The Marshfield Clinic Personalized Medicine Research Project: 2008 scientific update and lessons...

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The Marshfield Clinic Personalized Medicine Research Project: 2008 scientific update and lessons learned in the first 6 years
Catherine A McCarty1†, Peggy Peissig2, Michael D Caldwell3 & Russell A Wilke4,5,6
†Author for correspondence1Center for Human Genetics, Marshfield Clinic Research Foundation, 1000 N Oak Avenue (ML1), Marshfield, WI 54449, USATel.: +1 715 389 3120;Fax: +1 715 389 4950;E-mail: [email protected] Informatics Research Center, Marshfield Clinic Research Foundation, 1000 N Oak Avenue (ML1), Marshfield, WI 54449, USA3Department of Surgery, Marshfield Clinic, 1000 N Oak Avenue (ML1), Marshfield, WI 54449, USA4Department of Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee,WI, USA5Department of Pharmacology and Toxicology, Medical College of Wisconsin, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee,WI, USA6Human and Molecular Genetics Center, Medical College of Wisconsin, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee,WI, USA

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Keywords: biobank, genetic epidemiology, methods, pharmacogenetics

10.2217/17410541.5.5.529 © 2

The Marshfield Clinic Personalized Medicine Research Project is the largest population-based biobank in the USA, with the ability to recontact subjects to obtain additional information to facilitate gene–environment studies. Nearly 20,000 adults have enrolled in the Personalized Medicine Research Project since 2001, after providing active written consent to access their Marshfield Clinic medical records to define phenotype and providing blood samples from which DNA, plasma and serum samples were stored. Numerous studies are underway in the area of pharmacogenetics and genetic epidemiology. In addition to the scientific discoveries being made, much has been learned regarding biobanking and the management of large amounts of data being generated. The purpose of this paper is to share the advice provided by the external Scientific Advisory Board and the scientific lessons learned along the way to build this research infrastructure and facilitate its use.

The Marshfield Clinic Personalized MedicineResearch Project (PMRP) was launched, alongwith other international biobanking efforts, in2002 [1]. This was followed by a Grand Chal-lenge issued in 2003 by Francis Collins and hiscolleagues from the National Human GenomeResearch Institute (MD, USA) to ‘developrobust strategies for identifying the genetic con-tributions to disease and drug response’ [2]. Inthis visionary paper, Collins et al. mentionedthe PMRP and two other large biobanks as lon-gitudinal population-based cohort studies thatcould help to address this Grand Challenge.

The ultimate goal of the PMRP is totranslate genetic data into specific knowledgeabout disease that is clinically relevant and willenhance patient care, with the short-term goalof establishing a database to allow research ingenetic epidemiology, pharmacogenetics andpopulation genetics. The PMRP is a biobankwith DNA, plasma and serum samples andaccess to the Marshfield Clinic medical recordsof nearly 20,000 actively consented adults aged18 years and older. Details about the studymethodology have been published previously [3].The purpose of the current review is to providea scientific update on the PMRP after 6 years ofenrollment, to provide information regardingprojects currently using the PMRP database,and to survey some of the lessons learnedduring the establishment of this biobank forstudies involving genetic epidemiologyand pharmacogenetics.

Scientific Advisory BoardA tremendous amount of effort was invested inthe preparation of the PMRP biobank, longbefore its activation in 2002. The details of ourefforts have been presented previously withinPersonalized Medicine, within the specific con-text of discussing infrastructure development(Scientific Advisory Board [SAB], CommunityAdvisory Group, and the Ethics and SecurityAdvisory Board) [3]. The SAB met twice priorto the launch of the PMRP in September2002, and once again 15 months after enroll-ment had commenced. Tables 1–3 summarizethe recommendations made by the SAB attheir three meetings and the actions taken.Funding to support the SAB ran out before thecohort was large enough to undertake studiesusing the biobank.

Oversight committeePartly in response to the advice of the SAB that acommittee be formed to review and approveapplications to use the biobank, Tissue AccessGuidelines and an Oversight Committee werewritten and formed. The Tissue Access Guide-lines are available on the PMRP website [101]. Inbrief, in addition to Marshfield Clinic Institu-tional Review Board approval, scientific meritand approval by the Oversight Committee isrequired for the release of samples from thebiobank. Where external scientific merit has notbeen approved through a traditional peer-reviewmechanism, such as the NIH for funding, the

008 Future Medicine Ltd ISSN 1741-0541 Personalized Medicine (2008) 5(5), 529–541 529

SPECIAL REPORT – McCarty, Peissig, Caldwell & Wilke

530

Table 1. Recommenactions taken.

Recommendation

Collect the DNA as plan

Include a control popula

Limit yourself to a smallperhaps two to three

Create a process for peothat include the core idedata, how many subjectphenotyping will be und

Consider the warfarin pproof-of-concept study very quickly and demonsufficient resources to th

Identify external collabo

Consider allowing de-idoff site for genotyping

PMRP: Personalized Medic

Research Committee at the Marshfield Clinicwill review research proposals. The compositionof the Oversight Committee is as follows:

• Director of Medical Research, Chair ofOversight Committee

• Principal Investigator of the PMRP• Department Chair of Medical Genetics• Director of the Center for Human Genetics• Director of the Marshfield Clinic Laboratories,

or his/her designee• Director of Informatics and Decision Support• One or two members from the University of

Wisconsin, Madison (WI, USA), ideally onewith expertise in statistical genetics

The Director of Medical Research has discre-tion to add additional ad hoc, permanent or ex-officio members as necessary. The OversightCommittee meets monthly to review applica-tions to use the biobank and to prioritize infra-structure projects, such as the many informationsystems projects to facilitate access and qualityassurance for the three specimen types. They donot assess scientific merit; rather, they considerissues such as the amount of sample remainingand the quantity of sample requested for a study.

Requests to the Oversight Committee toaccess PMRP samples are submitted and trackedonline. Laboratory staff do not release samplesuntil all approvals have been documented,

including a Material Transfer Agreement if nec-essary. The legal department at the MarshfieldClinic developed a template for Material Trans-fer Agreements involving PMRP samples tospeed up the approval process.

So far, no requests to access the plasma orserum samples have been reviewed by the Over-sight Committee. We anticipate that the deci-sions surrounding the release of those specimensmay be more challenging, given the smallerquantity and the lack of an equivalent technol-ogy to whole-genome amplification to allowpreservation of the original sample.

Sample trackingA significant challenge for the PMRP was theability to manage the collection and tracking ofbiological samples. The PMRP uses MarshfieldClinic’s practice management and laboratoryinformation systems (LIS) for subject recruit-ment and DNA, plasma and serum sample col-lection. The initial decision to use these systemswas based on cost and the length of time itwould take to implement another informationsystem to support the recruiting and sample col-lection efforts. The LIS was not designed to linkmultiple samples together for an individual or totrack the location of an individual’s geneticmaterial within the freezer or elsewhere, afterseveral generations of plating. In addition,

dations from the first Scientific Advisory Board meeting, held in November 2001, and

Actions taken

ned Recruitment commenced in September 2001

tion Cohort is population-based, allowing for case–control or case–cohort designs

number of focused studies, Initially, the warfarin pharmacogenetics study was the only study being undertaken

ple to develop project proposals as about hypothesis, preliminary s, study power, and how the ertaken, in 3–5 pages

The Research Foundation already has a process to review studies for scientific merit. We are looking to streamline the process for PMRP studies where institutional funding is not requested

harmacogenetics study as a where you could have results strate the success if you assign e project

The warfarin pharmacogenetics study became the main study undertaken. To speed the process, recruitment was performed outside the biobank because the biobank was conducting general population recruitment

rators – academic versus industry The decision was made to concentrate on academic partnerships initially, in part because of a negative (although not universal) reaction from the Community Advisory Group to discussion regarding potential collaboration with industry

entified DNA samples to be sent The written informed consent document allows for sharing of samples and data. Sharing of both data and samples has already occurred

ine Research Project.

Personalized Medicine (2008) 5(5) future science groupfuture science group

The Marshfield Clinic Personalized Medicine Research Project – SPECIAL REPORT

future science groupfuture science group


Recommendation

Publish a paper in a peecharacteristics of the popower of the populationdid not slow the time to

Expand on the collection

Proceed with clinical stustudy within 6 months

Consider alliances with collections of SNPs/hapl

Continue diligence in sefor genotyping

Consider how in-house

quality information for each sample was storedin another unrelated database and needed to bemerged into a single system for efficient speci-men management. Owing to these limitations,the PMRP evaluated options to either modifythe existing LIS for biospecimen management orpurchase a commercial system. At an early stage,focus was directed at evaluating commercial bio-specimen tracking systems because the internalsoftware development resources were limited.Four commercial systems were evaluated, with afinal selection of the Nautilus® biospecimentracking system (Thermo Fischer, PA, USA).The Nautilus product offered a complete speci-men tracking system with many out-of-the-boxcustomizable features and integration tools thatwould allow PMRP software developers to cus-tomize user interfaces and interface to Marsh-field Clinic information systems. The laboratorytechnicians found the Nautilus user interfaceeasy to follow and felt that the solution met thefunctionality requested. The PMRP laboratoryand informatics teams are currently redesigningmany workflow processes and integrating Nauti-lus to promote efficient specimen handling forPMRP and other research activities.

Informatics has been a critical part of thePMRP since its infancy. One of the basic goalsof this project was to use both genetic sequencedata and existing clinical data to accelerate thestudy of diseases. To this end, PMRP capitalizes

on the use of Marshfield’s in-house developedCattail’s Software Suite to provide most of theclinical data for this effort. Data from the Cat-tails Suite are deposited into a centralized datarepository, where they are used for the ongoingclinical care of patients. Data from the central-ized data repository are transferred nightly toMarshfield Clinic’s data warehouse, where thedata are cleansed and integrated into the exist-ing data warehouse structure. Prior to addingdata sources to the data warehouse, the datasource is modeled and then integrated into theenterprise data model. This enables the datawarehouse development team to standardizenames, data types and variable definitions. Thedata are also grouped into logical subject areasthat are understandable to the users of the data.Internally developed applications and commer-cial bioinformatics tools provide access to thedata for a variety of clinical and business users.Figure 1 denotes the strategy used to develop thedata warehouse. Within the data warehouse,patient data from as early as 1960 are availableelectronically and linked together by a uniquepatient identifier. The data carry a time stampso historical profiles of clinical activity can bedeveloped for each PMRP participant. Datafrom the data warehouse are used for PMRPstudies and enable scientists to accurately iden-tify and categorize patient’s phenotypes forresearch studies.

dations from the second Scientific Advisory Board meeting, held in April 2002, and

Actions taken

r-reviewed journal defining the pulation and demonstrating the , incorporating genetic data if it publication

Two papers were published, one in 2005 [3] and one in 2007 [18], describing the biobank and available data

of family cohorts Information about relatedness is collected on the enrollment questionnaire. The decision was made not to recruit families specifically but to build a population-based biobank for association studies

dies; complete the warfarin The initial paper from this study was published in 2004 [27]; it was delayed, in part, by recruitment difficulties in the clinic. The prospective clinical study commenced immediately after the retrospective study was completed, with results published in 2005 [29]

other entities to obtain otypes and software for analysis

Collaborations have been initiated with scientists at the University of Wisconsin (WI, USA), with support from the Clinical and Translational Science Award, and with scientists at Vanderbilt University (TN, USA)

eking appropriate methods Genotyping technologies are continually assessed. In the context of multicenter studies, whole-genome association genotyping is being conducted at core laboratory facilities. Candidate-gene studies in-house are completed on the Sequenom® platform

SNP discovery will be undertaken This has not been undertaken due to limited staff and the decision to prioritize the development of the phenotypic infrastructure

531www.futuremedicine.com


532


Recommendation

Have a narrow focus onwith more depth

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Decide on the relative bthe PMRP as a national activity at Marshfield. If resource, more details abe available

The SAB should meet mtwice per year

PMRP: Personalized Medic

Personalized Medicine Research Project par-ticipants are asked to supply information ontheir health habits, environment, family historyand parent–sibling–child relationships. Thesedata reside in the data warehouse and are therebyuseful for PMRP studies. The InstitutionalReview Board and PMRP Oversight Committeeprovide approval for the use of these data. Datasecurity controls have also been developed toensure use of these data for PMRP studies onlyunless appropriate approval has been granted foradditional use.

Figure 2 denotes three distinct sources of dataused by the PMRP. The data within this figureflow from left to right into the PersonalizedMedicine Research Database (PMRD). The clin-ical data flow was described previously in thedata warehouse discussion. Clinical data consist-ing of diagnoses, laboratory values, procedures,insurance claims, clinical registry, billing andmedications data, found within the data ware-house, are used to phenotype PMRP subjects.Once a study population (and associated studydata) are identified and validated, data analysisvariables are packaged and sent to an encryptionprocess prior to being merged with the geneticdata located in the PMRD.

Personalized Medicine Research Project datarepresent a second data flow (shown in green inFigure 2). The movement of these data is similar

to the clinical data flow, except that the data arecollected as part of the PMRP. These datainclude information on a subject’s environment,health habits, pedigree and family history. ThePMRP data can either be packaged with the clin-ical data or packaged separately before sending tothe encryption process.

When genetic samples are genotyped, thegenetic data are deposited directly into thePMRD. A map between the genetic data sampleidentification number and the patient’sencrypted identification number is kept so thatall types of data can be combined for analysis.The PMRD has dramatically expanded in sizesince inception, and genotype data storage esti-mates are expected to exceed 10 terabytes overthe next 2 years. The current database and datastorage architecture will not support the esti-mated growth, thus the PMRP informatics teamis evaluating options for future system growth.

Study infrastructure & additional dataManolio and Collins of the National HumanGenome Research Institute discussed the com-plexity of studying the interaction of genes andenvironment in health and disease [4]. Limitedpersonal exposure information was collected onthe original PMRP enrollment questionnaire(smoking and alcohol use primarily), in part toencourage a high participation rate, leaving the

dations from the third Scientific Advisory Board meeting, held in November 2003, and

Actions taken

a smaller set of projects After initiating three internal studies initially, the decision was made to further encourage external collaborations and use of the database, thus the number and scope of projects increased

t, vision and well-defined g a Scientific Director

The overall goal of the PMRP is to translate genetic data into specific knowledge regarding disease that is clinically relevant and will enhance patient care, with a short-term goal to establish a database to allow research in genetic epidemiology, pharmacogenetics and population genetics. Funding limitations have precluded the hiring of a full-time Scientific Director, but the Oversight Committee fulfills this role

ollaborations Members of the Pharmacogenetics Research Network were invited to Marshfield in July 2006 to learn more about the PMRP. This visit resulted in the establishment of several collaborations, as mentioned in Tables 5 & 6. The Clinical and Translational Science Award is helping to facilitate increased collaboration with scientists at the University of Wisconsin (WI, USA)

alance between creating resource versus a research it is going to be a national bout data sharing need to

The decision was made to further encourage external collaborators, in part to realize the potential of the resource for genetic discovery. Guidelines for access are available on the PMRP website [101]

ore regularly, perhaps The grant that supported the SAB meetings ended, so additional meetings could not be held

ine Research Project; SAB: Scientific Advisory Board.




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possibility of recontact open through the writ-ten informed consent document. Given thatdietary intake and physical activity are relatedto so many health outcomes, the strategic deci-sion was made to retrospectively collect the dataon enrolled subjects and to add the data collec-tion prospectively with new enrollment. Marsh-field Clinic is a partner with the University ofWisconsin in their Clinical and TranslationalScience Award and Institute for Clinical andTranslational Research [102], and this collectionof dietary intake and physical activity data wasa major infrastructure project in years 1 and 2of Clinical and Translational Science Award toincrease the value of PMRP as a researchresource for gene–environment studies. TheMarshfield Clinic Institutional Review Boardreviewed and approved the protocol.

Dietary intakeConsideration of several dietary assessment toolswas undertaken. The gold standard, weighedfood records, were deemed to be impractical dueto the respondent burden and expense to quan-tify nutrient intake from the records. The 24-h

recalls were also considered to be too burden-some to subjects and staff. Food frequency ques-tionnaires (FFQs) are widely used to assessdietary intake in epidemiologic studies becausethey are more representative of usual intake andless expensive to implement than other method-ologies, including weighed food records and24-h dietary recalls, as they are usually self-administered [5,6]. The selected FFQ for thePMRP, the Diet History Questionnaire (DHQ)[103], was developed by researchers at theNational Cancer Institute and has been shown tobe superior to the commonly used Willett FFQand similar to the Block FFQ for estimatingabsolute nutrient intakes [7–13]. The DHQ com-prises 124 separate food items and asks aboutportion sizes for most foods. In addition, thereare ten questions regarding nutrient supplementintake. The DHQ is printed and scanned byOptimum Solutions (CA, USA). After scanning,the data from the questionnaires will be stored inASCII format and uploaded into the nutrientanalysis software package. Diet*Calc software,available from the NIH, will be used for thenutrient analyses of the DHQ data [104].

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Table 4. Comparison

Nutrient

Total energy (kcal)

Fat (%kcal)

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Protein (%kcal)

Carbohydrate (%kcal)

Calcium (mg)

Dietary fiber (g)

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Quantification of physical activityAs with measurement of dietary intake for epide-miologic studies, there are a number of differentvalidated tools that have been used to measurephysical activity in previous studies. The agree-ment between physical activity questionnaire andgold standard tends to be somewhat lower thanfor dietary intake, but is reasonable for rankingrelative activity levels in groups. We have chosento use a previously developed physical activityassessment tool to allow comparison with resultsfrom other study populations. Requirements ofthe selected tool for the current study included:

• Self-administered

• Previously validated

• Validated for use in a similar study populationacross a range of ages

The selected physical activity questionnaire, theBaecke questionnaire, is self-administered, vali-dated for use in both men and women, and cur-rently being used in a large, prospective study inthe USA [14–17]. The questionnaire has been shownto have high reliability (coefficients ranging from0.74 to 0.88) and accurate assessment of bothhigh-intensity activity and light-intensity activity,such as walking. It comprises 16 questions andgenerates three indices of activity: a work index, asport index and a leisure-time index.

The initial selection of PMRP subjects fromwhich to obtain the DHQ and physical activitydata included people with a BMI of 40 or overand two age- and sex-matched subjects with aBMI under 25 per obese subject. Two mailingsand a follow-up telephone call led to a 65%response rate (n = 2103 completed question-naires) in subjects who could be contacted. Sum-

mary DHQ data are presented in Table 4.Although average total daily caloric intake was notsignificantly different between the two groups, thedata reveal significant differences in many of theother specific nutrient and food categoriesbetween obese and healthy weight subjects. Fol-low-up with the rest of the PMRP cohort toobtain these data is anticipated to be completedby the end of 2008.

The DHQ and physical activity question-naires have been added prospectively for all newsubjects being enrolled into PMRP. Subjects aregiven the questionnaires and asked to completethem and return them in stamped, self-addressedenvelopes. With no further reminders, theresponse rate for prospective collection has been74%, thus demonstrating the efficiency ofcollecting information at the time of enrollment.

Genetic association studiesThe following sections outline the studies thatare currently accessing the PMRP biobank underthe categories of pharmacogenetics and geneticepidemiology. Although the PMRP was alsodesigned to support studies of population genet-ics, to date there are no projects in this area. Inaddition to summarizing the study objectives, wehave included infrastructure lessons learnedthrough these studies. Results appear in separatepeer-reviewed publications, as well as the PMRPstudy newsletters available on the PMRPwebsite [101]. As suggested by the SAB in theirearly meetings, scientific discoveries using thePMRP have been enhanced through externalcollaborations, with a number of collaborationswith members of the Pharmacogenetics ResearchNetwork [105].

of daily dietary intake between healthy weight (BMI <25) and obese (BMI ≥40) subjects.

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52.2 (38.2, 67.5) 49.8 (37.0, 65.0) <0.001

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16.4 (6.7, 37.8) 16.1 (6.0, 38.8) 0.54

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759.5 (272.4, 1820.7) 764.5 (287.1, 1910.7) 0.01

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rror

in t

he s

ex

mar

kers

was

iden

tifie

d in

thi

s st

udy

of 4

50 s

ubje

cts,

and

hig

hlig

hted

th

e ne

ed to

dev

elop

a m

olec

ular

fing

erpr

int t

o id

entif

y th

e sa

mpl

es. T

he

resu

lts o

f th

is p

roje

ct w

ill b

e re

port

ed s

epar

atel

y. A

noth

er le

sson

le

arne

d in

this

pro

ject

was

the

amou

nt o

f tim

e ne

cess

ary

to c

hara

cter

ize

drug

exp

osur

e fr

om t

he m

inin

g of

ele

ctro

nic

note

s fo

r in

dica

tion

of

drug

use

. Fin

ally

, we

disc

over

ed t

hat

the

smok

ing

ques

tions

in t

he

orig

inal

PM

RP q

uest

ionn

aire

did

not

allo

w f

or t

he c

alcu

latio

n of

pac

k ye

ars

beca

use

they

did

not

incl

ude

a qu

estio

n ab

out

how

long

sub

ject

s ha

d sm

oked

. Sub

sequ

ently

, pos

tcar

ds w

ere

mai

led

to th

e ne

arly

10,

000

PMRP

sub

ject

s w

ho r

epor

ted

that

the

y ha

d ev

er s

mok

ed c

igar

ette

s to

co

llect

info

rmat

ion

abou

t du

ratio

n of

sm

okin

g.

In p

repa

ratio

n

FMS

To s

tudy

a c

andi

date

gen

e fo

r FM

S an

d qu

antif

y ge

ne–e

nviro

nmen

t in

tera

ctio

n w

ith c

igar

ette

sm

okin

g, m

otor

veh

icle

ac

cide

nts

and

othe

r tr

aum

a

Non

eIn

itial

fea

sibi

lity

estim

ates

ove

rest

imat

ed t

he n

umbe

r of

FM

S ca

ses

in

the

PMRP

coh

ort

whe

n ap

plyi

ng s

tric

t di

agno

stic

crit

eria

. The

pro

ject

tim

elin

e w

as a

ltere

d to

allo

w f

or t

arge

ted

recr

uitm

ent

of F

MS

subj

ects

fr

om z

ip c

odes

oth

er t

han

the

orig

inal

19

zip

code

s se

lect

ed f

or

PMRP

enro

llmen

t

In p

repa

ratio

n

Ost

eopo

rosi

sTo

iden

tify

cand

idat

e ge

nes

for

oste

opor

osis

and

to

quan

tify

pote

ntia

l ge

ne–e

nviro

nmen

t in

tera

ctio

ns w

ith

ciga

rett

e sm

okin

g an

d st

atin

use

PGRN

col

leag

ues

Man

y w

omen

had

not

und

ergo

ne B

MD

tes

ting

to c

onfir

m c

ontr

ol

stat

us. A

n ar

ticle

was

writ

ten

for

the

twic

e-ye

arly

PM

RP n

ewsl

ette

r de

scrib

ing

the

stud

y an

d in

form

ing

wom

en o

f sc

reen

ing

guid

elin

es

rela

ted

to B

MD

tes

ting

in w

omen

age

d 50

year

s an

d ol

der

In p

repa

ratio

n

AD

: Alz

hei

mer

’s D

isea

se; B

MD

: Bo

ne

min

eral

den

sity

; CA

D: C

oro

nar

y ar

tery

dis

ease

; FM

S: F

ibro

mya

lgia

syn

dro

me;

GW

AS:

Gen

om

e-w

ide

asso

ciat

ion

stu

die

s; H

DL:

Hig

h-d

ensi

ty li

po

pro

tein

; M

I:M

yoca

rdia

l in

farc

tio

n; P

MR

P:Pe

rso

nal

ized

Med

icin

e R

esea

rch

Pro

ject

.



CA

DTo

ser

ve a

s a

repl

icat

ion

coho

rt f

or

GW

AS

to id

entif

y m

arke

rs a

ssoc

iate

d w

ith C

AD

Med

ical

Col

lege

of

Wis

cons

inC

hang

es in

the

rea

ding

of

caro

tid u

ltras

onog

raph

y ov

er t

ime

nece

ssita

te m

anua

l rev

iew

of

char

ts t

o cl

assi

fy c

ase–

cont

rol s

tatu

sN

one

yet,

as

the

stud

y w

as o

nly

rece

ntly

fun

ded

Cat

arac

t an

d lo

w H

DL

To d

evel

op e

lect

roni

c al

gorit

hms

for

cata

ract

and

low

HD

L, t

o co

nduc

t co

mm

unity

con

sulta

tion

activ

ities

re

late

d to

dat

a sh

arin

g, a

nd t

o co

nduc

t a

GW

AS

of c

atar

act

and

low

HD

L

Uni

vers

ity o

f W

isco

nsin

(WI,

USA

), M

edic

al

Col

lege

of

Wis

cons

in,

Vand

erbi

lt U

nive

rsity

(T

N,U

SA)

The

amou

nt o

f di

sc s

pace

to

stor

e an

d m

anag

e da

ta f

rom

GW

AS

is

subs

tant

ial.

Alth

ough

the

PMRP

con

sent

form

allo

ws

for d

ata

shar

ing,

it

need

s to

be

mor

e ex

plic

it ab

out

the

data

-sha

ring

requ

irem

ents

of

GW

AS

fund

ed b

y th

e N

IH

Com

mun

ity

cons

ulta

tion

man

uscr

ipt

unde

r re

view

Dys

lipid

emia

in

sev

erel

y ob

ese

subj

ects

To s

tudy

can

dida

te g

enes

ass

ocia

ted

with

dia

bete

s an

d dy

slip

idem

ia in

su

bjec

ts w

ith a

BM

I of

40+

and

iden

tify

pote

ntia

l gen

e–en

viro

nmen

t in

tera

ctio

ns w

ith d

iet

and

activ

ity

Med

ical

Col

lege

of

Wis

cons

inA

sta

ndar

d te

mpl

ate

for

Mat

eria

l Tra

nsfe

r A

gree

men

ts s

peed

s th

e le

gal

proc

ess

to a

llow

the

shi

pmen

t of

sam

ples

to

othe

r la

bora

torie

s fo

r ge

noty

ping

Non

e ye

t, a

s th

e pr

ojec

t ha

s on

ly r

ecen

tly

been

initi

ated

Hyp

erte

nsiv

e he

art

dise

ase

To id

entif

y ca

ndid

ate

mar

kers

in t

he

vita

min

D p

athw

ay t

hat

incr

ease

ris

k fo

rhy

pert

ensi

on a

nd h

yper

tens

ive

hear

tdi

seas

e

Uni

vers

ity o

f M

ichi

gan

(MI,

USA

)

Repl

icat

ion

of f

indi

ngs

from

ani

mal

mod

els

is a

sou

nd s

trat

egy

In p

repa

ratio

n

Myo

card

ial i

nfar

ctio

nTo

rep

licat

e tw

o SN

Ps o

n 9p

21

iden

tifie

d in

GW

AS

for

MI [

21] i

n th

e co

ntex

t of

kno

wn

clin

ical

cov

aria

tes,

in

clud

ing

age,

sex

, sm

okin

g, p

hysi

cal

activ

ity, d

iabe

tes,

BM

I, fa

mily

his

tory

of

MI,

and

hype

rten

sion

Med

ical

Col

lege

of

Wis

cons

in,

Uni

vers

ity o

f W

isco

nsin

The

first

stu

dy t

o us

e al

l 20,

000

PMRP

sam

ples

, thi

s st

udy

bene

fited

fr

om a

mas

ter

plat

ing

proj

ect

that

sig

nific

antly

red

uced

the

tim

e to

cr

eate

pla

tes

to s

hip

off

site

for

gen

otyp

ing

Non

e ye

t, a

s th

e pr

ojec

t w

as o

nly

rece

ntly

initi

ated

Tab

le 5

. Gen

etic

ep

idem

iolo

gy

stu

die

s u

sin

g t

he

Pers

on

aliz

ed M

edic

ine

Res

earc

h P

roje

ct b

iob

ank,

less

on

s le

arn

ed a

nd

res

ult

ing

pu

blic

atio

ns

(co

nt.

).

Stu

dy

Purp

ose

Exte

rnal

co

llab

ora

tio

ns

Less

on

s le

arn

edPu

blic

atio

ns

AD

: Alz

hei

mer

’s D

isea

se; B

MD

: Bo

ne

min

eral

den

sity

; CA

D: C

oro

nar

y ar

tery

dis

ease

; FM

S: F

ibro

mya

lgia

syn

dro

me;

GW

AS:

Gen

om

e-w

ide

asso

ciat

ion

stu

die

s; H

DL:

Hig

h-d

ensi

ty li

po

pro

tein

; M

I:M

yoca

rdia

l in

farc

tio

n; P

MR

P:Pe

rso

nal

ized

Med

icin

e R

esea

rch

Pro

ject

.

537future science groupfuture science group www.futuremedicine.com

Ta
ble

6. P

har

mac

og

enet

ic s

tud

ies

usi

ng

th

e PM

RP

bio

ban

k, le

sso

ns

lear

ned

an

d r

esu

ltin

g p

ub

licat

ion

s.

Stu

dy

Purp

ose

Exte

rnal

co

llab

ora

tio

ns

Less

on

s le

arn

edPu

blic

atio

ns

Topi

cal β

-blo

cker

s fo

r gl

auco

ma

To id

entif

y ca

ndid

ate

mar

kers

th

at p

redi

ct a

20%

or g

reat

er

drop

in in

trao

cula

r pr

essu

re

Med

ical

Col

lege

of

Wis

cons

in (W

I, U

SA)

Con

serv

ativ

e de

finiti

ons

for

win

dow

s of

fol

low

-up

data

cre

ate

hom

ogen

ous

data

sets

, whi

le d

ecre

asin

g sa

mpl

e si

ze[2

2–24

]

Stat

in e

ffic

acy

To id

entif

y ge

netic

mar

kers

of

LD

L re

spon

se t

o at

orva

stat

in

Phar

mac

ogen

etic

s Re

sear

ch N

etw

ork

colle

ague

s (C

hild

ren’

s H

ospi

tal

Oak

land

Res

earc

h In

stitu

te, C

A, U

SA)

Allo

w a

dditi

onal

tim

e fo

r M

TAs

that

nee

d to

be

revi

ewed

and

app

rove

d by

m

ultip

le in

stitu

tions

. Mas

ter

DN

A p

late

s dr

amat

ical

ly d

ecre

ase

the

amou

nt

of t

ime

nece

ssar

y to

iden

tify

and

plat

e D

NA

sam

ples

for

gen

otyp

ing

[25,

26]

Met

form

in

for

diab

etes

To e

valu

ate

cand

idat

e m

arke

rs f

or H

bA1c

res

pons

e to

met

form

in in

Cau

casi

ans

from

PM

RP a

nd

Afr

ican

–Am

eric

ans

from

K

aise

r G

eorg

ia (G

A, U

SA)

Phar

mac

ogen

etic

s Re

sear

ch N

etw

ork

(Uni

vers

ity o

f C

alifo

rnia

, San

Fr

anci

sco,

CA

, USA

), K

aise

r G

eorg

ia

As

the

PMRP

is 9

8% C

auca

sian

, col

labo

ratio

n w

ith o

ther

gro

ups

is e

ssen

tial

to a

llow

rep

licat

ion

of f

indi

ngs

in o

ther

rac

e/et

hnic

gro

ups

War

farin

To id

entif

y pr

edic

tors

of

stab

le w

arfa

rin d

ose

and

deve

lop

a do

sing

cal

cula

tor

to in

clud

e al

l kno

wn

mod

ifier

s of

sta

ble

dose

Phar

mac

ogen

etic

s Re

sear

ch N

etw

ork

(Uni

vers

ity o

f Flo

rida,

FL

, USA

), In

tern

atio

nal

War

farin

Con

sort

ium

As

reco

mm

ende

d by

the

SA

B, t

his

was

the

firs

t st

udy

to s

how

case

the

po

tent

ial o

f th

e M

arsh

field

bio

bank

and

to

deve

lop

man

y ex

tern

al

colla

bora

tions

, inc

ludi

ng o

ne to

iden

tify

new

com

poun

ds f

or c

linic

al t

estin

g.

Thes

e st

udie

s ha

ve le

d to

sev

eral

pee

r-re

view

ed p

ublic

atio

ns, t

he d

isco

very

of

a n

ew g

enet

ic a

ssoc

iatio

n w

ith w

arfa

rin s

tabl

e th

erap

eutic

dos

e, f

undi

ng

from

the

Age

ncy

for

Hea

lthca

re R

esea

rch

and

Qua

lity

to p

rosp

ectiv

ely

eval

uate

the

eff

icac

y of

gen

e-ba

sed

pres

crib

ing

for

war

farin

, and

the

de

velo

pmen

t of

the

IWPC

, an

inte

rnat

iona

l con

sort

ium

agg

rega

ting

6000

patie

nt’s

data

to

stud

y w

arfa

rin p

harm

acog

enet

ics.

The

dat

a fr

om t

he

IWPC

will

be

plac

ed in

the

pub

lic d

omai

n th

roug

h th

e Ph

arm

GK

B w

ebsi

te[1

09] i

n la

te20

08

[27–

31]

Tam

oxife

n in

br

east

can

cer

To id

entif

y m

aker

s fo

r re

spon

se a

nd a

dver

se

reac

tions

(dee

p-ve

in

thro

mbo

sis)

to

tam

oxife

n fo

r br

east

can

cer

Phar

mac

ogen

etic

s Re

sear

ch N

etw

ork

(Indi

ana

Uni

vers

ity,

IN, U

SA),

Med

ical

C

olle

ge o

f W

isco

nsin

A s

tand

ard

tem

plat

e M

TA s

peed

s th

e le

gal p

roce

ssU

nder

rev

iew

Stat

in m

yoto

xici

ty

and

rhab

dom

yoly

sis

To id

entif

y ge

netic

mar

kers

th

at p

redi

ct t

he m

ost

com

mon

tox

icity

for

one

of

the

mos

t co

mm

only

pr

escr

ibed

dru

gs in

the

wor

ld

Phar

mac

ogen

etic

s Re

sear

ch N

etw

ork

(Chi

ldre

n’s

Hos

pita

l O

akla

nd R

esea

rch

Inst

itute

), M

edic

al

Col

lege

of

Wis

cons

in

Stat

in m

yoto

xici

ty is

ver

y di

ffic

ult

to p

heno

type

usi

ng m

edic

al r

ecor

ds

beca

use

the

docu

men

tatio

n of

pai

n sy

mpt

oms

is n

ot s

tand

ard

[32,

33]

IWPC

: In

tern

atio

nal

War

fari

n P

har

mac

og

enet

ic C

on

sort

ium

; LD

L: L

ow

-den

sity

lip

op

rote

in; M

TA: M

ater

ial T

ran

sfer

Ag

reem

ents

; PM

RP:

Per

son

aliz

ed M

edic

ine

Res

earc

h P

roje

ct; S

AB

: Sci

enti

fic

Ad

viso

ry B

oar

d.




Genetic epidemiologyIn addition to standard case–control studies ofdisease onset, the PMRP is ideally suited to thestudy of risk factors for disease progression,because over 20 years of medical history infor-mation is available for approximately 75% of thecohort [18]. Table 5 summarizes the genetic epide-miology studies using the PMRP database andthe many lessons learned.

Pharmacogenetic studies Prior to the implementation of electronic pre-scribing and a paperless environment in 2007,mention of medication use in the text was cap-tured through natural language processing and isavailable back to 1993. These resources haveallowed the initiation of many pharmacogeneticstudies, several of which are in collaborationwith colleagues in the PharmacogeneticsResearch Network [105]. As with genetic epidemi-ology, many lessons have been learned to increaseefficiency and accuracy (Table 6).

ConclusionIn summary, much has been learned since thePMRP was launched in 2002, and many discov-ery projects are underway. With each new studyundertaken, it is important to revisit proceduresto be sure that they keep pace with genetic andstatistical tools that are being developed andrefined. We have found that it is far more efficientto collect personal exposure and environmentaldata at the time that people are enrolled into thebiobank and to conduct quality assurance on thesamples as they are received. Collaboration hasgreatly enhanced the science, and multidiscipli-nary teams are essential to address the complexissues involved with studying complex diseases. Asnew biobanks are being initiated, the sharing ofmethods and standards will help to facilitatesharing of data for comparison and replication.

Future perspectiveBiobanking Banking of biological materials for research andclinical purposes will likely continue to increaseand will decrease the time between discoveryand clinical translation. Much can be learnedby sharing the success and failures of theseendeavors. The PMRP has been committed tosharing data, and lessons learned, for the widerscientific community.

The current National Human GenomeResearch Institute-funded electronic medicalrecords and genomics (eMERGE) network [106],

of which PMRP is a member, is charged withdeveloping standards to allow for the efficientsharing of data from across the network. TheeMERGE network is a national consortiumformed to develop, disseminate and applyapproaches to research that combine DNAbiorepositories with electronic medical recordsystems for large-scale, high-throughput geneticresearch. Through researching new method-ologies and disseminating the information, thisconsortium will improve the use of bioreposito-ries for genomic research. The five sites fundedincluded Marshfield Clinic, Northwestern Uni-versity (IL, USA), Vanderbilt University (TN,USA), Mayo Clinic (MN, USA) and GroupHealth Cooperative (WA, USA).

Organizations such as the Public PopulationProject in Genomics (P3G) [107] are also seekingto develop best practice for biobanking. P3G is anot-for-profit international consortium to pro-mote collaboration between researchers in thefield of population genomics. It was launched toprovide the international population genomicscommunity with the resources, tools and know-how to facilitate data management for improvedmethods of knowledge transfer and sharing. Itsmain objective is the creation of an open, publicand accessible knowledge database. The motto is‘transparency and collaboration’. All groups ben-efit from the sharing of methodologies and data.

The challenge for all of these groups is toidentify infrastructure funding and to ensuretimely translation of research results.

Translation into personalized healthcareSmall- and large-scale genetic association studiesare moving expert biological knowledge from thebench to the bedside at an unprecedented rate.The Personalized Health Care Initiative from theDepartment of Health and Human Services seeksto “improve the safety, quality and effectiveness ofhealthcare for every patient in the US by usinggenomics … to enable medicine to be tailored toeach person’s needs” [108]. The substrate of func-tional genomics is expanding geometrically, andefficient bioinformatics resources are being devel-oped feverishly in an effort to help scientists andclinicians leverage this knowledge to improvehealthcare. The potential seems unlimited.Genetic risk determinants can be merged withclinical data to predict patient risk, before theonset of disease. This should allow focused earlyintervention for patients at highest risk. Geneticmarkers can also be used for risk stratification oncea particular condition has developed. This should



540

Executive summary

Scientific Advisory Bo

• The Scientific Advisoryhave been useful to hfunding to support thfrom the Marshfield Cbioinformatics tools n

Oversight Committee

• It is neccessary to devCommittee should hacrucial to the studies.

Sample tracking

• It is neccessary to outdataset that allows fopurchasing a system a

Study infrastructure &

• The collection of persorequired to collect thedata collected should

Genetic association st

• Many lessons have beprocedures to keep p

optimize secondary prevention and reduce theburden of comorbidity being placed upon ourhealthcare infrastructure as the population contin-ues to age. Genetic markers will also be highly use-ful in directing therapy, in the context ofpharmacologic as well as nonpharmacologic inter-vention. For drugs with a narrow therapeuticindex, this has already become a clinical reality.Many antineoplastic agents are prescribed and/ordosed based upon genotype in an effort to reducethe risk of adverse drug reactions, and evidence ismounting that this approach will be beneficial forother drugs, such as anticoagulants. As technologyadvances (e.g., genome-wide association studies),the genetic architecture underlying drug responsewill almost certainly become more fully character-ized for a multitude of therapeutic agents, makingthis prospective gene-based approach to risk reduc-tion and treatment prescription advantageous forall drugs, including those with a relatively widetherapeutic index [19,20]. Proteomics and metabo-lomics will further the usefulness of genomics dis-covery for personalized healthcare. The vastamount of information necessary for discovery anddecision support requires a robust informaticsinfrastructure. A well-designed and -executedbiobank is merely the first step in the path frombasic discoveries to personalized healthcare.

Acknowledgements

The authors acknowledge Dr Laura Coleman and BickolMukesh for their contributions to the analysis of the dietaryintake data.

Financial & competing interests disclosure The research was funded, in part, by grant number 1 D1ARH00025-01 from the Office of Rural Health Policy,Health Resources and Services Administration, from theDepartment of Commerce (WI, USA) and grant number1UL1RR025011 from the Clinical and Translational Sci-ence Award (CTSA) program of the National Center forResearch Resource National Institute of Health. The mem-bers of the PMRP Scientific Advisory Board include: DavidAltshuler, MD, PhD, Massachusetts Institute for Technology(MA, USA), Chair; David Flockhart, MD, PhD, IndianaUniversity (IN, USA); Stephen Liggett, MD, University ofMaryland (MD, USA); Gabor Marth, DSc, Boston College(MA, USA); Jurg Ott, PhD, Rockefeller University (NY,USA); Lenna Peltonen, MD, PhD, Biomedicum Helsinki(Helsinki, Finland); Wendell Weber, MD, PhD, Universityof Michigan (MI, USA). The authors have no other rele-vant affiliations or financial involvement with any organi-zation or entity with a financial interest in or financialconflict with the subject matter or materials discussed in themanuscript apart from those disclosed.

No writing assistance was utilized in the production ofthis manuscript.

ard

Board was very useful in advising on design and strategic issues for growth and development, and it would ave their advice on issues that developed as the biobank grew, such as new technologies. Infrastructure e continued engagement of the Scientific Advisory Board has been difficult to identify. Institutional support linic on an annual basis must be prioritized, and has been used to continue recruitment and to develop the ecessary to access the biobank.

elop the process and procedures to access the biobank and make forms available online. The Oversight ve representation from content experts in the types of samples available, as well as the informatics support

line the computer hardware and software needs to manage an ever-growing genotypic and phenotypic r easy searchability. The advantages and disadvantages of developing the necessary software in-house or nd having it customized as needed must be weighed up.

additional data

nal/environmental exposure data at the time of study enrollment should be considered. Fewer resources are information at the time of enrollment, and the participation will be higher then. However, the amount of

be weighed against the potential for a lower participation rate initially because of respondent burden.

udies

en learned in the conduct of the genetic discovery studies, as outlined in Tables 5 & 6. Constant review of ace with changes in technology is essential.



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Websites101. Marshfield Clinic Research Foundation

Personalized Medicine Research Projectwww.marshfieldclinic.org/pmrp

102. University of Wisconsin Institute for Clinical and Translational Research www.ictr.wisc.edu

103. US NIH, National Cancer Institute: Risk factor monitoring and methods: diet history questionnaire (2007) http://riskfactor.cancer.gov/DHQ

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105. US NIH, National Institute of General Medical Sciences: Pharmacogenetics research network (2008) www.nigms.nih.gov/Initiatives/PGRN

106. The eMERGE Network – Electronic Medical Records and Genomics www.gwas.org

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107. Pharmacogenetics Research Network www.nigms.nih.gov/Initiatives/PGRN

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108. HHS.gov: Personalised Health Care www.dhhs.gov/myhealthcare

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109. PharmGKB: The Pharmacogenetics and Pharmacogenomics Knowledge Basewww.pharmgkb.org


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