
factors and clinical variables including smoking, history of gout, marijuana use, admission
medication, and waist circumference were also captured.
Research and routine clinical data obtained by using the platform are linked to ex-
ternally analysed research data on biomarkers, lipidomics, genetics, epigenetics, and diet.
Specialised centres for analysis include the Christchurch Heart Institute-NT-proBNP and
GDF-15, AgResearch (Invermay, Dunedin)-genotyping and the epigenetics analysis, AgRe-
search (Lincoln)-lipidomic analysis, and the Liggins Institute (University of Auckland)-
Lp(a) concentrations. The results of these sample analyses are then sent to the MENZACS
central data science management group at the University of Auckland for linkage to the
main dataset accompanied with appropriate encryption processes. These data are then
linked to national routinely collected data on past and future hospitalisations, dispensed
medications, and death provided by the national Ministry of Health and curated by the
Vascular Information and the Web (VIEW) programme of cardiovascular research (University
of Auckland). Individualised patient data linkage was enabled by matching each patient’s
unique National Health Index (NHI) number to an encrypted NHI using a well-established
protocol of de-identification, data security, and management that is central to the ongoing
processes of the VIEW and ANZACS-QI programmes [
18
,
24
].This process allows long term
follow up of 100% of the cohort that remained as residents in New Zealand.
Given the multi-ethnic emphasis of the study, in-depth data about family history,
ancestry, ethnic background, iwi (tribal) affiliation, participants’ and parents’ country of
birth, and grandparents’ ethnicities are obtained. A dietary food frequency questionnaire
(FFQ), with the wording of the food groups based on that used in the EPIC-Heart study [
25
]
and adapted to the modern multi-ethnic New Zealand environment, was administered to
all participants to survey dietary habits. This is a contemporary and culturally-appropriate
questionnaire, which has been validated and shown to be reproducible in New Zealand
adults [
26
], and is designed to enable comparison between cohorts and investigate the
relationship between diet and chronic disease.
2.5. Biological Samples
A total of 40 mL of blood for genomic and biomarker analysis is drawn from each
participant in a non-fasting state and seated. The time of acquisition of this blood sample
Cardiogenetics 2021,11 88
in relation to the time of admission was recorded. The samples are centrifuged (at 4
C,
4000 rpm for 10 min) and separated as required into cryogenic tubes and frozen within 30
min of collection. The resulting EDTA and lithium heparin plasma, serum, and whole blood
samples are stored at
80
C in a secure dedicated facility in the University of Auckland
School of Medical Sciences under the aegis of Te Ira K
¯
awai Auckland Regional Biobank
framework (https://www.aucklandregionaltissuebank.ac.nz/ accessed on 19 April 2021)
or at the Christchurch Heart Institute’s Health and Disability Ethics Committee (HDEC)
accredited tissue bank. All samples are logged in a specimen tracking and storage system.
This is via OpenSpecimen (Krishagni Solutions Pvt Ltd., Pune, India) in Auckland or
STARLims (Abbott Informatics, Hollywood, FL, USA) in Christchurch.
For M
¯
aori, the separation of body parts, tissues, or fluids from the person is acknowl-
edged as an important cultural consideration and appropriate protocols are involved. In
terms of using tissue or fluid samples for research it is accepted that those samples and the
DNA extracted from them are taonga (gifts) and are therefore tapu (sacred). A kaupapa
M
¯
aori research protocol information sheet has been created by the M
¯
aori Governance
Group which outlines the appropriate tikanga (M
¯
aori custom) processes developed to
ensure that the blood samples are treated with care and respect. There are processes around
karakia (blessing) that is usually performed prior to a sample being destroyed or sent away
for analysis.
2.6. Biochemical and Genetic Analyses
Laboratory results from tests undertaken as part of routine clinical care are available
to the study and this includes creatinine, high sensitivity troponin, and lipid profiles. These
have been recorded for >98% of the cohort. HbA1c is assayed when clinically indicated
and has been recorded in 79% of the cohort. Additional research assays will measure
other established and emerging risk markers and will include N-terminal pro B-type
natriuretic peptide (NT-proBNP), Growth Differentiation Factor 15 (GDF-15), lipoprotein(a),
and untargeted lipidomics using a mass spectrometry based lipidomics platform. This
will measure more than 300 lipid molecules in plasma, which includes sphingolipids,
phospholipids, glycerolipids, ceramides and di- and triglycerolipids, and cholesterol esters.
Genomic DNA on all participants has been extracted from 1 mL frozen whole blood
using an automated QiaSympony DNA extraction process. Genome-wide genotyping will
be performed using the Illumina Infinium Global Screening Array (640k SNPs, Illumina
Inc., San Diego, CA, USA). This platform has been selected based on its ability to process
samples within New Zealand and has high imputation accuracy at minor allele frequencies
of >1% across multiple populations and includes curated clinical research variants and
quality control markers. Epigenetic analysis will provide DNA methylation profiles in
a subset of 1015 MENZACS participants (including all M
¯
aori participants) and will be
performed using the Illumina Infinium Human Methylation EPIC beadchip array.
2.7. Clinical Outcome Variables
Clinical outcomes are defined from the national registries of ICD-10-AM (International
Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Aus-
tralian Modification) coded hospitalisations and death and ACHI (Australian Classification
of Health Interventions) coded procedures. A primary outcome of interest is major adverse
cardiac events (MACE) defined as coronary revascularisation, readmission for cardiovascu-
lar cause including recurrent ACS, and death. Specific secondary outcomes include fatal or
non-fatal ACS, fatal or non-fatal stroke or transient ischaemic attack (TIA), cardiovascular
death, and all-cause death. Cardiovascular death will be defined from the ICD-10 coded
death certificate or if death had occurred within 28 days of a CV hospitalisation.
2.8. Key Research Questions
This study will act as a resource for genomic discovery as well as providing a com-
prehensive study of the environmental, genetic, and conventional risk factors that are
Cardiogenetics 2021,11 89
associated with ACS in New Zealand. Whilst the data will allow “hypothesis free” unbi-
ased discovery studies (see below), specific research questions and themes include:
What dietary, lifestyle, and socio-economic factors are associated with first time ACS
and subsequent outcomes;
Can risk stratification be refined using clinical, biomarker, genetic, and epigenetic
factors to build on existing secondary risk equations in New Zealand [27];
Association studies of genetic variants with first time ACS and subsequent outcomes;
The interaction of genomics, environmental factors, and biomarkers associated with
certain phenotypes (e.g., diabetics, metabolic syndrome, hypertension, and obesity);
Pharmacogenetic variability and the frequency of certain known variants across a
diverse New Zealand population;
Ethnic variation in genomic and genetic “signatures” related to cardiovascular risk factors.
2.9. Statistical Approach
A Data Science Advisory Group (DSAG) has been formed to provide specialist exper-
tise in theoretical and applied statistics; this includes statistical genetics and will guide all
analyses. Key analytical considerations include assessment of biological variation within
and between data sources, reducing data dimensionality, time-to-event analyses, and the
development of incremental risk scores for clinical use.
Existing clinical [
28
] and polygenic risk scores [
29
33
] will provide a starting point
for the development of new incremental risk scores. In collaboration with data source
specialists in nutrition, biomarkers, lipidomics, genetics, epigenetics, clinical science, and
national health data repositories, the DSAG will discuss and advise on specialty-specific
approaches to data reduction and analyses. The outputs of these analyses will inform how
the data sources are best represented in the model, how model performance is assessed,
and what model structure will be used. All data science will have input from the MGG on
the appropriate use and interpretation of data in the M¯
aori and Pacific context.
In the current report, key descriptors of the MENZACS study cohort (Table 1) have
been presented as mean ±standard deviation, median (interquartile range), or frequency
(percentage) as relevant. Any other analyses performed to this point have focused on the
extent of missing data—for demographic and clinical variables and for the earlier quality
assurance assessments of dataset linkage and the calculation of a published genetic risk
score [31].
Table 1. Baseline demographics of the MENZACS cohort.
nDenominator #
Age, years 61 (53, 69) 2015
Male 1589 (78.9) 2015
Ethnicity 2015
M¯
aori 259 (12.8)
Pacific 104 (5.2)
Indian 94 (4.7)
Chinese 13 (0.6)
European 1499 (74.4)
Other * 46 (2.3)
Cardiogenetics 2021,11 90
Table 1. Cont.
nDenominator #
NZDep Index, quintile 2015
1 (least deprived) 479 (23.8)
2 416 (20.6)
3 361 (17.9)
4 374 (18.6)
5 (most deprived) 385 (19.1)
Charlson comorbidity score 2015
0 (no comorbidity) 1801 (89.4)
1–2 (moderate) 189 (9.4)
3 (severe) 25 (1.2)
Diabetes on admission 368 (18.5) 1986
COPD 126 (6.4) 1984
Smoking status 2014
Never smoked 838 (41.6)
Ex-smoker 700 (34.8)
Current smoker 476 (23.6)
BMI, kg/m229.5 ±5.6 2015
30 kg/m2788 (39.1)
TC: HDL 4.7 ±1.7 1872
4 1209 (64.6)
LDL cholesterol, mmol/L 3.0 ±1.4 1985
eGFR, mL/min/1.73 m279 (68, 92) 1967
HbA1c, mmol/mol 1610
Diabetes 62 (50, 79) 320
No diabetes 38 (35, 40) 1290
Values are n(column percentage), median (interquartile range), or mean
±
standard deviation.
#
Due to the nature
of the registry, some variables were not mandatory and resulted in limited missing data which is represented by
the denominator. NZDep = New Zealand Socioeconomic Deprivation; COPD = chronic obstructive pulmonary
disease; BMI = body mass index; TC:HDL = ratio of total to high-density lipoprotein cholesterol; LDL = low-
density lipoprotein; eGFR = estimated glomerular filtration rate, HbA1c = glycosylated haemoglobin. * “Other”
ethnicities are non-Chinese Asian, Middle Eastern, Latin American, African, or Other.
3. Study Progress
The MENZACS study commenced with a pilot phase of recruitment at Auckland City
Hospital (ACH) in July 2015. Middlemore and Christchurch started recruitment in March
2016, Waikato Hospital in May 2016, North Shore Hospital in May 2018, and Tauranga
Hospital in July 2018. The first phase of recruitment was completed in July 2019. Of the
4846 patients who were screened and met the inclusion criteria, 229 were excluded and 2601
were not enrolled due to patient or logistic issues and one withdrew, leaving a total of 2015
patients included in this cohort (Figure 2). Fifty-seven patients did not have a diagnosis
of confirmed ACS in the ANZACS-QI registry, and, thus, an adjudication process was
undertaken by designated cardiologists at each centre who reviewed the clinical records
and determined whether ACS occurred or not (including the type of ACS event). This
resulted in 11 of these patients being excluded as confirmed non-ACS events.
Cardiogenetics 2021,11 91
Cardiogenetics 2021, 11, FOR PEER REVIEW 8
Figure 2. Flow diagram of screening and enrolment into the MENZACS.
3.1. Baseline Characteristics
The baseline demographics of the initial MENZACS cohort are shown in Table 1. The
median age was 61 years, with 61% aged <65 years, and the cohort was predominantly
male (79%). Māori constituted 13% of the cohort, Pacific and Indian peoples each com-
prised 5%, and 74% of participants were of European ethnicity. Based on the ethnic distri-
bution and demographics of a contemporaneous cohort of first-time acute coronary syn-
drome patients in the ANZACS-QI registry, there is unlikely to have been an ethnic or
risk factor bias in enrolment status in MENZACS [4].
Nineteen percent were in the most deprived quintile, 19% had diabetes, and 24%
were current smokers. Almost all patients underwent angiography during the index ad-
mission and revascularisation rates were high, with 90% of the cohort undergoing either
PCI or CABG during their hospital admission. These rates are consistent with the recruit-
ing centres for MENZACS being secondary and tertiary referral centres for coronary in-
tervention. Comprehensive information on extent of coronary artery disease, left ventric-
ular function, GRACE score [34], and admission and discharge medication was obtained
(Table 2).
Patients screened and met inclusion criteria
2015–2019
n = 4846
Final cohort
n = 2015
Exclusions: n = 229
• Elevation of troponin and/or ECG changes not thought to be due to an ACS.
• eGFR <15 mL/min/m2) or receiving/planned to receive renal replacement therapy.
• Not a New Zealand resident.
Not enrolled: n = 2601
• Patient declined research 536, 21%; declined genetic research 14, 0.5%.
declined venepuncture 110, 4% ; declined other 86, 3%.
No interpreter 372, 14%.
Patient discharged or transferred to another hospital 916, 35%.
Patient too unwell 16%.
Other factors 406, 16%.
Withdrawn from study: n = 1
Figure 2. Flow diagram of screening and enrolment into the MENZACS.
3.1. Baseline Characteristics
The baseline demographics of the initial MENZACS cohort are shown in Table 1. The
median age was 61 years, with 61% aged <65 years, and the cohort was predominantly male
(79%). M
¯
aori constituted 13% of the cohort, Pacific and Indian peoples each comprised 5%,
and 74% of participants were of European ethnicity. Based on the ethnic distribution and
demographics of a contemporaneous cohort of first-time acute coronary syndrome patients
in the ANZACS-QI registry, there is unlikely to have been an ethnic or risk factor bias in
enrolment status in MENZACS [4].
Nineteen percent were in the most deprived quintile, 19% had diabetes, and 24% were
current smokers. Almost all patients underwent angiography during the index admission
and revascularisation rates were high, with 90% of the cohort undergoing either PCI or
CABG during their hospital admission. Theserates are consistent with the recruiting centres
for MENZACS being secondary and tertiary referral centres for coronary intervention.
Comprehensive information on extent of coronary artery disease, left ventricular function,
GRACE score [34], and admission and discharge medication was obtained (Table 2).
3.2. Quality Assessment
3.2.1. Data Linkage
A quality assurance assessment using data on the first 500 participants was per-
formed. It confirmed that all MENZACS data sources can be linked via an encrypted NHI
number. This involved transferring and merging the genetic database with MENZACS
and ANZACS-QI data held at the National Institute of Health Innovation, University of
Auckland (NIHI) and similarly, transferring, and merging diet data. A MENZACS study
encrypted NHI was applied to the final merged dataset.
Cardiogenetics 2021,11 92
Table 2. Baseline clinical characteristics of the MENZACS cohort.
n(%) Denominator
Type of acute coronary syndrome 2015
STEMI 827 (41.0)
Non-STEMI 1083 (53.8)
Unstable angina 105 (5.2)
Coronary angiography 1968 (99.1) 1985
Ejection fraction assessed 1824 (92.4) 1974
Ejection fraction <50% 693 (35.1)
GRACE in-hospital score 1984
Low <1% 580 (29.2)
Intermediate 1–2% 864 (43.6)
High 3% 540 (27.2)
Management 1971
PCI 1408 (71.4)
CABG 371 (18.8)
Medications on admission 2015
Statin 493 (24.5)
Beta-blocker 241 (12.0)
ACEi/ARB 566 (28.1)
Aspirin 324 (16.1)
Medications on discharge 1972
Statin 1922 (97.5)
Beta-blocker 1652 (83.8)
ACEi/ARB 1550 (78.6)
Aspirin 1927 (97.7)
Other antiplatelet agent 1636 (83.0)
Dual antiplatelet therapy 1611 (81.7)
STEMI = ST-elevation myocardial infarction; GRACE = Global Registry of Acute Coronary Events; PCI = percu-
taneous coronary intervention; CABG = coronary artery bypass graft; ACEi = angiotensin-converting-enzyme
inhibitor; ARB = angiotensin receptor blocker.
3.2.2. DNA Quality and Quantification
By using 100 samples from four sites, genomic DNA was isolated from 3 mL of
frozen whole blood. All samples had DNA yields sufficient for genotyping (
50 ng/
µ
L)
and 96% of samples had 260/280 ratios > 1.7, which indicated high purity. Genotyping
was performed for 23 coronary-disease associated or gender-related single nucleotide
polymorphisms (SNPs) using an Agena Bioscience MassARRAY
®
. A genetic risk score
based on published methods [
31
] was able to be calculated for 97% of samples and gender
was correctly identified in 100% of samples (see Supplementary Figure S1).
4. Discussion
MENZACS has been established as a significant epidemiological bioresource for
the study of environmental and genetic factors contributing to ACS in New Zealand’s
contemporary ethnically diverse population. Genomic research into cardiovascular disease
in New Zealand with the Post-Myocardial Infarction Study and Coronary Disease Cohort
Study have already contributed valuable insights into genomic risk variants associated
with clinical outcome and age of onset of CVD [
35
,
36
]. Building on this experience, the
Cardiogenetics 2021,11 93
MENZACS cohort will have comprehensive data to gain a better understanding of genetic
influence on the varying phenotypic presentations of ACS in New Zealand’s population
and will explore the clinical utility of genomics in predicting secondary outcomes. The
strength of this registry-based study is in the breadth and depth of data gathered, which
will enable research into clinical, nutritional, genomic, lipidomic, and epigenetic factors
influencing secondary outcomes.
The current MENZACS cohort reflects a population of patients who are treated in-
tensively at the time of their index ACS admission, with 99% undergoing coronary an-
giography, 90% having coronary revascularization, and the vast majority prescribed statin
(97%) and dual antiplatelet therapy (82%) at the time of hospital discharge. Compared to
the ANZACS-QI registry cohort of patients with first-time ACS over a similar time period
(January 2015 to December 2016), there were slightly more M
¯
aori participants and more
patients had STEMI [
8
]. However, the overall demographic differences are small and reflect
a referral population in the enrolment centres in the current study. Importantly, with the
requirement to represent patients who undergo coronary angiography, ANZACS-QI only
captures approximately 60% of New Zealanders admitted to hospital with their first ACS
and there are important differences in patient characteristics and outcomes between those
who are and are not included in the registry. Patients who are not captured in ANZACS-QI
are older, are more commonly women with a higher comorbidity burden, and are more
than twice as likely to experience death or a non-fatal CV readmission within 12 months of
the index ACS admission [8].
The initial phase of this research has highlighted several findings relevant to the study
of acute coronary disease in New Zealand. Firstly, MENZACS has served as a “proof of
concept” that research studies can be successfully embedded within a web-based electronic
registry used for clinical quality improvement purposes. The level of data capture was very
high with minimal missing data and successful linkage of multiple datasets; this enabled a
cost effective and efficient means of running a registry-based research study in an acute
care environment. Linkage to national and routinely collected health data has allowed
anonymised long-term follow-up of patient outcome, rehospitalisation, and medication
dispensing. One limitation of the study is that there can be no feedback of information to
an individual patient due to the anonymisation process. However, participants can opt to
be approached for future research studies as part of the consent process.
Another limitation of the study is that a relatively high percentage of screened patients
were not able to be enrolled in the study. The logistic issues related to performing a study
such as MENZACS in tertiary and secondary referral centres have been significant. Patients
are often transferred back to the referring hospital soon after coronary intervention at
regional centres and may be sedated or are too unwell to enroll in the study. In addition,
the length of hospital stay in the contemporary era of ACS management is short, resulting
in a limited time period to approach patients for research during an acute index ACS
admission. Overall, the willingness to participate in a study involving donating DNA
has been very high and the research team has worked hard to ensure appropriate and
detailed explanation is given in a culturally appropriate context. The M
¯
aori Governance
Group has been integral to guiding culturally appropriate study processes, including
conceptualising the study goals, facilitating recruitment strategies, developing sample
handling and disposal protocols, and data governance.
The vast majority of studies examining the genetic contribution to the risk of secondary
events in those with established coronary artery disease have been in European popula-
tions, with the largest being the GENIUS-CHD consortium involving over 185,000 partic-
ipants [
37
,
38
]. However, there are far fewer studies of non-European populations who
are at particularly high risk [
39
,
40
]. The predictive value of polygenic risk scores de-
rived from cohorts of predominantly European ancestry can be attenuated in other ethnic
groups and this emphasises the need for well phenotyped studies involving indigenous
populations [
11
,
41
,
42
]. This is a crucial goal as genomic research focussed on European pop-
ulations can compound inequity when applying the results of the research, for example, in
Cardiogenetics 2021,11 94
the utility of risk prediction and health prevention strategies [
41
,
43
45
]. The high incidence
of premature CVD and worse cardiovascular health outcomes among some ethnic groups
and a single national public healthcare system with a unique patient identification number
renders New Zealand ideally suited to study the genetic and environmental drivers and
influences on cardiometabolic outcomes.
The first phase of MENZACS analyses will focus on the association of established
cardiovascular risk factors with secondary cardiovascular outcomes, and the development
of incremental risk prediction tools utilising genetic, biomarker, lipidomic, and epigenetic
markers. Subsequent studies will examine inter-ethnic variation, nutritional, lifestyle,
pharmacogenomic, and kaupapa M
¯
aori approaches to optimising outcomes following an
ACS, and assist in personalisation of risk stratification, and therapeutic intervention.
Supplementary Materials:
The following are available online at https://www.mdpi.com/article/10
.3390/cardiogenetics11020010/s1, Figure S1: Distribution of 27 SNP genetic risk score by gender.
Author Contributions:
Conceptualization, M.E.L., V.A.C., R.N.D., K.K.P., N.E. and A.R.; methodol-
ogy, M.E.L., V.A.C., R.N.D., K.K.P., N.E. and A.R.; writing—original draft preparation M.E.L., V.A.C.,
R.N.D., K.K.P., N.E., A.R., review and editing, M.E.L., V.A.C., R.N.D., K.K.P., N.E., A.R., S.A., Y.C.,
K.E.B., C.W., R.S., A.K., W.H., G.D., R.T., A.M.R., G.P., P.G. All authors have read and agreed to the
published version of the manuscript.
Funding:
The MENZACS study is supported by grants from the Heart Foundation (Heart Health
Research Trust grant 1957), Healthier Lives National Science Challenge (Ministry of Business In-
novation and Employment Reference UOOX1902), Green Lane Research and Educational Fund
(17/26/4130), Freemasons Foundation, and the University of Auckland. R.N.D. is the holder of the
Heart Foundation Chair of Heart Health; K.K.P. is the holder of the Heart Foundation Hynds Senior
Fellowship; N.E. holds a NZ Heart Foundation Post-doctoral Research Fellowship; K.E.B. holds a Sir
Charles Hercus Health Research Fellowship from the Health Research Council of New Zealand.
Institutional Review Board Statement:
The study was conducted according to the guidelines of the
Declaration of Helsinki, and approved by the New Zealand Northern B Health and Disability Ethics
Committee (Ref: 15/NTB/59) 14 April 2015.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Restrictions apply to the availability of these data.
Acknowledgments:
MENZACS Executive Group; M Legget * (Chair and Co-PI), V Cameron (Co-PI),
S Aish * (Project manager), R Doughty *, N Earle *, K Poppe *, A Rolleston, C Wall. * Coordinating
Centre. MENZACS Steering Group; M Legget, R Doughty, R Stewart, A Kerr, W Harrison, G
Devlin, V Cameron, R Troughton, AM Richards, S Aish, K Poppe, C Wall, G Porter, and P Gladding.
International Advisors. J. Danesh (Cambridge, UK), and J Howson (Oxford, UK). MENZACS M
¯
aori
Governance Group; A Rolleston (Chair), K Southey, K Henare, R Stewart, C Grey, and H Wihongi.
MENZACS Data Science Group; K Poppe (Chair), N Earle, J Howson, T Lumley, and A Pilbrow.
Study centres; University of Auckland (M Oakes-Ter Bals, M Heath, P Shepherd, A Rykers, T Frugier,
J Copedo, B Wu, Y Jiang, B Seers, A Chaptynova, C Fyfe, S Wall, and N Kluger). Auckland City
Hospital (R Stewart, and K Marshall). Christchurch Hospital and Christchurch Heart Institute (V
Cameron, A Pilbrow, S Prue, L Skelton, and R Troughton,). Waikato Hospital (C Nunn, G Devlin, V
Pera, L Lowe, S Pilkington, and G Francis). Middlemore Hospital (A Kerr, L Pearce, M Ma, R Railton,
L Sharp, P Sharma, and J Gilmore). Tauranga Hospital (G Porter, J Goodson, J Shippey, J Tisch, K
Presley, T McKenzie, and CCU Staff). North Shore Hospital: T Scott, G McAnnalley, C Hulbert, K
Smith, C Campbell, K Stanley, C Clow, and J Chen. AgResearch: K. Fraser. Enigma Solutions Ltd.: S
Breen, and C Wiltshire. The MENZACS investigators would like to express their deepest gratitude to
all the patients who have participated in the study.
Conflicts of Interest:
RND has received research grants (administered through host institution the
University of Auckland) from the NZ Heart Foundation, Health Research Council of New Zealand,
Roche Diagnostics and Bayer. AMR holds grants and/or aid in kind and has received speaker fees
and Advisory Board fees from Roche Diagnostics, Abbot Labs, Sphingotec, Critical Diagnostics, and
Thermo Fisher and has received biomarker study support in kind and/or as grants from AstraZeneca
and Bristol Myers Squibb. RT has received grant funding and consulting fees from Roche Diagnostics.
Cardiogenetics 2021,11 95
PG holds stock in Theranostics Lab, a molecular diagnostics company providing polygenic risk
scores. All other authors declare no conflicts of interest.
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... 13 Many current publications are investigating genetic variations through genome-wide association studies that may help elucidate the variations in ACS presentation among ethnic and racial groups. 14,15 African American Population ...
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Introduction Anticoagulants are among the most frequently prescribed medications in the United States. Racial and ethnic disparities in incidence and outcomes of thrombotic disorders are well-documented, but differences in response to anticoagulation are incompletely understood. Objective The objective of this review is to describe the impact of race and ethnicity on surrogate and clinical end points related to anticoagulation and discuss racial or ethnic considerations for prescribing anticoagulants. Methods A PubMed and MEDLINE search of clinical trials published between 1950 and May 2018 was conducted using search terms related to anticoagulation, specific anticoagulant drugs, race, and ethnicity. References of identified studies were also reviewed. English-language human studies on safety or efficacy of anticoagulants reporting data for different races or ethnicities were eligible for inclusion. Results Seventeen relevant studies were identified. The majority of major trials reviewed for inclusion either did not include representative populations or did not report on the racial breakdown of participants. Racial differences in pharmacokinetics, dosing requirements, drug response, and/or safety end points were identified for unfractionated heparin, enoxaparin, argatroban, warfarin, rivaroxaban, and edoxaban. Conclusions Race appears to influence drug concentrations, dosing, or safety for some but not all direct oral anticoagulants. This information should be considered when selecting anticoagulant therapy for nonwhite individuals.
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Objective Following acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS. Methods Adults aged 30–79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS. Results The PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%–35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%–51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell’s c-statistic was 0.69 and 0.68, respectively. Conclusions The PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS.
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Aims: Clinical registry-derived data are widely used to represent patient populations. In New Zealand (NZ), a national registry - the All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry - aims to include all patients undergoing coronary angiography; other acute coronary syndrome (ACS) patients are also registered but without complete capture. This study compares national hospitalisation data of all first-time ACS admissions in NZ with patients in the ANZACS-QI registry, to investigate the use of clinical registry-derived data in research and in assessing clinical care. Methods and results: Patients admitted with first-time ACS in the NZ National Hospitalisation Dataset between 01/01/2015-31/12/2016 were included. Clinical characteristics and time to 12-month clinical outcomes were compared between patients captured and not-captured in the registry. 16,569 patients were admitted with first-time ACS, median age 69 years, 61% male; 60% (n = 9918) were enrolled in ANZACS-QI. Registry-captured patients were younger, more often male, and with a lower comorbidity burden than non-captured patients. Overall, 16% patients died within 12 months, 15% experienced a non-fatal cardiovascular readmission and 28% either died or were readmitted. Patients not captured in the registry were more than twice as likely to have experienced death or a non-fatal cardiovascular readmission within 12 months as captured patients. Conclusions: First-time ACS patients captured in the ANZACS-QI registry had very different clinical characteristics and outcomes than those not captured. Cardiovascular registry-derived data is dependent on registry design and may not be representative of the wider patient population; this must be considered when using registry-derived data.
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Precision oncology guided by genomic research has an increasingly important role in the care of people with cancer. However, substantial inequities remain in cancer outcomes of Indigenous peoples, including Indigenous Māori in Aotearoa New Zealand (New Zealand). These inequities will be perpetuated unless deliberate steps are taken to include Indigenous peoples in all parts of cancer research-as research participants, in research leadership, and in research governance. This approach is especially important when there have been historical breaches of trust that have discouraged their participation in health research. This Personal View describes a precision oncology research roadmap for neuroendocrine tumour research, which seeks to reflect the values of New Zealand's Indigenous Māori people. This roadmap includes facilitating ongoing dialogue, Māori leadership, reciprocity, agreed kawa (guiding principles), tikanga (cultural protocols), and honest monitoring of what is and what is not being achieved. We challenge cancer researchers worldwide to generate locally appropriate roadmaps that honestly assess their practices to benefit Indigenous people internationally.
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Background: The All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry was designed to collect data on all coronary angiograms and percutaneous coronary interventions (PCI) in New Zealand, and all acute coronary syndromes (ACS) associated with these procedures. This study compares the completeness of capture in ANZACS-QI of coronary procedures and ACS admissions with those recorded in the National Hospitalisation Dataset and evaluates data quality by assessing agreement in ACS diagnoses and coronary procedures between datasets. Methods: The national dataset, which included all New Zealand public hospital admissions in 2015 (n=962,700 episodes), was anonymously linked with the ANZACS-QI CathPCI (n=14,649 coronary angiogram episodes) and ACS cohorts (n=8,141 episodes) for 2015. Total numbers of coronary angiogram, PCI and ACS admissions were used as denominators and calculated by combining unique episodes from both data sources. Results: Of all coronary angiogram episodes (n=15,377) and all PCI episodes (n=5,711), 92% were captured in both datasets, 5% in the national dataset only and 3% in ANZACS-QI only. Overall, 95% of coronary angiogram and PCI episodes were captured in ANZACS-QI. Of ACS episodes with associated coronary angiography (n=8,237), 85% were captured. Overall, 54% of all ACS episodes (n=15,167) were captured, including 71% in <70-year-olds. Seventy-five percent of all ST-elevation myocardial infarctions (STEMI) were captured. Ninety percent of ACS diagnoses in ANZACS-QI had a matching diagnosis in the national dataset. There was excellent agreement in recorded gender, date of birth and ethnicity (>99%). Sub-type of ACS was also highly concordant for STEMI and non-STEMI diagnoses (92% and 89% agreement, respectively). Conclusions: Consistent with its aim, the ANZACS-QI registry captured almost all New Zealand public hospital coronary angiography and PCI procedures including those associated with an ACS diagnosis. The high level of agreement between the registry and national dataset supports the use of both datasets for ongoing quality improvement reporting and research.
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Background: The "GENetIcs of sUbSequent Coronary Heart Disease" (GENIUS-CHD) consortium was established to facilitate discovery and validation of genetic variants and biomarkers for risk of subsequent CHD events, in individuals with established CHD. Methods: The consortium currently includes 57 studies from 18 countries, recruiting 185,614 participants with either acute coronary syndrome, stable CHD or a mixture of both at baseline. All studies collected biological samples and followed-up study participants prospectively for subsequent events. Results: Enrollment into the individual studies took place between 1985 to present day with duration of follow up ranging from 9 months to 15 years. Within each study, participants with CHD are predominantly of self-reported European descent (38%-100%), mostly male (44%-91%) with mean ages at recruitment ranging from 40 to 75 years. Initial feasibility analyses, using a federated analysis approach, yielded expected associations between age (HR 1.15 95% CI 1.14-1.16) per 5-year increase, male sex (HR 1.17, 95% CI 1.13-1.21) and smoking (HR 1.43, 95% CI 1.35-1.51) with risk of subsequent CHD death or myocardial infarction, and differing associations with other individual and composite cardiovascular endpoints. Conclusions: GENIUS-CHD is a global collaboration seeking to elucidate genetic and non-genetic determinants of subsequent event risk in individuals with established CHD, in order to improve residual risk prediction and identify novel drug targets for secondary prevention. Initial analyses demonstrate the feasibility and reliability of a federated analysis approach. The consortium now plans to initiate and test novel hypotheses as well as supporting replication and validation analyses for other investigators.