Key Features
The Melbourne Children’s LifeCourse Initiative enables researchers to more effectively
leverage the value of existing cohorts to improve child and adolescent health.
The initiative includes 33 studies hosted by or in collaboration with the Murdoch
Children’s Research Institute, including 22 core longitudinal cohorts that are fully
catalogued.
These core studies capture health and development for >40 000 children, young people
and families tracked for up to four decades, enriched through linkage to administrative
data and collection of biosamples.
Metadata are standardized and curated by LifeCourse to allow researchers internationally
to search and browse information about the available data and request data access
via https://lifecourse.melbournechildrens.com.
Beyond the significant contributions of individual studies, a programme of research
working across cohorts is increasingly emerging that addresses a shared interest in
pathways leading to mental health, cardiometabolic health and immune-related conditions.
Efforts of cohort researchers are informed by partnering statisticians’ ongoing development
and refinement of analytical methods for observational studies, with a key focus on
causal inference to inform the development of policy, interventions and trials.
Data resource basics
The major health challenges facing children and adolescents increasingly reflect chronic
problems that have complex biopsychosocial and environmental dimensions.
1
In high-income countries, nearly a quarter of children and adolescents are overweight
or obese,
2
up to a quarter experience a mental disorder in any given year,
3
allergic diseases continue to rise
4
and life-threatening diseases such as cancer remain a major problem.
5
Overall, children and young people from disadvantaged backgrounds are disproportionately
impacted by adverse health and developmental outcomes
6
,
7
and these disparities are expected to be further exacerbated in the context of the
COVID-19 pandemic.
8
Despite their burden and impact on health pathways across the life course,
9
,
10
the origins of many of the major health issues facing children and adolescents are
not yet well understood. This limits our capacity to realize opportunities for early
prevention and intervention (e.g. on factors such as social disadvantage and infection)
that may have cumulative health benefits over the life course.
10
Cohort studies provide a valuable resource in this regard, particularly when enriched
with biospecimens. They allow the impacts of early-life exposures and complex biopsychosocial
mechanisms to be investigated over extended periods of development, including those
exposures that could never be ethically, cost-effectively or time-efficiently examined
within stand-alone randomized trials.
11
This is facilitated by recent methodological advances, which provide a framework for
analysing causal relationships through explicit emulation of the hypothetical ‘target
trial’ that would have ideally been conducted.
11
,
12
In addition, there remains a largely untapped potential to work systematically across
cohorts. For example, appropriate harmonization and pooling of data from multiple
cohorts can improve precision of estimation when investigating rare exposures and/or
outcomes.
13
Cohorts can also be brought together to enhance confidence in findings through replication
14
and to address questions spanning different age periods or constructs.
15
There are, however, a range of barriers to more fully realizing the potential gains
of cross-cohort approaches. For example, discoverability of common and complementary
data elements across cohorts can be hampered by different ways of describing and documenting
data across studies. Restrictive data access protocols can limit the feasibility of
analysing participant-level data from multiple cohorts. Working in siloes poses a
barrier to achieving alignment between cohort measures and protocols, which limits
opportunities for data alignment and pooling. Even where aligned data are available,
cohort researchers can lack opportunities to connect across teams and with methods
experts to develop necessary skills and knowledge.
In the Northern Hemisphere, initiatives have emerged to tackle these barriers by bringing
child and adolescent cohort studies that capture a wide range of exposures and outcomes
together in common platforms, enabling their use both independently and within cross-cohort
designs. An example is Cohort and Longitudinal Studies Enhancement Resources (CLOSER),
16
which was established in 2012 and now brings together 19 major longitudinal cohorts
in the UK (14 child and adolescent). The EU Child Cohort Network similarly brings
together 18 cohorts to allow investigations of early-life exposures and adult health
outcomes.
17
These platforms build on the important groundwork developed by consortia drawing studies
together around specific conditions, such as the International Childhood Cancer Cohort
Consortium (I4C) focused on childhood cancer,
5
which have required the development of sophisticated governance models and methodological
approaches to realize their objectives.
5
Origins and aims of LifeCourse
An equally rich history of early-life cohort studies in the Southern Hemisphere has
been largely underrepresented in emerging platforms to date. In response, the Murdoch
Children’s Research Institute (MCRI), located in Melbourne, Australia, established
the LifeCourse initiative in 2013 (https://lifecourse.melbournechildrens.com), with
the aim of bringing together the large hub of cohort studies that were hosted by or
in collaboration with the MCRI at that time (representing over half of the total number
of child and adolescent cohorts in the Australasian region). LifeCourse was established
in partnership with the University of Melbourne Department of Paediatrics and the
Royal Children’s Hospital (which, together with MCRI, comprises the Melbourne Children’s
Campus) and drew on wide ranging collaborations via the participating cohorts and
research teams. A small leadership committee oversees LifeCourse, supported by a project
team, partnering with a statistical group that undertakes research in analytic methods
for observational studies, and collaborating with investigators, project managers
and data users across the cohorts.
The LifeCourse initiative now supports 33 studies in total, each of which is independently
managed by their study team. This includes 22 active longitudinal cohorts that have
metadata fully integrated into the LifeCourse platform and at a minimum data-sharing
protocols in place that enable collaboration or data use beyond the primary study
team (Table 1). Together these 22 core studies capture the development of >40 000
children and young people and their families (Table 1). They include traditional population-based
prospective longitudinal cohort studies that are broadly representative, though participant
retention and engagement of culturally and socially diverse populations, such as families
from Aboriginal and Torres Strait Islander and refugee backgrounds, remain a key focus.
They also include cohorts from randomized–controlled trials, largely in clinical populations,
that have extended follow-up for analysis beyond the trial’s primary focus. Beyond
the 22 core cohorts, LifeCourse continues to provide more basic support to an additional
11 studies (Supplementary Table S1, available as Supplementary data at IJE online)
that were engaged early in the inception of the initiative and remain scientifically
significant but reflect different study designs (e.g. tissue banks, cross-sectional
surveys, cohort consortia) or have more restricted data access.
Table 1
Features of core longitudinal cohorts supported by the LifeCourse platform
Cohort name
N
Primary study type
Sampling frame
Year commenced
Age range (years)
Number of data collection waves
Study focus
Data acquisition
Protocol or illustrative reference
Surveys
Bio samples
Imaging
Data linkage
AQUA: Asking Questions about Alcohol in Pregnancy Study
2146
Cohort
Women attending one of seven antenatal clinics in 2011–12 who were <19 weeks’ pregnant
with a single baby
2011
0–8
7
Alcohol consumption during pregnancy and health and development of index child at
birth and over childhood
Y
Y
Y
Y
37
AREST CF (Australian Respiratory Early Surveillance Team for Cystic Fibrosis) Early
Surveillance Program: Detection of early lung disease in cystic fibrosis
168
Case–control
The longitudinal inception cohort consists of children diagnosed with CF and recruited
before 12 weeks of age. The repeated cross-sectional cohort consists of children diagnosed
with CF aged 6 years and under. Control groups were also recruited
2006
0–8
Varies by case/control and sub-study involvement
Assessment, treatment and prevention of cystic fibrosis lung disease in young children
Y
Y
Y
–
38
ART Studies: Review of the health of adults conceived with and without Assisted Reproductive
Technologies
Mothers: 1524, young adults: 1096
Case–control
ART mothers: traced from clinic database (Melbourne IVF and Monash IVF in Victoria,
Australia). Non-ART mothers: population-based controls recruited by random digit dialling
(households in Victoria, Australia). ART and non-ART young adults: approached with
maternal consent
2008
18–35
2
Health and development of young adults born with and without assisted conception
Y
–
–
–
39
Australian Temperament Project (ATP)/Generation 3 (ATPG3)
ATP: 2443;ATPG3: 1167
Longitudinal cohort
A representative sample of families with a 4- to 8-month-old child attending maternal
and child health centres across 20 local government areas in Victoria were recruited
and followed every 2 years across childhood and adolescence and every 3 years across
young adulthood. In 2012, the study expanded to a third generation by recruiting offspring
born to original ATP participants and their partners
1983
ATP: 0–38, ATPG3: 0–12
15 (ATP), 5 (ATPG3)
Social-emotional development from infancy to adulthood, and transgenerational (pre-conception)
determinants of infant mental health, attachment and wellbeing
Y
Y
Y
Y
40
Baby Biotics
167
RCT
Infants aged 0–3 months with infant colic. Recruitment was from a range of services
widely used by and readily accessible to parents seeking medical advice regarding
their crying babies in Melbourne, Australia, followed up at 3 years
2011
0–1
7
Effect of probiotic Lactobacillus reuteri on infant colic and maternal mental health
and family functioning. Long-term outcomes of colic
Y
Y
–
–
41
Barwon Infant Study (BIS)
1074
Longitudinal cohort
Antenatal recruitment of eligible women from two hospitals in the Barwon region of
Victoria (at 28 weeks’ gestation)
2010
0–11
12
An investigation into the early-life origins of a range of non-communicable diseases
in the modern environment
Y
Y
Y
Y
42
Children’s Attention Project (CAP) and Neuroimaging of the Children’s Attention Project
sub-study (NICAP)
497
Case–control
CAP: Grade 1 children with and without ADHD, recruited across 43 socio-economically
diverse government primary schools across Melbourne, Australia. NICAP: Recruited from
CAP cohort, with equal number of cases and controls
2011
7–13
5
ADHD with a range of outcomes: mental health, academic, family and child wellbeing,
quality of life
Y
Y
Y
Y
43
,
44
Childhood to Adolescence Transition Study (CATS)
1239
Longitudinal cohort
All Grade 3 students (8–9 years of age) from a stratified cluster sample of schools
in Melbourne, Australia were invited to take part
2012
8–17
10
The health and emotional development of children as they pass through puberty, the
middle years of school and the transition to high school
Y
Y
Y
Y
COBRA: Childhood Overweight BioRepository of Australia
500
Cohort
Presentation to the specialist weight management service at The Royal Children’s Hospital
2009
2–18
2
To develop a unique biorepository of data and biological samples from overweight and
obese children
Y
Y
–
–
45
Early Language in Victoria Study (ELVS)
1910
Longitudinal cohort
Maternal and child health nurses approached all parents of babies aged 8–10 months
within six local government areas of Melbourne, Australia
2003
0–20
14
Speech and language development from infancy to adulthood
Y
Y
Y
Y
46
HealthNuts
5300
Longitudinal cohort
12-month-old infants presenting for routine scheduled vaccination at local government-led
immunization clinics across Melbourne, Australia
2007
1–15
4
Understanding the natural history and determinants of allergic disorders including
food allergy, asthma, eczema and hay fever
Y
Y
Y
Y
4
International Youth Development Study (IYDS)
5769
Longitudinal cohort
A two-stage cluster sample design was used to recruit students in Victoria, Australia
and Washington State, USA
2002
9–28
9
Risk and protective factors of healthy and problem behaviours in young people, and
how differences in Australian and US cultures and schools affect youth development
Y
–
–
Y
27
Longitudinal Study of Australian Children’s Child Health CheckPoint (LSAC CheckPoint)
1874
Biophysical module within longitudinal cohort
LSAC had a two-stage clustered sampling design, randomly selecting 10% of all Australian
postcodes (stratified by state and urban/rural), then children registered in Medicare
Australia’s database and aged 3–19 months (B cohort) or 4–5 years old (K cohort).
B cohort families who completed a Wave 6 interview were invited into CheckPoint
2004
0–18
One module within multi-wave study
LSAC is Australia’s largest and only nationally representative children’s longitudinal
study. The cohorts are followed with a broad focus including health and development,
education, family and parenting characteristics and socio-economic environment. LSAC’s
Child Health CheckPoint is a one-off physical health and biospecimens module for the
B cohort children and parents
Y
Y
Y
Y
47
Melbourne Infant Study: BCG for Allergy and Infection Reduction (MIS BAIR)
1272
RCT
Pregnant women attending participating antenatal clinics in Melbourne and Geelong
were approached to participate. Pregnant women or mothers interested in joining the
study but not being cared for at a study maternity site were also enrolled
2013
0–5
16
To assess the effect of neonatal BCG (tuberculosis) vaccination on clinical allergy
and infection outcomes over the first 5 years of life
Y
Y
Y
–
48
Memory Maestros
Whole cohort: 1802. RCT: 452
RCT
Observational cohort: children in grade 1 classrooms from 44 schools in metropolitan
Melbourne (Australia). RCT: those children from the observational cohort screened
as having low working memory
2012
5–9
5
Development of working memory in children
Y
Y
–
Y
49
Mothers’ and Young People’s Study (MYPS)
1507
Longitudinal cohort
Prospective pregnancy cohort of first-time mothers and their first-born children recruited
at six public hospitals in Melbourne
2003
0–18
15
Maternal mental health and wellbeing, child health and wellbeing from birth to age
18 years and intergenerational impacts of exposure to intimate-partner violence
Y
–
–
–
50
Peri/post-natal Epigenetic Twins Study (PETS)
250 twin pairs
Longitudinal cohort
Women attending multiple-pregnancy clinics at three Melbourne hospitals (Royal Women’s
Hospital, Monash Medical Centre, Mercy Hospital for Women) who were at 18–22 weeks’
gestation
2007
0–11
7
Investigating whether epigenetic markers measured at birth and early life can provide
clues to the causal links between intrauterine exposures influencing perinatal phenotype
and the risk of chronic cardiometabolic and neurodevelopmental diseases later in life
Y
Y
Y
Y
51
right@home
736
RCT
Pregnant women attending antenatal clinics in select Victorian and Tasmanian regions
with 2 or more of 10 risk factors
2013
0–7
17
Promoting equity in children’s early learning and development for families experiencing
high levels of adversity
Y
Y
–
Y
52
Triple B: The Triple B Pregnancy Cohort Study (Bumps, Babies and Beyond)
1623
Longitudinal cohort
Women attending antenatal services attached to major hospitals, and specialist drug
and alcohol antenatal services, in NSW and WA
2009
0–8
8
Effects of substance use and mental health during pregnancy in women and partners
on infant development and family functioning
Y
Y
–
Y
53
Victorian Adolescent Health Cohort Study (VAHCS)/Victorian Intergenerational Health
Cohort Study (VIHCS)
VAHCS: 2032; VIHCS: 1026
Longitudinal cohort
VAHCS: representative sample of mid-secondary school adolescents (aged 14–15 years)
across Victoria (Australia) were selected using a two-stage cluster sampling procedure.
VIHCS: all active members of VAHCS who reported having a child between the recruitment
phases (2006 and 2014)
1992
VAHCS: 14–35, VIHCS: 0–8
11 (VAHCS), 4 (VIHCS)
Mental and physical health problems and risk behaviours in the adolescent-to-adulthood
transition and the role of pre-conception factors in outcomes of the next generation
Y
Y
–
Y
54
VicCHILD: Victorian Childhood Hearing Impairment Longitudinal Databank
1000
Register with longitudinal data collection
Victorian children with permanent hearing loss. Since 2012, recruitment has been through
the Victorian Infant Hearing Screening Program. Since 2016, additional recruitment
has been through a paediatric hearing clinical service
2012
0–18.5
6
Advancing understanding of hearing loss
Y
Y
–
Y
55
VITALITY: Primary prevention of infant food allergy: an RCT of post-natal vitamin
D supplementation
2681
RCT
Randomly selected council-run immunization sessions, maternal and child health nurse
sessions, and online across Melbourne, Australia
2014
0–6
7
To assess the role of post-natal vitamin D supplementation for the prevention of infant
food allergy, lower respiratory infections and eczema
Y
Y
–
Y
56
Y = Yes. ADHD, attention-deficit/hyperactivity disorder; RCT, randomized–controlled
trial. For further details and updates since the time of submission, see https://lifecourse.melbournechildrens.com/cohorts/.
LifeCourse aims to enable local and international researchers to capitalize on the
availability of these extensive cohort data to advance understanding of health issues
emerging over the life course. This includes an ongoing focus on addressing the major
barriers to cross-cohort research, translated into four interrelated platform goals
(Figure 1):
Figure 1
Overview of the LifeCourse initiative
Promoting data discoverability by curating browsable and searchable metadata, allowing
researchers to easily identify relevant data available within and across cohorts.
Facilitating data reuse by providing a central gateway for data access requests, which
optimizes efficiency on the applicant side and ensures that all ethical and governance
requirements are upheld for cohort custodians.
Promoting prospective harmonization by providing guidance on common measurement tools
and facilitating the collection of aligned cohort data around key initiatives.
Creating opportunities for connection and synergy through a range of ‘meeting places’,
including linking researchers to methodological expertise in the partnering statistical
group.
The outcomes of these efforts include a growing programme of research focused on mental
health, cardiometabolic health and immune-related conditions, strengthened through
the use of cross-cohort methodologies enabled by the platform.
Data collected
Across the 22 core cohorts (Table 1), data have been collected via surveys (e.g. web-based
questionnaires), biosamples (e.g. blood), imaging (e.g. functional magnetic resonance
imaging; fMRI), direct assessments (e.g. dental check), records abstraction (e.g.
medical records) and data linkage (e.g. academic testing) (Table 1). There is considerable
measurement consistency across outcomes and exposures relevant to focal areas of mental
health (e.g. symptom inventories), cardiovascular health (e.g. obesity) and immune
responses and related conditions (e.g. allergic diseases; Table 2). In 2020–2021,
over half of the cohorts also rapidly adapted to collecting data on the direct (e.g.
infection) and indirect (e.g. mental health) impacts of COVID-19.
Table 2
Data captured by core LifeCourse cohorts across key research streams
Cohort name
Demographics (e.g. gender, age, socio-economic position)
Mental health (e.g. symptom inventories, diagnosis)
Cardiometabolic health (e.g. risk and protective factors, direct assessments)
Immune-related conditions (e.g. allergies and eczema, inflammatory biomarkers)
COVID-19 impacts (e.g. infection, financial impacts)
AQUA: Asking Questions about Alcohol in Pregnancy Study
Y
Y
Y
–
–
AREST CF (Australian Respiratory Early Surveillance Team for Cystic Fibrosis) Early
Surveillance Program: Detection of early lung disease in cystic fibrosis
Y
Y
Y
Y
–
ART Studies: Review of the health of adults conceived with and without Assisted Reproductive
Technologies
Y
Y
Y
Y
–
Australian Temperament Project (ATP)/Generation 3 (ATPG3)
Y
Y
Y
Y
Y
Baby Biotics
Y
Y
–
Y
–
Barwon Infant Study (BIS)
Y
Y
Y
Y
Y
Children’s Attention Project (CAP) and Neuroimaging of the Children’s Attention Project
sub-study (NICAP)
Y
Y
Y
–
–
Childhood to Adolescence Transition Study (CATS)
Y
Y
Y
Y
Y
COBRA: Childhood Overweight BioRepository of Australia
Y
Y
Y
Y
–
Early Language in Victoria Study (ELVS)
Y
Y
Y
–
Y
HealthNuts
Y
Y
Y
Y
Y
International Youth Development Study (IYDS)
Y
Y
Y
–
–
Longitudinal Study of Australian Children’s Child Health CheckPoint (LSAC CheckPoint)
Y
Y
Y
Y
–
Memory Maestros
Y
Y
Y
–
–
Melbourne Infant Study: BCG for Allergy and Infection Reduction (MIS BAIR)
Y
Y
Y
Y
Y
Mothers' and Young People's Study (MYPS)
Y
Y
Y
–
Y
Peri/post-natal Epigenetic Twins Study (PETS)
Y
Y
Y
Y
Y
right@home
Y
Y
Y
–
Y
Triple B: The Triple B Pregnancy Cohort Study (Bumps, Babies and Beyond)
Y
Y
Y
–
Y
Victorian Adolescent Health Cohort Study (VAHCS)/Victorian Intergenerational Health
Cohort Study (VIHCS)
Y
Y
Y
–
Y
VicCHILD: Victorian Childhood Hearing Impairment Longitudinal Databank
Y
Y
–
–
Y
VITALITY: Primary prevention of infant food allergy: a randomized–controlled trial
of post-natal vitamin D supplementation
Y
Y
Y
Y
Y
Y = Yes.
Collation of metadata
To maximize discoverability of these participant data for researchers, the LifeCourse
platform collates standardized study metadata for presentation on a publicly accessible
website (https://lifecourse.melbournechildrens.com). Indexing rich metadata is critical
to making cohort data Findable, Accessible, Interoperable and Reusable (the FAIR framework
18
) and aligns to the principle of Open Materials whereby details of a study’s design
and measures are publicly accessible.
19
Study metadata are organized at several levels (Figure 2). At the highest level, description
of key design features, such as the year established and number of participants, is
provided in a standardized format. At a more detailed level, measures captured within
each wave of data collection are described according to a common terminology (Systematized
Nomenclature of Medicine; SNOMED
20
) and organized into content domains. SNOMED currently covers 80% of the concepts
captured across LifeCourse cohorts and terms have been systematically developed for
remaining gaps in areas such as education and childcare.
21
Using this standardized system of description provides consistency with international
standards and facilitates external comparisons of data availability.
Figure 2
Standardized presentation of study-level and measure-level metadata on the LifeCourse
website. Images taken with permission from https://lifecourse.melbournechildrens.com.
Prospective harmonization
Using identical measures and procedures across studies avoids the need to introduce
assumptions about the equivalence of different measures or item sets during data pooling.
However, this needs to be balanced with the potential consequences of overly prescriptive
approaches.
22
For example, many scales are not easily transferable across settings, such as from
the clinical to community contexts.
LifeCourse facilitates the use of a common set of well-validated measures during the
survey design phase where appropriate, such as through our measurement library (https://lifecourse.melbournechildrens.com/measurement-library/)
while recognizing the need for study-specific approaches in many instances. In the
COVID-19 context, for example, a number of cohorts collected aligned data from the
CoRonavIruS health and Impact Survey (CRISIS)
23
as well as specialized scales tailored to their own needs. This balance between common
and study-specific measures enables cohorts to continue building their specialized
research programmes while simultaneously facilitating cross-cohort research approaches
to address shared questions. Harmonized protocols for the collection and analysis
of biosamples have also proved advantageous, such as collaborative genotyping and
epigenotyping of participants across cohorts.
Data resource use
Each cohort has a vibrant individual programme of research aligning to their scientific
agenda and benefitting from nuanced, study-specific data. Beyond the significant contributions
of individual cohorts, a programme of research working across cohorts is increasingly
emerging that addresses a shared interest in pathways leading to mental health, cardiometabolic
health and immune-related conditions. The LifeCourse cohorts have collected particularly
rich data in these domains (Table 2), allowing cross-cohort investigations within
and at the intersections of these research streams, including in the COVID-19 context.
This work is facilitated by LifeCourse’s efforts to enable data discoverability and
access, promote prospective data harmonization and connect researchers across disciplinary
boundaries. Below we outline illustrative examples of research using cross-cohort
approaches in each of these key areas.
Both this cross-cohort research and that of individual cohorts are strengthened by
the ongoing partnership between LifeCourse and the Melbourne Children’s campus Clinical
Epidemiology and Biostatistics Unit (CEBU), which provides cohort researchers with
access to cutting-edge methodological approaches. The CEBU methodological hub specializes
in the development of novel methods and guidance in statistical areas that are key
for longitudinal cohort studies, such as causal inference,
11
as well as providing collaboration, open resources such as for analysis planning
24
and training workshops. This is particularly relevant when using cross-cohort approaches,
where new methodological challenges can arise.
Mental health
The complex origins of mental health and illness emerge in the earliest periods of
life and over two-thirds of core LifeCourse cohorts have tracked key exposures from
infancy (Table 1). This has enabled investigation of the replicability of effects
in the context of what are expected to be complex, multi-determined pathways to mental
health and illness over long time spans.
25
A particularly long temporal perspective is offered by two transgenerational cohorts
tracking offspring of the original index child (Australian Temperament Project Generation
3 and Victorian Intergenerational Health Cohort Study). Strongly aligned protocols
across these two studies have allowed intergenerational cycles of mental health to
be explored in pooled data analyses.
26
The availability of biosamples, such as co-ordinated extraction of genetic and epigenetic
data from LifeCourse cohorts with well-aligned, repeated assessments of social-emotional
development, is allowing investigation of the biological mechanisms that underpin
these developmental pathways. International collaborations are progressing cross-national
comparisons of intergenerational effects,
27
the influence of differing school policies
28
and the natural history of positive mental health and wellbeing.
29
Cardiometabolic health
Cardiometabolic disease as used herein refers to cardiovascular disease resulting
from metabolic syndrome and its risk factors obesity and diabetes, and remains the
leading cause of mortality worldwide. Following recent paradigm shifts, cardiometabolic
disease is now conceptualized as a chronic inflammatory condition that develops from
early life onwards, manifesting as progressive clinical disease predominantly in adulthood.
30
LifeCourse provides an opportunity to investigate the early exposures and pre-clinical
risk phenotypes for cardiometabolic disease, with in-depth phenotypic measures from
birth to adulthood. Almost all LifeCourse cohorts contain some data relevant to the
early origins of cardiometabolic health, such as (i) non-invasive assessments of pre-clinical
large arterial vascular phenotypes (e.g. blood pressure, arterial stiffness and intima-media
thickness, IMT); (ii) microvascular parameters; (iii) anthropometry and body composition;
and (iv) circulating biomarkers of metabolic health and inflammation. Work is underway
across LifeCourse and international cohorts to investigate how inflammation across
the life course predicts these cardiometabolic phenotypes.
Immune-related conditions
Immune dysregulation and inflammation are not only integral to common childhood conditions
such as infection and allergic diseases, but also increasingly recognized as key mechanisms
in the development of a range of adult non-communicable diseases, including mental
health and cardiometabolic disease.
31
Over half of the LifeCourse cohorts contain data relevant to immune health and these
data are being used to understand how early-life exposures can drive immune dysregulation.
For example, aligned data from the Barwon Infant Study (BIS) and the Longitudinal
Study of Australian Children Child Health CheckPoint (LSAC CheckPoint) has demonstrated
that children’s experiences of adversity relate to GlycA, an inflammatory biomarker,
in both mid and late childhood.
32
Allergy has also been a major focus of LifeCourse, which includes several internationally
renowned cohorts established to investigate these conditions. For example, data from
the HealthNuts and BIS cohorts have been used to compare allergy prevalence estimates
across regional and metropolitan areas,
33
whereas HealthNuts and LSAC CheckPoint have found inconsistent associations between
caesarean delivery and asthma, and a negligible association with eczema.
34
COVID-19
The need to capture the direct and indirect effects of the COVID-19 pandemic for children
and adolescents has provided further impetus for crossing traditional disciplinary
boundaries. Longitudinal studies established prior to the pandemic are optimally positioned
to show how COVID-19 may have impacted life-course trajectories.
35
The COVID-Wellbeing working group has been formed to map pre-pandemic risk and resilience
factors for mental health outcomes across the distinct populations of children and
young people captured by LifeCourse cohorts. Collection of these data in a number
of biomedically focused cohorts will allow examination of the interplay of social
and biological factors. Findings will be used to inform the targeting of prevention
and intervention efforts in the post-pandemic recovery period.
Strengths and weaknesses
Beyond the quality, scope and richness of the underlying cohorts themselves, strengths
of the LifeCourse initiative include the availability of richly described and structured
cohort metadata, a common approach to data access requests and alignment of key data
including for bioassays with many conducted in a single extraction on the same platform
(e.g. metabolomics). This provides efficiency, comparability and feasibility in the
use of these data, enhancing their value for promoting life-course health. This underlying
infrastructure is further enhanced by partnering with methodologists and providing
a range of other spaces fostering collaboration, driving the intellectual and human
capital needed to make best use of these data.
Nevertheless, there are still a range of areas for further development. Making the
process through which metadata are collated as simple and efficient as possible is
key to improving accuracy and reducing time lags in the presentation of new metadata,
such as in the COVID-19 context where many cohorts simultaneously pivoted to collecting
data with time-critical applications. Raising the quality and comprehensiveness of
the underpinning documentation in individual cohorts would further improve efficiency
of metadata collation, which otherwise becomes progressively harder to remediate for
long-running studies.
36
Work is currently underway to develop best-practice data management templates and
guides specific to the cohort context. The integration of required LifeCourse metadata
fields into these templates will significantly enhance the ongoing sustainability
of the platform.
Despite a central process for data access requests (outlined below), we do not yet
have an integrated process through to data transfer. This is undertaken by the custodians
of individual cohorts with varying processes and requirements aligning to their different
governance structures and participant consents. We continue to work towards addressing
ethics and governance barriers (e.g. promoting use of participant consents that allow
appropriate data reuse) as well as technical infrastructure to support FAIR data provision.
For example, the integrated data platform currently in development for the Generation
Victoria ‘mega-cohort’ has the potential to support other studies in future, with
enhanced features such as direct data browsing and a secure research environment for
analyses. The ongoing efforts of LifeCourse to promote data discoverability and accessibility
are critical to ensuing cohorts’ readiness to engage with such opportunities in future.
Finally, there are barriers to achieving these ambitions that are outside the immediate
control (but perhaps in the sphere of influence) of LifeCourse and other such platforms.
In moving towards Open Data, there must be mechanisms to acknowledge the teams responsible
for data generation and to value this as an academic contribution without which the
ensuing knowledge cannot accrue. The research community should be ambitious in addressing
this fundamental issue rather than trying to curtail the efficient and ethical reuse
of existing cohort data.
37
Undertaking the types of cross-cohort research enabled by the platform typically requires
more resourcing than single-cohort analyses, including in terms of biostatistical
expertise, and so funding structures may also require review to appropriately resource
this work and develop workforce capacity.
Data resource access
Community of practice
LifeCourse is designed to facilitate collaborations and engage new data users from
within and beyond the Melbourne Children’s Campus. LifeCourse hosts a range of meeting
places that provide space for new connections and collaborations to thrive (find out
more at https://lifecourse.melbournechildrens.com and contact lifecourse@mcri.edu.au
to join our mailing lists). Researchers not only benefit through synergistic research
collaborations but can also deepen their collective expertise by sharing knowledge
and experience about common issues.
Centralized data access requests
To reduce logistical barriers to data access, LifeCourse acts as a liaison connecting
data users and custodians. Applicants are invited to complete an initial enquiry through
a central gateway (https://lifecourse.melbournechildrens.com/data-access/), requiring
preliminary information on the team, primary research question and cohort/s of interest.
LifeCourse confirms the in-principle feasibility of the request with the relevant
cohort/s, after which an application is submitted with full details of the project
and data and/or samples required. To overcome variations in governance structures
across cohorts, cohort custodians retain decision-making responsibility and undertake
the transfer of data and/or samples. Applications are assessed by cohorts for criteria
such as (i) feasibility given the available data (e.g. quality issues with the data
requested); (ii) consistency with ethical requirements (e.g. limits of participant
consents); (iii) appropriateness for the purpose and strategic plans of the cohort
(e.g. redundancy with research already underway); and (iv) scientific quality.
Notes
The LifeCourse Cohort Investigators: Valerie Sung1–3; Emma Sciberras4; Sheena Reilly5;
John W Toumbourou4,6; Kirsten P Perrett1,2,7; Catherine Marraffa1,2,8; Angela Guzys1;
Jennifer J Koplin1,2; Stephanie J Brown2,9; Gehan Roberts1,2,3; Jon Quach1,10; Tim
J. Silk1,4; Avihu Boneh1,2; Delyse Hutchinson2,4,6,11; Evelyne Muggli1,2; Sharon Lewis2,12
1Murdoch Children’s Research Institute, Melbourne, Australia; 2Department of Paediatrics,
The University of Melbourne, Melbourne, Australia; 3Centre for Community Child Health,
Royal Children’s Hospital, Melbourne, Australia; 4Centre for Social and Early Emotional
Development, School of Psychology, Faculty of Health, Deakin University, Australia;
5Griffith University, Queensland, Australia; 6Centre for Adolescent Health, Murdoch
Children’s Research Institute, Melbourne, Australia; 7Department of Allergy and Immunology,
Royal Children’s Hospital, Melbourne, Australia; 8Department of Neurodevelopment and
Disability, Royal Children’s Hospital, Melbourne, Australia; 9Intergenerational Health,
Murdoch Children’s Research Institute, Melbourne, Australia; 10Melbourne Graduate
School of Education, The University of Melbourne, Melbourne, Australia; 11National
Drug and Alcohol Research Centre, Faculty of Medicine, University of New South Wales,
Sydney, Australia; 12Reproductive Epidemiology, Murdoch Children’s Research Institute,
Melbourne, Australia.
Ethics approval
Ethics approvals for the studies described are managed by each individual study team,
across a range of human research ethics committees.
Author contributions
M.O’C. undertook primary drafting for most of the manuscript. M.M.-B. drafted and
provided oversight for statistical/methodological components of the manuscript. C.O.
and D.B. drafted specific sections of the manuscript and provided senior supervision
for this work. All authors reviewed the manuscript and provided important intellectual
content. The LifeCourse Cohort Investigators ensured accurate description of their
cohort.
Supplementary data
Supplementary data are available at IJE online.
Funding
The Melbourne Children’s LifeCourse platform is funded by the Royal Children’s Hospital
Foundation grant #2018–984, which includes support for M.O’C. M.M.-B. is the recipient
of an Australian Research Council Discovery Early Career Researcher Award (project
number DE190101326) funded by the Australian Government. S.G. is supported by Australian
National Health and Medical Research Council (NHMRC) Practitioner Fellowship (1155290).
C.O. is supported by an NHMRC Investigator Grant (APP1175086). D.B. is supported by
an NHMRC Investigator Grant (1175744). M.W. is supported by an NHMRC Principal Research
Fellowship (1160906). Research at the Murdoch Children’s Research Institute is supported
by the Victorian Government’s Operational Infrastructure Program. The views reported
in this paper are those of the authors only.
Supplementary Material
dyac086_Supplementary_Data
Click here for additional data file.