LifeLines Scientific Report

LifeLines for Researchers
A unique resource of data, samples and expertise
www.lifelines.net
www.lifelines.nl
Hanneke Jansen
MD/PhD, investigated the level of HbA1c in the blood of
2,921 non-diabetic adults.
Experts suggested the use of HbA1c levels to diagnose new-onset
diabetes. LifeLines data on Body Mass Index, waist circumference,
fasting plasma glucose, erythrocyte indices, current smoking and alcohol
use, and genome-wide genetic data revealed that high HbA1c levels are
determined by other factors besides preceding glucose levels. The use of
HbA1c levels may therefore not be suitable to diagnose diabetes.
“My experience with LifeLines data was very
good: the data was clear and ready-to-use. When I had
questions about the data, I got a quick answer.”
Bart Klijs
Health scientist, studies depression, highly prevalent in
modern western societies.
We believe that people evaluate themselves in relation to others. We
disentangled how socio-economic position –compared to the average position
of people living in the same neighbourhood- is related to depression. Our
research is embedded in a larger programme on the societal aspects of healthy
ageing. Our LifeLines data are enriched with information on neighbourhood
level income from Statistics Netherlands.
“Given its large sample size, the geographical spread of
participants and the diagnostic instrument used to establish
depression, the LifeLines dataset is uniquely suited for
the project.”
Content
Contact
UMCG
LifeLines
P.O. Box 30.001
9700 Groningen
Email: [email protected]
Website: lifelines.net
© LifeLines 2013
Colofon
Text: Marije van Beilen Psychologie &
Wetenschapscommunicatie
(Marije van Beilen & Corinne van Beilen)
Design and infographics:
Kuenst.nl (Nynke Kuipers &
Meinte Strikwerda)
Photo’s: Henk Veenstra,
Jeroen van Kooten and others
Prephase 3
LifeLines 4
LifeLines for Researchers 6
Cohort Study and Biobank
8
Interview Pim van der Harst 10
Access to LifeLines
12
LifeLines Extensive Networks 14
Interview Judith Rosmalen 16
LifeLines Scientific Organization 18
LifeLines Data Collection
20
1
Steef Sinkeler
MD, improves the estimations of renal
function for scientific purposes.
The number of patients at risk for renal disease
is growing rapidly due to a higher prevalence
of diabetes and cardiovascular problems. We
need reliable measures to identify patients-atrisk in an early stage. The accuracy of the widely
used measurement to assess renal functioning is
questionable. A method –based on urine creatinine
excretion- is more accurate, provided urine is
collected adequately.
“With the LifeLines cohort we
developed a sophisticated formula
to assess creatinine excretion that allows
a more accurate estimation of renal
function world-wide.”
2
Prephase
This first scientific report marks the start of the next phase of LifeLines. After more than
five years of data collection, these data are now ready to be explored by researchers. Not
just data, but a whole infrastructure is available for investigators in The Netherlands and
abroad, from both public and private institutions. Apart from the large scale high quality
data in many domains, LifeLines provides state of the art high performance computer
power, a team of methodological experts, an (inter)national network of biobank
researchers, and later this year a fully automated biorepository to retrieve a selection
from the millions of stored biosamples overnight.
The examinations of the LifeLines cohort continue and there are ample opportunities
for researchers to add their own assessment in the entire 165,000 participants or in
a subgroup they select. From assays in fresh or stored samples to additional tests or
questionnaires. Again, experts are available to help from methodological issues to
valorization and IP solutions.
The scientific opportunities of LifeLines are described in this report, more details are
available on www.lifelines.net. We are looking forward to welcome researchers to
the LifeLines community. Please submit a proposal to use the data or add to the data
collection.
We are proud to the opportunities of LifeLines to contribute to improve knowledge on
Healthy Ageing, and are eager to share these with researchers world-wide.
On behalf of the LifeLines scientific crew,
Ronald Stolk
Professor of Clinical Epidemiology
Chief Scientific Officer LifeLines
3
LifeLines is one of the world’s
in the understanding of the
largest population-based
etiology of disease.
studies and offers a unique
The developed infrastructure
data and biomaterial resource
enables to perform both
to researchers world-wide. Its
large-scale and detailed
cohort study and biobank link
epidemiological studies
information on environmental
to gene-environmental
exposures, (epi)genetics,
factors in a broad range of
nutritional, psychological and
multifactorial diseases. Only
social factors, as well as data on
this multidimensional and
health care use to cover societal
multidisciplinary approach will
impact. It forms a pivotal base
deliver the depth of insight
for important breakthroughs
required to understand the
in the screening, prevention,
origins and course of (chronic)
diagnosis, and treatment of
diseases.
(chronic) diseases as well as
LifeLines
LifeLines’ broad scope,
large study population
and long follow-up make
it one of the world’s most
valuable multidimensional
cohort studies and
biobanks
4
Large sample: 165,000 individuals (expected in December 2013), covering
three generations
Scope: (epi)genetic, biomedical, nutritional, psychological, social
and environmental factors in relation to healthy ageing,
disease development and general well-being
Follow-up: for the duration of participant’s life; collection of detailed
follow-up data and biomaterial with extensive standardized
measurements
Started: 2007
Interactive Data Exchange at Multiple Measurement Levels
dimensions
expanding data b
ank
environment
social
psychologic
nutrition/ lifestyle
biomedic
(epi)genetic
addon
stud
ies
colle
cting
data
ge
d
nka
ata li
5
LifeLines for Researchers
The research infrastructure, as
well as data and biomaterials
collected by LifeLines can be
utilized by a great number of
researchers from a variety of
clinical, biomedical, genetic,
psychological, environmental
and sociological disciplines.
LifeLines was established as an
open research infrastructure
with ample opportunities
to include additional
measurements to the protocol.
Access to LifeLines benefits
clinical as well as fundamental
research purposes, and is suited
to the individual researcher
As LifeLines’ cohort study and biobank
has no pre-determined research
objective, it caters to a wide range of
research disciplines
6
as well as large international
research programmes.
Researchers from various
backgrounds are currently
working with the LifeLines data.
LifeLines offers
researchers the unique
opportunity to add
questionnaire and
measurements to the
LifeLines protocol to
answer their research
question
Facilitation and Research
Infrastructure
Researchers gain access to a research
infrastructure that opens up a broad range
of opportunities, comprising:
An elaborated, longitudinal cohort and
biobank with biomaterial
A collaborative network of other
researchers working with LifeLines data,
and other biobanks
A center of expertise on biobanking,
ensuring the best possible service and
quality of data and biomaterials, as well
as support in statistical analyses
Researchers’ Own
Additions to Data
Collection
In addition to accessing the collected
data and biomaterials, researchers can
add data to the LifeLines research
infrastructure for their own specific
research question. LifeLines can send
an additional questionnaire or perform
additional measurement on a specific
topic of interest of the researcher to (a
subgroup of) the LifeLines population.
Type of requests
Sample request
Linkage external data
Additional data collection
Infrastructure project
Data request
13%
4%
6%
10%
67%
Examples of implemented additional research:
A
dditional questionnaire for subgroup of the population: questionnaire
on burden of informal care givers
Additional measurements/ samples: detailed genomics data
Linking of external data sources: geocoding, neighbourhood
characteristics, air pollution
Linking of patient-based biobank with LifeLines biobank
Direct Available Data
Also, external data sources can be linked
to the LifeLines data. In short, LifeLines’
infrastructure, cohort, knowledge and
know-how is at the disposal of researchers
to answer their specific research
questions. This saves researchers valuable
time, while being ensured of high quality,
ready-to-use data. In this role, LifeLines
facilitates the creation of research
communities by matching researchers
who are working with similar data and
have joint research interests.
All LifeLines data is monitored on
inconsistencies and can be accessed
through a remote access procedure, which
runs on a high performance computer
cluster. Researchers currently have access
to ready-to-use complete baseline data
of 95,000 participants. Recurrent data
releases (more participants and followup data) will become available every
six months. When researchers request
collection of additional data, the data
release will take more time.
7
LifeLines has a unique
three generation design
Cohort Study and Biobank
Three Generations: LifeLines Cohort Dimensions
Index persons: invited to participate through
their general practitioner
Probands invite their family members (parents,
partner, parents-in-law and children) to take
part
Index
persons
(25–50
years)
Father
A-SELECT:
45,000
CHILDREN: 35,000
This results in a three-generation study
Based on the age of the participant, they are included in the children’s protocol (0–18 years),
the adult protocol (18–65 years) or the elderly
protocol (> 65 years)
Mother
For children five specific sub-protocols are
developed, corresponding with the different
developmental stages
PARENTS ALIVE: 55,000
Child
Child
Child
TOTAL NUMBER OF
PARTICIPANTS: 165,000
Partner’s
Father
Partner’s
Mother
Based on estimated numbers
8
Partner
PARTNER: 30,000
Men
56,802
Women
79,812
Total
136,614
Number of participants as per 22 May 2013
5 years
1,5 years
1,5 years
Baseline visit
& follow-up visits
5 years
1,5 years
1,5 years
1,5 years
1,5 years
1,5 years
Follow-up
data collection
Follow-up by
record linkage
The homogenous composition of the
population in the North of The Netherlands is highly suitable for observational
follow-up studies, as people in the Dutch
Northern provinces tend to keep living
in the same area for many generations.
LifeLines covers three generations and has
a high response rate. This design enables
the prospective investigation of risk
factors, which is crucial in the study of
(health) behavioural and environmental
and other time-varying exposures, as
well as interactions between genetic and
environmental risk factors.
Key benefits of this
three-generation design:
Vast statistical advantages: multiple-level information, separation of
non-genetic and genetic familial transmission, direct haplotype assessment,
and increased power and precision
Unique possibilities to study social
characteristics: socioeconomic mobility, partner preferences, and betweengeneration similarities
Data Collection and
Sample Storage
All participants receive a number of
questionnaires and a medical examination.
Fasting blood samples and 24-hour urine
are collected for long term storage and
to perform laboratory measurements.
The participants are followed for at least
thirty years and are invited every five
years for a medical examination at a
local LifeLines research facility. In the
years in-between the participants receive
follow-up questionnaires. Follow-up on
morbidity and mortality will also be based
on general practitioners, hospital and
pharmacy records.
Conditioned transport of blood and urine
samples towards the highly automated
LifeLines laboratory guarantees complete
traceability. Samples are analyzed and
stored at -80 °C on the same day of collection. Uniquely 2D barcoded labware are
used for storage.
‘LifeStore’
The storage facility of LifeLines, ‘LifeStore’ is currently under construction in
Groningen, The Netherlands, and will be
fully operational beginning 2014. This is
a completely automated sample storage
with a capacity of 8+ million aliquots
at -80 °C which will do fully automated
overnight sample retrieval. Storage of
blood and urine samples at high quality
standards at different time points (every 5
year) facilitates the researchers to go back
in time to investigate traces of diseases
and the effects different of treatments
in the carefully processed and registered
biomaterials.
Timeline
Baseline visit: Participants visit
LifeLines Research Site
Measurements
Sample collection (blood and
24-hour urine)
Questionnaires
Second visit fasting
At home: 24h urine collection
and questionnaires
Follow-up data collection
(every 1,5 years)
Questionnaires
Follow-up
New questions (requested by
researchers)
Food frequency questionnaire
Follow-up by record linkage
(continuously)
Link with external data
Hospitals records
Follow-up visit
(every 5 years)
Measurements
ECG, anthropometry, lung function, blood pressure, cognition
Sample collection (fasting blood,
24h urine, scalp hair and faeces)
Questionnaires
9
PHOTO: JEROEN VAN KOOTEN
Interview
Pim van der Harst
“LifeLines makes you an
attractive partner for top
research groups all over
the world”
Our genes are at the heart of all bodily functions and present
in each of our cells. Variations in genes determine our health
throughout our lives. The heart function itself is influenced by a
great number of genes and variations of those genes.
Genetic and environmental factors constantly interact: they
jointly affect the heart and other bodily functions. The integration
of genetic and environmental factors form one of the main themes
in the LifeLines Healthy Ageing research.
10
You investigated the relationship between
genetic variation and heart function. How
did you make use of the LifeLines data?
“In a proportion of LifeLines participants
we have genotype data available covering
the entire human genome. This allows us
to perform GWAS studies.” GWAS –short
for Genome Wide Association Studyconcerns the investigation of common
genetic variants in different individuals to
link specific genetic information to specific
human traits. “Genetics research obviously
require large numbers: with more than 2,5
million variations on the genome we need
to deal with the multiple comparisons
problem. We investigated the variations
in the human genome in a very large
sample of 120,000 participants. For this,
we combined the LifeLines data with data
from other large biobanks. This way, we
found a total of 61 regions in the DNA
associated with heart function.”
understand the patients’ condition, as they
enter the clinic. They are not an isolated
set of genes, after all, every patient has his
own unique environmental history and
health behavior. If we know which genes
are involved and which environmental factors contribute, we will be able to increase
our understanding which might help us
diagnose heart disease in an earlier phase
and improve prevention of illness.”
Heart function is related to 61 different
regions in the DNA? That is much more
complex than I would have imagined.
“And we only looked for the regions
related to particular aspects of the
electrocardiogram (ECG), there are many
more to find if you broaden our view. We
are interested to isolate genes that are
also related to the development of heart
failure and therefore narrowed our view
to particular aspects of the ECG. But it is
indeed more complex as heart function
is not an isolated bodily function
determining heart failure symptoms or
healthy ageing in general: it is related
to, for example, kidney and pulmonary
function, the number of red blood cells or
social and psychological factors. LifeLines data offered us the opportunity to
investigate the associations between all
these different factors. As a cardiologist,
it is important to learn about the combination of risk factors, that all contribute
in some way to the development of heart
disease. After all, many patients come in
with multiple illnesses, comorbidity is a
significant problem. We need to be able to
What did you find, specifically?
“Well, first of all, we discovered new sets
of candidate genes that influence heart
function. Some of these genes were never
related to cardiac disease before. I find it
very exciting to identify new genes that
potentially regulate the size of heart cells
and the way these cells behave and put
someone at risk to develop heart disease.
Also these first findings might be helpful
to identify new potential targets of therapy to which we can design new medicine.”
That paper was published in Nature, quite
a success! I noticed that -at 34 years oldyou finished your training as a cardiologist
last year. Despite the large amount of time
consumed by a medical education, your
h-index has already reached 24. In addition to the scientific results we discussed;
what did using LifeLines data bring your
career, as a scientist?
“Most importantly, having access to large
data-bases gives a scientist international
stature. In my field of interest, complex
genetics, we need very large sample sizes.
Currently, I collaborate with more than
24 international groups. Together, we
can answer scientific questions requiring
samples of 100.000 or more. So, being
able to contribute LifeLines data made
me an attractive scientific partner for top
research groups all over the world. This
has been a huge stimulant for my personal
career as a scientist: collaboration with a
lot of groups is challenging but it is also
highly inspiring. An efficient organization
can result in more publications, we were
able to generate high impact results so
they are cited a lot.”
Pim van der Harst (1977) started his career
as a researcher during his cardiology
training, after finishing medical school cum
laude. He is now an Associate Professor in
Cardiology specializing in interventional cardiology and complex genetic research at the
University Medical Center Groningen. He
received several prestigious grants including
LifeLines data in his research proposals, and
was awarded scientific prizes for excellence
both within The Netherlands and abroad.
“Co-morbidity is a
significant problem in
heart disease”
11
Access to
LifeLines
Application Process
Researchers who are interested in utilizing
LifeLines data, biomaterial or the infrastructure may apply for access by submitting a short proposal to the LifeLines
Research Office describing their research
aim and request.
Research Proposal
The core of the LifeLines
project consists of
dedicated data collection
and biological sample
storage, including genetic
samples
Any researcher, including PhD students
and post-doctorate researchers, can apply
for data or biomaterial, when they are
connected to a department or institution
with the competence to carry out the proposed research project to term. LifeLines
also welcomes other public and private
partners. The proposal must fit within the
concept of Healthy Ageing.
LifeLines Scientific Board reviews all
proposals to ensure scientific quality, to
avoid duplicates of running proposals and
to confirm it fits into the Healthy Ageing
theme. A feasibility check is performed on
application for the LifeLines sample and
infrastructure.
RESEARCHER
LIFELINES
Research Proposal
Scientific review by
Scientific Board
Internal review
by LifeLines
Sample/data release
12
When a proposal is approved, the researcher will receive a contract and the
exclusive right to use the data for a pre-determined period of time. Data is released
within a remote system (LifeLines workspace) running on a high performance
computer cluster. In case the researcher
asked for additional data collection within
LifeLines, a member of the LifeLines
Research Office will be dedicated to the
project and work in close collaboration
with the researcher.
Data and biomaterial can be used for
scientific research only.
Scientific results become publically available. Applications are published on the
LifeLines website in consultation with the
researcher and publications with LifeLines
data or biomaterials are listed.
LifeLines invites researchers who are
investigating data or biomaterial to participate in the LifeLines research community to find additional information and
documentation. More importantly, the
research community stimulates researchers to share experiences and ideas and
serves as a platform for discussion.
For full guidelines for access to the
described services, please visit
www.lifelines.net
Costs
All data and materials for scientific research are provided on a fee-for-service
base. LifeLines recommends that researchers request a quotation of estimated costs
before applying for research grants and
subsidies.
Bennard Doornbos
MD/PhD, studies the impact of low
grade inflammation (hsCRP).
Low grade inflammation is related to general
health behavior, and modern diseases such as
cardiovascular disease, and to the speed of ageing
in general. We found that it is also associated
with the prevalence of depression. We also found
that Lifestyle, and more particular the Body Mass
Index of depressed patients explains a significant
part of this relationship. With the follow-up data
we will investigate speed of ageing in depression.
“The LifeLines data structure made
it possible to investigate comorbidity at different levels of
disease in individual patients.”
13
Through LifeLines leading
role in biobank networks,
researchers will be able
to use pooled data from
different cohort and
biobank studies and
gain access to the large
sample sizes needed to
investigate questions in
multifactorial diseases
LifeLines Extensive Networks
Biobank Networks
www.bioshare.eu
www.bbmri.nl
www.parelsnoer.org
www.bbmri.eu
www.p3g.org
www.biomedbridges.eu
www.esbb.org
Public-Private Partnerships
www.tipharma.com
www.tifn.nl
www.healthy-ageing.nl
14
As a center of expertise in biobanking, LifeLines takes part in a
number of strategic alliances, national and international biobank
networks and research collaborations. Through these networks
LifeLines established itself as one of the world leaders in the
science of biobanking, as well as contribute to the advancement
of public-private partnerships.
Biobanking and
Biomolecular Resources
Research Infrastructure
Matching data collection will be achieved
through the development of harmonization and standardization tools, implementation of these tools and demonstration
of their applicability. LifeLines actively
participates in BBMRI-NL, a collaboration
of all population-based and diseaseoriented Dutch Biobanks, in projects
devoted to biomarkers, gene expression,
harmonization and standardization, and
nutrition. The future aim is to integrate
BBMRI-NL with the Parelsnoer Institute and LifeLines, to create one, common, coherent biobank with high-quality
clinical and molecular data and optimized
accessibility. This Dutch Biobank Hub
will become part of BBMRI-ERIC.
Public-Private Partnerships
Active large European population studies:
CHRIS/MICRA (Bolzano, Italy), Estonian Biobank
(Tartu, Estonia), FINRISK (Helsinki, Finland),
KORA (Munchen, Germany), HUNT (Trondheim,
Norway), LifeGene (Stockholm, Sweden), NCDR
(Leicester, UK), Prevend (Groningen, Netherlands), SHIP (Greifswald, Germany), UKbiobank
(Oxford, UK).
Biobank Networks
LifeLines is an active partner in P3G
(world-wide), the European Research
Infrastructure Consortium BBMRI-ERIC,
and takes a frontline position in BioShare:
a consortium of leading large-scale
population biobanks and international
researchers from all domains of biobanking science. With its expertise in largescale bioinformatics solutions, LifeLines
is active in several European biomedical
sciences research-IT infrastructures, joined
in BioMedBridges. Finally, as the largest
sample collection in the Netherlands,
LifeLines is an important member of the
European society for the collection and
storage of biological materials ESBB.
As a partner in TI-Pharma’s aim to
improve the development of socially
valuable medicine, LifeLines participates in
the Mondriaan project in which data from
existing databases and registries in The
Netherlands will be pooled for statistical analyses. Also, LifeLines has joined
TI- Food and Nutrition with specific
projects related to nutrition and multifactorial diseases. Additionally, within the
Netherlands Consortium for Healthy
Ageing (NCHA) LifeLines focuses on
(epi)genomics in age-related diseases.
15
Interview
Judith Rosmalen
“We need data including information at different
levels: from genetic to environmental and
everything in between”
Crying: did you ever wonder why people think you may be sad or
angry, when your eyes are making the well-known wet salty drops
of water? Probably not. In some somatic symptoms, it is perfectly
clear that mind and body interact, but in others this interaction
is under debate. These so-called functional somatic symptoms
are a challenge for all medical professions. How a large data-base
such as LifeLines can shed different light on these mysterious
symptoms.
16
You used the data that LifeLines collected
about functional somatic symptoms. What
are they?
“Functional somatic symptoms are those
somatic symptoms that cannot be sufficiently explained by measurable physical
abnormalities. For example, we looked
at syndromes such as Chronic Fatigue
Syndrome, Irritable Bowel Syndrome and
Fibromyalgia. This type of symptoms is
believed to be the result of psychological
distress. We do indeed find higher stress
levels in patients with functional somatic
PHOTO: HENK VEENSTRA
symptoms but we don’t know what was
the cause and what was the effect. Do
patients become more distressed as the
result of having an unexplained condition
and the possible misunderstanding of the
medical practitioner, or is pre-existing psychological stress influencing the development of the symptoms? As usual, the truth
lies somewhere in between. We’d like to
find out where.”
You need large numbers to be able to
investigate such complex and interacting
issues?
“Indeed. LifeLines enabled us to perform
a study including three types of Functional
Syndromes, including 94,516 participants.
The large number of LifeLines participants
is obviously an attractive aspect of using
LifeLines data. We worked at another
interesting and longstanding medical
debate: Previous work suggested that the
medical profession should regard disorders, such as Chronic Fatigue Syndrome,
Irritable Bowel Syndrome and Fibromyalgia, as part of the same syndrome. By
some professionals they are seen as a heterogenic group of patients: some patients
may emphasize muscle aches and others
fatigue, but all with a similar psychological
etiology. The large patient sample showed
us that the truth is more complex.”
Your data did not confirm this ‘one size
fits all’ image of patients with functional
somatic disorders?
“The data taught us that the number of
participants with all three syndromes
is over 33 times higher than would be
“With the large numbers,
we can investigate the
more subtle differences
between individuals”
expected by chance. This suggests that
the three syndromes do share risk factors.
On the other hand, patients also show important differences. For example, although
all syndromes affect woman more often
than men, this is much more the case in
fibromyalgia compared to Chronic Fatigue
Syndrome. Also, the different syndromes
are associated with different types of
somatic and psychological complaints.”
What are the implications? Should we
treat these patients differently?
“Well, we plan to use the LL follow-up
data to investigate what causes the
overlap, and the differences. That’s what’s
interesting about the LifeLines data: a
broad and longitudinal data base offers the
opportunity to investigate the symptoms
at multiple etiological levels. For example, we can identify (shared) risk factors
at genetic, hormonal or other somatic
levels. We can also look at social or heath
care factors that may contribute to the
chance that functional somatic symptoms
become chronic. And, the consequences,
what does it mean to have these symptoms, in terms of psychological well-being,
socio-economic status or the ability to
work, are important to understand. If
we understand the specific issues that
influence these symptoms, we can tailor
medical care to the individual patient.”
How was the process to gain access to
the LifeLines data? Did you need to meet
certain scientific standards?
“LifeLines applies broad and flexible criteria; all researchers can apply for a publication proposal. The key to a LifeLines publication is solid scientific argumentation,
similar to grant proposals. We explained
the scientific importance of including
the questions about the prevalence of
the functional somatic syndromes that
we are now preparing a publication on.
Researchers can either contact LifeLines
with a proposal to include additional data
collection, or they can take a look at the
existing data-base. I recommend young
researchers to look at the additional value
of existing LifeLines data and to include
its fee in their grant proposals. That is the
moment when the fee for a publication
using LifeLines data can easily be incorporated within the grant proposal.”
Judith Rosmalen (1971) studied both
Medical Biology and Psychology. She is now
a Professor in Life course Epidemiology of
affective disorders, specialized in Somatization Disorders working at the Interdisciplinary Center Psychopathology and Emotion
regulation at the University Medical Center
Groningen. She is the president of EURASMUS (European Research Association for
Somatoform and Medically Unexplained
Symptoms), a European research network
aiming to study the etiology of somatization.
17
LifeLines Scientific
Organization
LifeLines takes a frontline
position in the science of
biobanking
Members Scientific Board
Prof P. (Paul) de Bakker,
Genetics - UMCU
Dr U. (Ute) Bültmann,
Social Medicine - UMCG
Dr J.M. (Marianne) Geleijnse,
Human Nutrition - WUR
Dr P. (Pim) v.d. Harst,
Cardiology - UMCG
Prof G.H. (Gerard) Koppelman,
Pediatric Pulmonology - UMCG
Prof J.G.M. (Judith) Rosmalen,
Psychiatry - UMCG
Dr E.F.C. (Liesbeth) van Rossum,
Endocrinology - EMC
Prof H. (Hauke) Smidt,
Microbiology - WUR
Dr M.A. (Morris) Swertz,
Bioinformatics - UMCG
Chief Scientific Officer
(Chair of the Scientific Board):
Prof R.P. (Ronald) Stolk,
Epidemiology - UMCG
Coordinator Research Office
(Secretary of the Scientific Board):
Dr S. (Salome) Scholtens,
Epidemiology - UMCG
18
Monitoring and Security
LifeLines is permanently aiming to improve biobanking worldwide by researching its own data and establishing professional guidelines, policies and protocols
for large study populations. As such it
takes a leading position in many international collaborative networks. LifeLines
has developed expertise in ethics and
privacy rules, the organization of collecting
and storing large quantities of biomaterials
and data and the guaranteed quality of the
data warehouse. LifeLines upholds high
quality standards and expects ISO certification next year.
The LifeLines scientific progress and
anchoring are monitored and secured by:
Scientific Board The national Scientific Board consists
of Principle Investigators who have the
responsibility:
to secure the scientific quality and utility
of the collected data
to review submitted research proposals
for use of LifeLines data
to build and facilitate interdisciplinary
collaborations
to form (inter)national research networks for LifeLines
to apply for research grants and other
funding
LifeLines Research
Office
The Research Office is the researchers’
gateway to the LifeLines data and the
main point of contact throughout the
entire process of application, analyses,
publication and follow-up. Applications
are processed by the Research Office
and monitored on release, additional
data requests, and publications. When
additional data is requested, the Research
Office takes care of its implementation
in the LifeLines infrastructure or linking
to external data sources. As its staff is
very familiar with the LifeLines data, the
Research Office offers advice on the use of
the data and statistical analyses, or refer to
other experts in a specific research field or
methodology. Additionally, the Research
Office guards and supports participation
in (inter)national research collaborations
and biobanking networks and concomitant
enrichment of the LifeLines data collection
and economic value creation. LifeLines
Research Office works in close collaboration with the Chief Scientific Officer and
the Scientific Board.
The LifeLines Research
Office is the gateway to all
LifeLines data
Funding Partners
The LifeLines Cohort Study is
supported by:
The Netherlands Organization of
Scientific Research NWO (grant
175.010.2007.006)
The Economic Structure Enhancing
Fund (FES) of the Dutch government,
The Ministry of Economic Affairs
The Ministry of Education, Culture and
Science
The Ministry for Health, Welfare and
Sports
The Northern Netherlands Collaboration of Provinces (SNN)
The Province of Groningen
The City of Groningen
The University Medical Center
Groningen
The University of Groningen
Dutch Kidney Foundation and Dutch
Diabetes Research Foundation.
Ilja Nolte
Genetic epidemiologist, worked on a genetic association
study in individuals with an extreme high or low Body
Mass Index (BMI).
We used LifeLines data in a genome-wide association study to test what
genes are associated with extremes of BMI. We concluded that the
same genes are involved in variations of normal and extreme BMI, but
their effects on extreme BMI are larger. Additionally, we estimated that
at maximum around 15% of extreme BMI can be explained by common
genetic variants.
“The amount of LifeLines data was practical to work
with the large computer clusters and automated dataanalyses.”
Funding for Global Harmonisation and
standardisation of data collection and for
participation in Biobank Research projects
is provided by the European Committee
via Framework Programme 7.
19
LifeLines Data Collection
Laboratory assessment
Measurements:
Anthropometry
Blood pressure
Pulmonary function tests
12-lead electrocardiogram (ECG)
Ruffs Figure Fluency Test (RFFT): test
of cognitive function
MINI: neuropsychiatric interview
Measurement of skin autofluorescence with a non-invasive Advanced
Glycation Endproducts (AGE)-reader
MMSE (minimal mental state examination) Elderly (65+)
Biomaterial
collection:
EDTA
Citrate
Coagulation
Gel Coalgulation
24H Urine
24H Urine + additive
EMS Urine
EMS Urine + additive
Buffycoat
Fasting venipuncture
24 h urine
First morning urine (EMS)
Questionnaires:
Demographics
Family composition
Work and educational level
Health & History of disease
Birth and development
Lifestyle and diet
Day time spending
Living environment
Quality of life
Health perception
Personality
Stress
Social support
20
Linkage:
GP Health record
Hospital records
Environmental data
Blood/urine:
Blood
Leuco
Ery
Hb
Ht
Thrombo
Neutr gran
Lympho
Mono
Eos gran
Basoph gran
HbA1c
Glucose
Sodium
Potassium
Ureum
Creatinine
eGFR
Urinic acid
Alk.Phos.
ASAT
ALAT
Calcium
Phosphate
Albumine
Triglyceride
Cholesterol
HDL-Chol
LDL-Chol
gamma-GT
FT3
FT4
TSH
hsCRP
Apolipo A1
Apolipo B100
Urine
Creatinine
Albumin