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Crit Rev Clin Lab Sci, Early Online: 1–18! 2015 Informa Healthcare USA, Inc. DOI: 10.3109/10408363.2014.997930

REVIEW ARTICLE

Genomic medicine and risk prediction across the disease spectrum

Maritha J. Kotze1, Hilmar K. Luckhoff1, Armand V. Peeters1, Karin Baatjes2, Mardelle Schoeman3,Lize van der Merwe3,4, Kathleen A. Grant1,5, Leslie R. Fisher1, Nicole van der Merwe1, Jacobus Pretorius1,David P. van Velden1, Ettienne J. Myburgh6, Fredrieka M. Pienaar7, Susan J. van Rensburg8, Yandiswa Y. Yako8,Alison V. September9, Kelebogile E. Moremi8, Frans J. Cronje10, Nicki Tiffin11, Christianne S. H. Bouwens12,Juanita Bezuidenhout1, Justus P. Apffelstaedt2, F. Stephen Hough12, Rajiv T. Erasmus7, and Johann W. Schneider1

1Division of Anatomical Pathology, Department of Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South

Africa, 2Department of Surgery, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa, 3Division of Molecular

Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University and Tygerberg Hospital, Cape Town, Western Cape,

South Africa, 4Department of Statistics, University of the Western Cape, Cape Town, Western Cape, South Africa, 5Department of Biomedical

Sciences, Faculty of Health and Wellness, Cape Peninsula University of Technology, Cape Town, South Africa, 6Panorama Medi-Clinic, Cape Town,

South Africa, 7GVI Oncology, Panorama Medi-Clinic, Cape Town, South Africa, 8Division of Chemical Pathology, Department of Pathology, Faculty

of Medicine and Health Sciences, Stellenbosch University and National Health Laboratory Service, Cape Town, South Africa, 9UCT/MRC Research

Unit for Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town, Cape Town, South Africa, 10Department of

Interdisciplinary Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa, 11South African National

Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, South Africa, and12Department of Internal Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa

Abstract

Genomic medicine is based on the knowledge that virtually every medical condition, diseasesusceptibility or response to treatment is caused, regulated or influenced by genes. Genetictesting may therefore add value across the disease spectrum, ranging from single-genedisorders with a Mendelian inheritance pattern to complex multi-factorial diseases. The criticalfactors for genomic risk prediction are to determine: (1) where the genomic footprint of aparticular susceptibility or dysfunction resides within this continuum, and (2) to what extent thegenetic determinants are modified by environmental exposures. Regarding the small subset ofhighly penetrant monogenic disorders, a positive family history and early disease onset aremostly sufficient to determine the appropriateness of genetic testing in the index case and toinform pre-symptomatic diagnosis in at-risk family members. In more prevalent polygenic non-communicable diseases (NCDs), the use of appropriate eligibility criteria is required to ensure abalance between benefit and risk. An additional screening step may therefore be necessary toidentify individuals most likely to benefit from genetic testing. This need provided the stimulusfor the development of a pathology-supported genetic testing (PSGT) service as a new modelfor the translational implementation of genomic medicine in clinical practice. PSGT is linked tothe establishment of a research database proven to be an invaluable resource for the validationof novel and previously described gene-disease associations replicated in the South Africanpopulation for a broad range of NCDs associated with increased cardio-metabolic risk. Theclinical importance of inquiry concerning family history in determining eligibility forpersonalized genotyping was supported beyond its current limited role in diagnosing orscreening for monogenic subtypes of NCDs. With the recent introduction of advancedmicroarray-based breast cancer subtyping, genetic testing has extended beyond the genomeof the host to also include tumor gene expression profiling for chemotherapy selection. Thedecreasing cost of next generation sequencing over recent years, together with improvementof both laboratory and computational protocols, enables the mapping of rare genetic disordersand discovery of shared genetic risk factors as novel therapeutic targets across diagnosticboundaries. This article reviews the challenges, successes, increasing inter-disciplinaryintegration and evolving strategies for extending PSGT towards exome and whole genomesequencing (WGS) within a dynamic framework. Specific points of overlap are highlighted

Keywords

Breast cancer, database, exome, genome,hg19, major allele reference sequence,metabolic syndrome, multiple sclerosis

History

Received 6 July 2014Revised 3 November 2014Accepted 20 November 2014Published online 19 January 2015

Referees: Prof Jeanine Marnewick, Cape Peninsula University of Technology, Health and Wellness Sciences, Cape Town, South Africa; Prof. RafaelRangel-Aldao, Biotechnology, Simon Bolivar University, Venezuela

Address for correspondence: Prof M. J. Kotze, Division of Anatomical Pathology, Department of Pathology, Faculty of Medicine and Health Sciences,University of Stellenbosch, Cape Town, South Africa. Tel: +27 21 9389324. E-mail: maritha@sun.ac.za

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between the application of PSGT and exome or WGS, as the next logical step in geneticallyuncharacterized patients for whom a particular disease pattern and/or therapeutic failure arenot adequately accounted for during the PSGT pre-screen. Discrepancies between differentnext generation sequencing platforms and low concordance among variant-calling pipelinescaution against offering exome or WGS as a stand-alone diagnostic approach. The publicreference human genome sequence (hg19) contains minor alleles at more than 1 million lociand variant calling using an advanced major allele reference genome sequence is crucial toensure data integrity. Understanding that genomic risk prediction is not deterministic butrather probabilistic provides the opportunity for disease prevention and targeted treatment in away that is unique to each individual patient.

Abbreviations: AOL: Adjuvant! Online; APOE: apolipoprotein E; BMI: body mass index; BRCA1:breast cancer gene 1; BRCA2: breast cancer gene 2; BIG: Breast International Group; CYP2D6:Cytochrome P450, family 2, subfamily D, polypeptide 6; CVD: cardiovascular disease; DTC:direct-to-consumer; EDSS: expanded disability status scale; ER: estrogen receptor; FH familialhypercholesterolaemia; FISH: fluorescence in situ hybridization; FFPE: formalin fixed paraffinembedded; GWAS genome-wide association studies; HH: hereditary hemochromatosis; HER2:human epidermal growth factor receptor 2; IHC: immunohistochemistry; ITM: intima mediathickness; MDD: major depressive disorder; MTHFR: methylene-tetrahydrofolate reductase;NCDs: non-communicable diseases; NAFLD: non-alcoholic fatty liver disease; NASH: non-alcoholic steatohepatitis; PSGT pathology-supported genetic testing; PCR: polymerase chainreaction; PR: progesterone receptor; RCTs: randomized controlled clinical trials; RASTER:microarray prognistics in breast cancer; MS: multiple sclerosis; RT-PCR: reverse transcriptasepolymerase chain reaction; SNPs: single nucleotide polymorphisms; TMPRSS6: transmembraneprotease, serine 6; TNBC: triple-negative breast cancer; VaD: vascular dementia; WES: wholeexome sequencing; WGS: whole genome sequencing

Introduction

A dramatic epidemiological transition in the prevalence from

acute to chronic non-communicable diseases (NCDs) has

been observed over the last century1. Major technological

advances in genomics2 are well placed to support a new

medical model that may be required in this context, in keeping

with the ideals of personalized medicine3. However, with the

exception of a restricted number of established clinical

applications, personalized genomics, recognized as a form

of medicine that uses information about genes, proteins and

the environment for improved risk management, has yet to be

embraced to the extent that was initially anticipated following

completion of sequencing of the human genome in 2003.

During most of the history of genetics, it has been a purely

scientific field, limited to the laboratory. Genetic testing

gained a small clinical role as a diagnostic tool for a number

of hereditary or congenital disorders, but with limited

therapeutic implications. As in the case of Huntington’s

disease, in spite of the ability to identify the gene defect, the

fact that no therapeutic options exist resulted in reluctance of

many patients to undergo pre-symptomatic genetic testing4.

Therapeutic implications of genetic diseases started entering

clinical practice in two areas: first, in the realm of risk

reduction therapy based on the identification of deleterious

germline mutations in at-risk individuals. Familial colon and

breast cancer are two examples where testing of DNA

extracted from blood, saliva or buccal swabs for germline

mutations allowed for surgical intervention to reduce the risk

of developing cancer. Second, the search for a cure for cancer

based on tumor behavior led to the development of several

biological agents targeting the kinase pathway in the cell

cycle. Genetic tests such as fluorescence in situ hybridization

(FISH) used in combination with immunohistochemistry

(IHC) became the gold standard for detection of human

epidermal growth factor receptor-2 (HER2) over-expressing

breast cancer using formalin fixed paraffin embedded (FFPE)

tissue. Although response rates can be dramatically improved

by anti-HER2 treatment in a subgroup of patients, predictive

markers for chemotherapy selection only became available

with the more recent introduction of transcriptional profiling

for breast cancer prognostication5. Based on these develop-

ments, a multi-disciplinary model of cancer risk assessment

and clinical management was established, which now pro-

vides a solid foundation for extended incorporation of

genomics in clinical practice.

In spite of more than two decades of clinical application of

genetics, most clinicians have little training and experience in

using genetic tests to guide therapeutic decision making.

There seems to be a progressively widening gap between the

explosion in novel genomic information and the ability to

apply this new knowledge to clinical patient care6. In contrast

to the initial expectation of a ‘‘one gene, one disease’’

concept, genetic aspects of NCDs are complicated by the

variable penetrance of disease-causing mutations and disease-

associated polymorphisms that may interact with various

biological, physical and social factors. It has therefore become

important to develop enrollment guidelines for participation

in genomics-based risk assessment and management pro-

grams formulated from evidence supporting the performance

and clinical utility of an ever-increasing number of genomic

tests7. Against this background, a pathology-supported gen-

etic testing (PSGT) service was developed to identify

subgroups of patients requiring different treatment strategies8.

An integrated service and research approach is used for

establishing and populating a research database to facilitate

the following:

(1) Development and evaluation of referral guidelines for

genomic tests with sufficient high-quality evidence of

clinical relevance published in the scientific literature

(clinical validation).

2 M. J. Kotze et al. Crit Rev Clin Lab Sci, Early Online: 1–18

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(2) Evaluation of the performance of new genomic tests

against the gold standard for improved quality assurance

(analytical validation).

(3) Documenting treatment decision making and health

outcomes over time to determine the impact of genomics

in a clinical setting outside a controlled research envir-

onment (clinical utility).

The need for a new clinical model to facilitate responsible

communication of complex genomic risk information, led to

the establishment of a central research database in parallel

with routine genetic testing service delivery using an ethically

approved protocol (project reference numbers N09/06/166

and 09/08/224, Stellenbosch University). Following informed

consent from the patient, a questionnaire is used to capture

data on personal and family medical conditions, medication

use and side effects, lifestyle factors and pathology test results

relevant to the genetic analysis performed. A waiver of

consent may also apply to specific ethically approved projects

where potential benefit to society is considered greater than

the perceived risk that may be related to such a sub-study. The

central genomics database resource (accessible to registered

users at www.gknowmix.org) was developed to facilitate

research translation at the interface between the laboratory

and clinic.

While randomized controlled clinical trials (RCTs) have

been the standard for developing new therapeutic interventions,

they remain costly to design and run, require large data sets and

need lengthy follow-up to assess the final outcome. In many

cases, the development of new technologies outpaces the

reporting of trial results. Alternative models are being

employed to allow faster data acquisition and earlier adoption

of new treatment options. One example of this approach is the

use of neo-adjuvant trials in oncology, where the effect of

chemotherapy can be seen on the tumor tissue as a result of the

intervention before removal. Similar substitute models have

been suggested for evaluation of complex genomic applica-

tions9. When aiming to match a biomarker profile with drug

treatment, the impact of the genomic test on clinical decision-

making is an important determinant of the level of regulation

required. The use of prospectively collected patient data and

tissue registries have recently gained acceptance as an alterna-

tive to RCTs, allowing careful monitoring of clinical outcome

in relation to the genomic test results10. Such surrogate trials

involving retrospective evaluation of randomized, prospect-

ively collected cohorts may allow conditional approval of new

genomic applications, provided that the selection criteria for the

data set conform to the disease of interest.

The use of DNA testing to identify high-penetrance

mutations causing monogenic disorders is well-evidenced.

Thousands of susceptibility variants identified by genome-

wide association studies (GWAS) are also implicated as

potential risk modifiers in both monogenic and complex

disease traits. While of limited or no value in risk prediction

when used in isolation, there is growing recognition of the

clinical usefulness for actionable functional gene variants

underlying key metabolic pathways across diagnostic bound-

aries8,11,12. In this context, sophisticated bioinformatics tools

are increasingly applied to identify clinically relevant genes

acting on the same biological pathway13. The discovery of

novel high impact rare variants and copy number repeats

facilitated by next generation whole exome sequencing

(WES) and whole genome sequencing (WGS) lends further

support to the notion that sporadic polygenic NCDs are in

many respects more similar to Mendelian disorders than

previously anticipated14,15. An arbitrary distinction between

the role of causative mutations in monogenic disorders versus

rare variants and single nucleotide polymorphisms (SNPs) in

polygenic diseases therefore seems superficial and belies the

underlying genetic complexity characteristic of disease

pathogenesis in general16. Recognition of this genetic intri-

cacy highlighted the need to define an optimal strategy by

which a convergent pathogenic model, incorporating clinic-

ally relevant genomic knowledge generated at the DNA, RNA

and/or protein levels, may be integrated into public health

research, policy and practice17.

In this review, we describe the development of the clinically

integrative PSGT approach to genomics-based NCD risk

assessment and management as an enabler of research

translation. The need for standardized referral guidelines and

eligibility criteria for genetic testing is first discussed in the

context of breast cancer genomics as a health discipline where

this requirement has been recognized and successfully

addressed. We consider the example of how assessment of

the underlying tumor pathology prompted re-evaluation of

existing guidelines for BRCA mutation analysis (germline

susceptibility testing) and gene expression profiling (tumor

pathology) for chemotherapy selection beyond the limited

scope of identifying monogenic breast cancer subtypes.

Establishment of a database resource provided the foundation

for development of test selection criteria for genomics-based

NCD risk management programs, focused on shared disease

pathways across seemingly unrelated illnesses. Insights gained

as a result are guiding the development of optimal strategies,

whereby PSGT itself could be positioned as a pre-screening

tool to facilitate selection of patients eligible for next-

generation sequencing. Combination of these technologies

may facilitate genome-wide studies in search of susceptibility

alleles for cardio-metabolic risk, as well as the identification of

genetic drivers within cancer genomes. Our initial focus on the

exome is justified by cost efficiencies, as the coding sequence

and intron-exon splice junctions are currently the most

informative regions of the genome for clinical application.

Moreover, the research component linked to the PSGT service

provides a valuable platform for validation of new genomic

applications against current standards, given the critical

importance for ongoing comparison with non-sequenced

based techniques, including bioinformatics tools increasingly

applied in clinical care.

Pathology-supported genetic testing across thedisease spectrum

Insight gained from extensive genetic research performed in

the diverse South African population led to development of

the PSGT concept, whereby pathology test results are

combined with genetic testing in an attempt to identify a

genetic component to the disease phenotype, while at the

same time providing information on relevant future risk

implications. This clinically integrated model applied as part

of a combined open-innovation research and service delivery

DOI: 10.3109/10408363.2014.997930 Genomic medicine and risk prediction across the disease spectrum 3

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platform, is positioned as a solution to the inherent limitations

of direct-to-consumer (DTC) genetic testing8. DTC genetic

testing is based on an incomplete view of the lifetime risk for

common complex diseases, as this model does not include

simultaneous evaluation of the personal and family medical

history relevant to the tests performed. PSGT involves a

biological pathway systems approach to clinically orientated

genomics as a means of guiding patient management within

the context of underlying pathology as vantage point, as

illustrated in Figure 1.

PSGT uses a multidisciplinary framework for the interpret-

ation of genetic information with the goal of identifying

treatable NCD subtypes requiring a more active approach to

therapeutic management. A top-down (phenotype-to-geno-

type) and bottom-up (genotype-to-phenotype) approach can be

applied simultaneously for consideration of patient data

obtained from diverse fields of healthcare linked via the

common thread of pathology. PSGT aims to empower the

clinician with genomic information that can be used to

facilitate (1) the diagnosis of monogenic/treatable disease

subtypes, (2) lowering of cumulative risk for disease progres-

sion or the development of co-morbidities and (3) formulation

of individualized treatment strategies tailored to the needs of

the individual. Moreover, the development of tailored

pharmacogenomic algorithms aimed at predicting treatment

failure and limiting exposure to serious drug side-effects may

ultimately serve to improve treatment compliance. A clinically

guided genomics-based approach to NCD risk assessment may

therefore address current as well as future risk, with the

ultimate goal of optimizing health and patient management

throughout the course of an individual’s lifespan8.

Rooted in extensive research performed in South Africa

concerning genetic underpinnings of both monogenic and

polygenic diseases, PSGT aims to facilitate evaluation of risk

factors and choice of intervention strategy in patients with

etiologically complex multifactorial disorders. Application of

this dynamic healthcare model was first described using

biochemical abnormalities as the vantage point to facilitate

improved risk management in genetically pre-disposed

patients with abnormal iron status18 or high cholesterol

levels19. Detection of a genetic contribution to iron overload

enables confirmation of a diagnosis of hereditary hemo-

chromatosis (HH) without the need for an invasive liver biopsy,

while accurate diagnosis of familial hypercholesterolemia

(FH) is required to determine the appropriateness of long-term

use of cholesterol-lowering medication in dyslipidemic

patients. Identification of founder mutations underlying the

high prevalence of these conditions in high-risk population

groups led to development of cost-effective single-gene tests

that may also be applied as part of multiplex genomic

applications targeting critical disease pathways of relevance

to a wide spectrum of chronic NCDs8. While the clinical utility

of single-gene testing for the spectrum of mutations defined as

causative in a high-risk population group is well-established,

evaluation of multiple low-penetrance mutations/SNPs found

to be of relevance across diagnostic boundaries is complicated

by uncertainty related to selection criteria and interpretation of

the results for clinical application. PSGT aims to overcome

these limitations and may also serve as a screening step for

selection of patients eligible for WES/WGS20. This approach is

similar to the strategy used routinely to identify patients with a

family history and/or clinical features suggestive of familial

breast cancer for full gene BRCA screening (Table 1),

following the exclusion of known causative mutations under-

lying the majority of affected cases due to a founder effect21. In

genetically uncharacterized patients where a particular disease

pattern or therapeutic intolerance/failure is not adequately

accounted for, extension from PSGT to WES/WGS could

further be considered for the identification of rare or novel

causative mutations or pathogenic pathways not covered as

Figure 1. Outline of pathology-supported genetic testing (PSGT) utilizing an open-innovation platform linking service delivery to the generation of aresearch database in order to facilitate targeted treatment as well as identify genetically uncharacterized patients eligible for extended further testing.

4 M. J. Kotze et al. Crit Rev Clin Lab Sci, Early Online: 1–18

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Table 1. Application of pathology-supported genetic testing (PSGT) in breast cancer risk management.

Process Evaluation Important considerations prior to genetic testing

Document clinical risk profile,relevant pathology data andfamily history in the context ofgenetic counseling support

Personal risk Early age at diagnosis (540 years).Presence of bilateral breast cancer and/or ovarian cancer.

Ancestral risk A limited number of founder mutations may account for thedisease in the majority of affected patients in high-riskpopulations (e.g. Ashkenazi Jewish, Afrikaners).

Familial risk Breast/ovarian cancer runs in the family from one generation tothe next.

In addition, other cancers including colon, prostate and malebreast cancer are important indicators especially if at leastfour close relatives younger than 60 years are affected, threebelow 50 years or two below 60 years and ovarian cancer inthe family.

Histopathology Triple-negative breast cancer (ER-, PR-, HER2-negative) andpatients with basal-like subtype are at increased risk to carrya BRCA1 mutation.

Receptor status important for referral of patients for tran-scriptional profiling used in anti-HER2 treatment andselection of chemotherapy23.

Treatment failure/side-effects Use of certain antidepressants may influence Tamoxifenresponse due to reduced CYP2D6 activity, found to be ofparticular concern in BRCA mutation carriers.

CYP2D6 metabolizes about 25% of commonly used prescrip-tion drugs and is therefore of relevance in a wide range ofclinical domains.

Define BRCA1/2 testing approach First screen an affected family member toidentify the causative mutation

Determine high familial risk for recurrence or bilateral breastcancer and increased risk of ovarian/other cancer in thecontext of treatment options.

Screen close relatives for known familymutation to exclude or confirm thefamilial risk

Determine risk to inherit a BRCA mutation and based on theoutcome the likelihood to develop cancer over the lifetimein the context of treatment options.

Pre-test genetic counseling Value of the test in a family memberwithout cancer

A positive test would indicate a very high risk for cancer thatrequires intensified surveillance or prophylactic surgerywith proven efficacy.

A negative test for the family mutation reduces the familial riskto that in the general population.

Value of the test in a patient alreadydiagnosed with cancer

A positive test indicates a high risk for recurrence/bilateralbreast cancer or ovarian cancer.

A negative test result for the family mutation means the cancerwas caused by other risk factors not tested for (extendedmutation screening may be recommended based on overallrisk profile).

Risk to offspring A 50% chance with each pregnancy to pass on the faulty BRCAgene (mutation-positive individuals).

No further risk implications for children when the causativefamily mutation was excluded.

Decide when to test Above the age of 18 years Women who need to have a bilateral oophorectomy usuallyprefer to know their risk before the operation.

Women who consider breast surgery may use the informationon BRCA mutation status as motivation for a bilateralmastectomy.

Allows family planning and adequate screening to be timedbetween pregnancies.

Decision about timing of risk reduction surgery based ongenetic risk and expression of disease occurring earlier insubsequent generations.

Choose BRCA test option Mutation-specific Screen at-risk family members for a known mutation previ-ously identified in the index patient diagnosed with breast/ovarian cancer.

Population-specific Screen for a limited number of mutations occurring at anincreased frequency in cancer patients from certain popu-lation groups (e.g. Ashkenazi Jews, Afrikaners of Europeandescent).

Full gene screen Screen for the cancer-causing mutation in breast cancerpatients who tested negative during the initial screen forfamily/population-specific mutations or when these two testoptions are not indicated.

Provide option for research par-ticipation centered around thestorage, decoding or destroying

CYP2D6 pharmacogenomics testing aspart of a chronic disease screeningprogram aimed at lowering of cumu-lative risk in breast cancer survivors42

Ongoing studies enable the research team to improve the testsand interpretation of results as new discoveries and action-able information become available in the scientificliterature.

(continued )

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part of the PSGT pre-screen framework. In order to prepare for

such change, it is important to note that the need for genetic

counseling will increase exponentially as WES/WGS becomes

a viable alternative to targeted sequencing in genetically

uncharacterized patients.

Determining eligibility for oncogenomic testing

Breast cancer oncogenomics is currently leading the way in

translating genetic discoveries into actionable clinical bene-

fits22. Since the role of genetic risk factors underlying

different subtypes of breast cancer is well-evidenced and

testing options have become part of clinical reality, research

efforts have been actively pursuing cost-effective strategies to

identify South African breast cancer patients who may benefit

from DNA-based testing and/or RNA-based gene profiling for

targeted treatment21,23. Development of selection criteria for

the increasing number of genomic applications was recog-

nized as an important research area to identify where

additional information, if any, provided by a genomic test

could fit into the context of current clinicopathological

prognostication of breast cancer.

Standardized selection criteria have been developed for

inclusion of patients in familial breast cancer screening

programs based on the high lifetime risk (40–85%) associated

with the BRCA1 and BRCA2 tumor suppressor genes24. BRCA

mutations only account for 30–40% of familial disease

clustering and less than 5% of total cases overall25,26.

Causative mutations therefore remain undetected in the

majority of affected families with currently used screening

methods, while detection of BRCA1/2 sequence variants of

unclear pathogenic significance constitutes an increasing

clinical challenge. RNA profiling has therefore become an

attractive option to determine functionality of gene variants

identified, and at the same time select patients sensitive to new

therapeutics focused on the genetic defect identified27. Global

RNA profiling and promoter methylation analysis performed

on 70 breast tumor biopsies also revealed the involvement of

hereditary factors in non-BRCA1/2 breast cancer families28.

The finding that family members may carry genetic suscep-

tibility not only to breast cancer but also to a particular subtype

of breast cancer implies that RNA profiling can be used to

identify functional subgroups within breast tumors, particu-

larly in families that tested negative for BRCA1/2 germline

mutations. In this context, genetic variation underlying

dysfunction of the folate-homocysteine methylation pathway

was shown to predict both the subtype of breast cancer and

disease progression29. HER2-enriched and basal-like subtypes

were positively associated with familial breast cancer and

inversely associated with plasma folate. The clinical relevance

of an extensively studied multi-functional SNP in the methy-

lene-tetrahydrofolate reductase (MTHFR) gene (rs1801133,

677 C4T) was supported by strong association with the

Luminal B subtype. The Luminal A subtype was associated

with lack of family history of breast cancer, late age of onset

and higher body mass index (BMI). A growing body of

evidence supported by WES suggests that rare variants and co-

inheritance of multiple low-penetrance mutations may explain

the majority of familial disease clustering not attributable to

BRCA1/2 mutations30. Functional polymorphisms in genes

coding for drug-metabolizing enzymes31 or those dependent

on vitamin co-factors for optimal activity32,33 may explain the

variable clinical expression and differences in treatment

response, drug toxicity and/or recurrence risk in patients

with the same diagnosis. Variation in the MTHFR and

Cytochrome P450, family 2, subfamily D, polypeptide 6

(CYP2D6) genes are considered of particular importance in

this context across diagnostic boundaries, due to their role in

gene–diet (nutrigenomics) and gene–drug (pharmacogenom-

ics) interactions. Appropriate clinical application related to

these aspects will depend on whether the patient is at risk or has

already been diagnosed with cancer and therefore correct

interpretation of genomic information facilitated by the PSGT

approach is a critical step in patient care.

It is now appreciated that, rather than constituting a single

clinical diagnosis, breast cancer defines a broad spectrum of

pathology accounting for significant inter-patient heterogen-

eity in presentation, prognosis and treatment outcomes34.

More accurate determination of breast cancer recurrence risk

based on the underlying tumor biology has become possible

with use of microarray analysis that enables disease classi-

fication into at least four intrinsic molecular subtypes35.

BRCA1 mutations were found to be more common in patients

with triple-negative breast cancer (TNBC) that lacks expres-

sion of estrogen receptor (ER), progesterone receptor (PR)

and HER236,37. Different breast cancer subtypes defined

partly by these three biomarkers furthermore showed variable

patterns of association with NCD’s, as indicated by the

relationship between TNBC and the metabolic syndrome38,39.

The metabolic syndrome, characterized by central obesity,

hypertension, dyslipidemia and impaired glucose tolerance, is

considered an important unifying risk factor of shared disease

Table 1. Continued

Process Evaluation Important considerations prior to genetic testing

of specimens used for routinegenetic testinga

This approach is of particular relevance for WES/WGS in non-responders/patients with severe drug side effects or genet-ically uncharacterized familial/early-onset cases20.

Clinical application Provide a comprehensive report based ondata integration

Report contains genetic information related to the clinicalcondition and/or family history.

Interpretation is focused on actionable genetic alterationsvalidated in the laboratory.

Genetic counseling and/or further expert clinical consultationmay be recommended based on the test outcome.

aRoutine genetic testing service delivery linked to the generation of a research database and biobank for improved quality assurance and validation ofnew tests against current standards.

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pathways implicated in a wide spectrum of NCDs. The role of

epigenetics in dysfunction of the methylation pathway

discussed above is well-established and may also cause

silencing of the BRCA1 gene in sporadic breast cancer40.

Recent findings that BRCA1 and BRCA2 mutations are more

common in patient subgroups with sporadic breast cancer

than previously anticipated have important implications for

genetic testing41. Variation in the CYP2D6 gene associated

with variability in treatment response was found to be of

particular relevance in BRCA mutation carriers, especially

when concomitantly treated with antidepressants that may

affect enzyme function31. CYP2D6 genotyping is therefore

considered appropriate in South African breast cancer

patients who are receiving Tamoxifen treatment and are at

high recurrence risk due to inheritance of a defective BRCA

gene in the family and/or when using potential competing

antidepressants42. Van der Merwe et al.42 proposed that the

same path used for development and implementation of

genetic tests for high-penetrance mutations such as those in

the BRCA1/2 genes, should also apply to variants with

reduced penetrance, with the exception that known environ-

mental triggers documented as part of the PSGT approach

should also be taken into account for clinical application.

The above-mentioned findings collectively highlight the

role of genetic variation not only in familial, but also in

sporadic breast cancer cases and recurrence risk. Use of

specific test selection criteria is aimed at a high probability for

detection of causative mutations in the index case and pre-

symptomatic diagnosis in at-risk family members, based on the

age of onset and a strong family history of breast, ovarian and

other relevant cancer types previously shown to be associated

with the BRCA1/2 genes. Since founder-related mutations in

the BRCA1 and BRCA2 genes account for the majority of cases

of monogenic breast cancer in the South African population

and other high-risk groups such as the Ashkenazi-Jewish

population, an individual’s ancestral origin is also an important

criterion in determining eligibility for high-penetrance BRCA

mutation screening21,43,44. Test options include DNA-based

BRCA mutation analysis for diagnosis of familial breast cancer

using (1) family-, or (2) population-specific mutation detection

methods, or (3) full gene screening of BRCA1 and BRCA2.

Selection of any of these three test options during pre-test

genetic counseling is based on previous identification of the

causative mutation in an affected family member or population

risk due to a founder effect, whereby a limited number of

common causative mutations generally accounts for the

disease in the majority of affected patients21.

In addition to consideration of the above-mentioned factors

focused primarily on selection of breast cancer patients for

BRCA mutation screening, tumor morphology and receptor

status are increasingly assessed to determine eligibility for

gene expression profiling. Microarray analysis represents a

higher level of investigative complexity and use of the PSGT

approach was essential for successful introduction of breast

cancer gene profiling in clinical practice, as evidenced by

reimbursement of the 70-gene MammaPrint profile as part of

oncology benefits by several medical schemes in South

Africa23. Unlike BRCA gene testing, the MammaPrint test

does not provide information about the risk for inheritance of

cancer in the family, but whether a patient with early stage

breast cancer may benefit from chemotherapy or not. The

prognostic and predictive value of this microarray test was

confirmed in both the adjuvant and neo-adjuvant set-

tings35,45,46, as further supported by prospective 5-year

follow-up data47. Despite the lack of supporting data from a

RCT, this level of evidence was considered sufficient to allow

conditional approval for routine clinical use of MammaPrint

in South Africa23. An important requirement was that a

central database be established for (1) evaluation of pre-

defined referral guidelines outside a controlled research

environment, (2) evaluation of the performance of microarray

technology against the gold standard for improved quality

assurance and (3) to determine the impact on clinical decision

making and clinical outcome. As discussed below, these

aspects were adequately addressed and led to successful

introduction of advanced microarray-based breast cancer gene

profiling into the South African healthcare system.

Utilization of a genomics database resource forcomparative effectiveness studies

The favorable impact of the 70-gene MammaPrint profile on

long-term clinical outcome48 supports the value of patient

registries, allowing for the evaluation of prospective follow-up

data in comparative effectiveness studies as a viable alternative

to RCTs10. Advanced microarray technology has proven to be

highly accurate in facilitating risk stratification and guiding not

only chemotherapy selection in resource-limited settings23, but

also HER2-targeted treatment based on patient re-classifica-

tion following reflex testing49. This implementation, facilitated

by utilization of the central research database, substantiated the

clinical usefulness of the MammaPrint Pre-screen Algorithm

(MPA), validated as an appropriate strategy to prevent

chemotherapy overtreatment in South African patients with

early-stage breast cancer22. Risk assessment is provided over

and above ER, PR and HER2 status (routinely performed in all

breast cancer patients using IHC/FISH) as a separate read-out

(Targetprint) of the versatile MammaPrint microarray plat-

form. From 2011, molecular subtyping into Luminal A,

Luminal B, basal-like and HER2-enriched subtypes based on

receptor pathway activity (BluePrint) was also added to the

MammaPrint service.

Given the concerns over the accuracy of standard tech-

niques used for determination of HER2 status in breast cancer

patients50,51, incorporation of RNA-based microarray analysis

may facilitate clinical care by resolving borderline cases and

providing a second opinion on standard protein- and DNA-

based HER2 testing. While the accuracy of reverse tran-

scriptase polymerase chain reaction (RT-PCR) has previously

been questioned for determination of HER2 status52–54, the

TargetPrint results obtained in 138 tumor specimens of South

African breast cancer patients showed 100% concordance

between microarray-based and IHC/FISH results upon reflex

testing in discordant cases49. Repeat IHC/FISH testing

confirmed the accuracy of TargetPrint for determination of

HER2 status, irrespective of whether fresh or FFPE tumor

specimens were used. FFPE tumor specimens were found to

be a reliable source of RNA for microarray analysis of HER2

status, analytically validated in South African breast cancer

patients using TargetPrint49.

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In contrast to centralized HER2 testing utilized in large

international breast cancer trials, most tests used in clinical

practice in South Africa are performed by different local

laboratories. They all employ international quality control

programs, but this does not necessarily equate to 100%

accuracy in the day to day reports used in clinical decision

making. Use of a central research database proved invaluable

to address practical clinical issues experienced by clinicians

and demonstrated that, in patients undergoing MammaPrint

genomic profiling, TargetPrint provides a reliable ancillary

method of assessing HER2 status in conjunction with IHC/

FISH. Furthermore, addition of the 80-gene BluePrint profile

as a separate read-out from the MammaPrint microarray

platform allows prediction of therapeutic outcomes based on

the identification of functional pathways implicated in

carcinogenesis and neoplastic transformation, independent

of hormone and HER2 receptor status35. Microarray-based

breast cancer gene profiling provides information not avail-

able through standard histopathology and enables quantifica-

tion of discordant/equivocal cases for appropriate

interpretation of results obtained at the DNA, RNA and

protein levels.

The significant impact of the 70-gene MammaPrint test on

treatment decisions in South African breast cancer patients

has recently been confirmed by Pohl et al.55 in an external

audit of the central genomics database. Although only those

patients expected to gain little benefit from additional

chemotherapy were selected for this audit, while still

having the option of endocrine therapy, gene profiling

could potentially change the treatment of one in two (52%)

patients irrespective of 10-year mortality based on clinical

risk assessment using the Adjuvant! Online (AOL) tool.

Mortality figures determined by AOL relates to statistical

comparison between groups and do not reflect the specific

risk for an individual patient. Genomic profiling determines

the programming or behavior of the tumor relative to a cut-

off point between low and high risk for metastases, regardless

of external morphology. Therefore, when a patient is

classified as high risk using MammaPrint, the AOL risk

becomes obsolete. In the prospective MicroarRAy

ProgniSTics in Breast CancER (RASTER) trial, a 5-year

distant recurrence-free interval of 100% was reported in

MammaPrint low-risk patients who did not receive adjuvant

chemotherapy, despite the presence of ‘‘high-risk’’ clinico-

pathological factors47. The risk of distant recurrence is

approximately 30% in patients with a high-risk MammaPrint

profile, while low risk patients have a 10% risk of recurrence

within 10 years. This translates into a three times higher risk

of dying in high risk versus low risk patients. When

chemotherapy is added there would be no significant

reduction in cancer deaths in the MammaPrint low-risk

patients, while the high risk group would benefit from

approximately 25% risk reduction47.

Establishment of a central genomics database also allowed

the identification of patients referred for a specific genetic

service who might be at risk of other hereditary or chronic

NCDs56. Accordingly, some of the patients referred for

microarray analysis of their breast tumors participated in the

chronic disease screening program and/or were tested for

germline mutations in the BRCA1 and BRCA2 genes based on

their clinical profile and familial risk. Preliminary data

obtained from comparative studies suggest an association

between BRCA1- and BRCA2-positive breast cancer and a

high-risk MammaPrint profile, independent of ER status.

Although pre-selection using the MPA23 in the majority of

patients tested may partly account for this finding, it is

important to note that tumors in BRCA1 positive patients are

more frequently triple-negative in comparison to tumors in

BRCA2 carriers. This supports previous findings showing that

having a first-degree family history of breast cancer is

associated with an increased risk of TNBC57. Furthermore,

increased incidences in TNBC and obesity may be related to

shared disease mechanisms associated with the components of

the metabolic syndrome38,39. Cumulative risk due to clustering

of metabolic syndrome features including central obesity,

hypertension, dyslipidemia and/or glucose intolerance in the

same patient, may lead to development of cardiovascular

disease (CVD) found to exceed the risk of breast cancer

recurrence at 10 years in breast cancer survivors58.

Thrombophilia or cardiotoxicity induced by some of the

therapeutic options for breast cancer is also a major concern

and warrants the development of pharmacogenomic treatment

algorithms aimed at prevention of drug failure and side effects.

Modifiable environmental risk factors including alcohol con-

sumption, smoking and obesity, shown to have a significant

effect on the recurrence rate of breast cancer59, should also be

taken into account in relation to the impact of genetic variation

in a high-risk environment.

BRCA mutations have been linked to an increased risk of

various types of cancer including risk for development of lung

cancer, found to at least double in smokers with the BRCA2

rs13314271 variant due to a combined effect60. An interaction

between the presence of BRCA mutations and diet diversity in

relation to fruit and vegetable intake has also been reported61.

These findings support the implementation of preventative

and therapeutic strategies based on our understanding of the

mechanisms through which genetic and environmental factors

contribute to cancer development, progression and recurrence

risk. For application of personalized medicine to be clinically

meaningful, genomic information needs to be considered

together with clinical and environmental influences. This

aspect is addressed by ongoing collection of clinical, path-

ology, lifestyle and genetic information in the PSGT research

database, substantiated by the need for monitoring of breast

cancer patients at risk of both physical and psychological

complications56.

The metabolic syndrome as a unifying risk factorfor common NCDs

Obesity and associated conditions such as dyslipidemia,

hypertension and type II diabetes are responsible for many

preventable diseases and premature death. The use of a

genomics-based approach targeting common disease mech-

anisms across the diagnostic spectrum may therefore be best

exemplified by considering the constellation of cardio-meta-

bolic risk factors (collectively termed the metabolic syn-

drome) as a unifying pathogenic model accounting for the

development or progression of multiple NCDs (Table 2), in

addition to breast cancer as discussed above.

8 M. J. Kotze et al. Crit Rev Clin Lab Sci, Early Online: 1–18

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The PSGT research database has proven to be an

invaluable resource for validation of novel and previously

described gene-disease associations replicated in the South

African population for a broad range of clinically related

NCDs associated with cardio-metabolic risk factors and

features of the metabolic syndrome77–80. The significant

positive association observed between BMI and homocysteine

levels, correlating with low folate intake in the diet,

confirmed the deleterious effect of a genetic disturbance in

the methylation pathway in patients with multiple sclerosis

(MS) and depression77,78. The effect of environmental factors

known to influence BMI and homocysteine were evaluated in

these studies not only as potential confounders that need to be

adjusted for during statistical analysis, but also as potential

modifiable contributors to the disease process that may in turn

be useful to mitigate the gene effect. In MS patients, smoking

was associated with disease progression, while daily intake of

at least five fruits and vegetables correlated with a favorable

MS disability score as measured by the Expanded Disability

Status Scale (EDSS)77. Furthermore, a recent ultrasonography

study investigating vascular risk factors in South African MS

patients, found a highly significant correlation between intima

media thickness (ITM – a surrogate marker for CVD) and

disability in MS based on the EDSS81. Evidence that vascular

risk may be modified by lifestyle factors in a way that

counteracts the effect on MS progression warrants a pro-

spective implementation study to determine whether lifestyle

intervention, possibly guided from the genetic background,

will result in improved clinical outcome.

The shared bidirectional pathogenic relationship between

the metabolic syndrome and neuropsychiatric illnesses

including major depressive disorder (MDD)65 provides the

rationale for routine evaluation of overall cardio-metabolic

risk in all patients diagnosed with MDD. Evidence that

elevated homocysteine levels in 86 MDD South Africans

studied by Delport et al.78 may be mediated by a combined

effect of the MTHFR 677C4T mutation and low folate intake

on BMI, prompted extended assessment of MDD patients for

presence of the metabolic syndrome. In this pilot, the majority

of MDD patients were obese (BMI 430 kg/m2) and waist

circumference measured in these patients confirmed cen-

tral obesity as a defining characteristic of the metabolic

syndrome (Figure 2). A 14.6% increase in BMI was noted for

each additional feature of the metabolic syndrome present in

the study cohort, for fixed age and gender (Figure 3). As

previously described in South African patients at risk of

CVD82, the metabolic syndrome was defined by the presence

of three or more of the following features: central obesity

characterized by waist circumference 4102 cm in males and

488 cm in females, blood pressure �130/85 mmHg, fasting

glucose �5.6 mmol/L, HDL-cholesterol 51.0 mmol/L in

males and 51.3 mmol/L in females and triglyceride levels

�1.7 mmol/L. While alcohol intake was not associated with

an increasing number of metabolic syndrome components

identified (p¼ 0.460), a significant negative association was

found with physical activity (p¼ 0.006). This finding reflects

the importance of exercise to reduce the disease risk

associated with the metabolic syndrome.

A multitude of varied factors have been proposed to

explain the co-existence of MDD and the metabolic syn-

drome, including unhealthy diet and lifestyle habits, poor

general access to healthcare, hypothalamic shift and the side-

effects of medications such as tricyclic antidepressants and

atypical antipsychotics, which can cause weight gain and

Table 2. Non-communicable diseases in addition to cancer in which the metabolic syndrome is considered major driver ofdisease development or progression.

Disease category Comorbidity References

Pulmonary disorders Chronic obstructive pulmonary disease 62

Endocrine disorders Polycystic ovary syndrome (women) 63

Erectile dysfunction (men) 64

Neuropsychiatric disorders Major depressive disorder 65

Schizophrenia 66

Bipolar disorder 67

Mild cognitive impairment 68

Alzheimer’s disease 69

Multiple sclerosis 70

Gastrointestinal and hepatic disorders Complicated gallstone disease 71

Non-alcoholic fatty liver disease 72

Musculoskeletal and rheumatologic disorders Osteoarthritis 73

Gout 74

Nephrological disorders Nephrolithiasis 75

Miscellaneous Obstructive sleep apnea 76

Figure 2. Bar graph illustrating the prevalence of metabolic syndromefeatures in South African patients diagnosed with major depressivedisorder. Dyslipidemia was defined as the presence of either hyper-triglyceridemia or hypoalphalipoproteinemia or both.

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unfavorable metabolic changes83. Emotional stress disrupts

the integrity of the hypothalamic–pituitary–adrenal axis and

increases the production of cortisol, noradrenaline and

cytokines, considered of particular relevance in South

African patients with a genetic predisposition for early onset

MDD.79 Since the diagnosis of a life-threatening disease such

as breast cancer may also increase the risk of depression in

South African patients42, assessment of BMI as a useful

correlate of central obesity represents an important clinical

indicator for participation in the chronic disease screening

program.

Genetics of dyslipidemia in relation to chronicdisease risk management

Each component of the metabolic syndrome is regulated by

both genetic and acquired factors resulting in variable

phenotypic expression. A genotype-only approach to NCD

risk management therefore profoundly limits the capacity for

the clinical translation of genomic research. Testing for well-

evidenced and clinically actionable functional variants such as

the apolipoprotein E (APOE) polymorphism included in the

CVD multi-gene assay developed in South Africa19,84 are

considered relevant to identify environmental and epistatic

drivers of clinical expression in complex disease traits.

Comprehensive patient assessment considering diverse med-

ical, biochemical, genetic and lifestyle data is used to develop

tailored intervention strategies guided partly from a genetic

background to decrease cumulative NCD risk in genetically

susceptible individuals8.

The majority of South African patients who present

biochemically with type III dysbetalipoproteinemia are

homozygous for the epsilon-2 allele ("-2) of APOE85. The

deleterious effect of this allele is triggered by a second hit

such as obesity, diabetes and hypothyroidism. This is in

accordance with an increasing number of metabolic syndrome

features found to be associated with the APOE "-2 allele in

South African patients at risk of CVD82. In this context, it is

important to note that hepatic manifestation of the metabolic

syndrome, termed the non-alcoholic fatty liver disease

(NAFLD), is characterized by increased intra-hepatocellular

accumulation of triglycerides in excess of 5% of liver mass72.

Several studies have shown that serum triglycerides, total and

LDL cholesterol levels are increased, and HDL cholesterol

levels decreased, in NAFLD patients. Similar but more severe

derangements in lipid profiles are observed in patients with

progressive hepatic necro-inflammation, which defines the

more aggressive inflammatory steatohepatitis (NASH) pheno-

type86,87. A high-fat, Western-style diet appears to unmask the

association between APOE "-2 and impaired lipid homeosta-

sis, which could promote progression to NASH88.

The aforementioned genotype–phenotype associations

require careful consideration in the context of the metabolic

syndrome and/or NAFLD, given the possibility of coexisting

FH, due to an increased prevalence of this severe form of

dyslipidemia in South Africa as a consequence of a founder

effect19,84. Confirming a suspected diagnosis of FH has

profound implications for the clinical management of patients

and at-risk family members, as it necessitates early initiation

of long-term lipid-lowering pharmacotherapy to effectively

reduce risk for adverse cardiac events as well as cognitive

decline89. In comparison, APOE "-4 allele carriers without

FH may not only be less responsive to both lipid-lowering

statins and medications commonly used in the treatment of

dementia90,91, but also more susceptible to deleterious dietary

and lifestyle habits associated with greater cumulative risk for

CVD and dementia92. In an investigation of the role of APOE

"-4 as a genetic risk factor for dyslipidemia in South Africans

with and without FH, Kotze et al.93 found that the APOE "-4allele was associated with hypercholesterolemia in the

unaffected control group, while an additive effect on the

lipid profiles was not apparent in patients with FH. This

finding and underrepresentation of the APOE "-4 allele in

genetically characterized FH patients studied, suggested that

the genetic effect of this variant is masked or overridden by

the known causative FH mutation.

APOE "-4 is also a well-established genetic risk factor for

late-onset Alzheimer’s disease and a major determinant of

inter-patient heterogeneity, which influences nearly every

pathogenic domain affected in this condition94. Its hypercho-

lesterolemic effects promote accelerated atherogenesis impli-

cated not only in ischemic cerebrovascular disease associated

with Alzheimer’s disease as well as vascular dementia, but also

microvascular dysfunction underlying white matter pathology

observed in subcortical dementias and certain Alzheimer’s

disease subtypes95. This raised the possibility that having a

family history of Alzheimer’s disease may potentiate cumula-

tive risk associated with phenotypic expression of the APOE

"-4 allele in an additive or synergistic manner. In order to

determine whether expression of the known dyslipidemic

effects attributable to polymorphic variation in the APOE gene

are modified by a family history of Alzheimer’s disease, data

from more than 500 South African individuals participating in

the genomics-based chronic disease screening program were

evaluated, based on the presence or absence of a known family

Figure 3. Boxplot illustrating an estimated 14.6% increase on averagein BMI after adjustment for age and sex, per feature of themetabolic syndrome, present in patients diagnosed with major depressivedisorder. The metabolic syndrome was defined by the presence of threeor more of the following features: central obesity characterized by waistcircumference4102 cm in males and488 cm in females, blood pressure�130/85 mmHg, fasting glucose �5.6 mmol/L, HDL-cholesterol51.0 mmol/L in males and 51.3 mmol/L in females and triglyceridelevels �1.7 mmol/L.

10 M. J. Kotze et al. Crit Rev Clin Lab Sci, Early Online: 1–18

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history of Alzheimer’s disease. In this study80, we showed that

both the clinical expression of a hypercholesterolemic pheno-

type in APOE "-4 allele carriers and its apparent mitigation by

regular physical activity, were dependent on the interaction

between APOE genotype and Alzheimer’s disease family

history. Knowing that action can be taken to modify a genetic

risk factor is valuable, particularly in diseases where no

effective medical treatment is available.

Selection criteria for personalized genomic testing used to

diagnose or screen for FH are already in place in South Africa

based on existing diagnostic algorithms, which include clinical

factors such as xanthomas, early onset vascular complications

or a strong family history of early-onset coronary heart disease

as major determinants of testing eligibility96. While APOE

genotyping is generally performed to increase diagnostic

accuracy for AD in symptomatic patients who present atyp-

ically97, our findings support a novel clinical application for

APOE genotyping as a means of identifying a high-risk

subgroup of asymptomatic hypercholesterolemics80 set to

derive optimal benefit from timely implementation of tailored

lifestyle-centered intervention strategies aimed at decreasing

current CVD risk as well as reducing the risk for Alzheimer’s

disease later in life19. In addition, the clinical importance of

inquiry concerning family history in determining eligibility for

personalized genotyping used to inform therapeutic decision

making is supported beyond its current limited role in

diagnosing or screening for Mendelian disorders such as FH.

Furthermore, in a recent alcohol cross-over intervention

study98, we showed that an expected increase in beneficial

HDL cholesterol as previously demonstrated by Djousse

et al.99, was less pronounced in APOE "-4 allele carriers.

Alcohol consumption is known to potentiate the association

between APOE "-4 and elevated LDL cholesterol100. In the

alcohol intervention study performed in South Africa, the low-

penetrance HFE C282Y and H63D mutations underlying the

most common autosomal recessive form of HH, were also

shown to mediate the association between alcohol consump-

tion and dyslipidemia. A significant increase in triglycerides

observed only in study participants who tested positive for

HFE gene variations may provide an explanation for the effect

of alcohol on elevation of the levels of this form of fat stored as

energy in the body98.

In dyslipidemics, including FH patients, using cholesterol-

lowering medication, side-effects such as muscle pain,

myalgia, and decreased efficacy of pharmacological agents

in Alzheimer’s disease patients could possibly be explained

by variation in the APOE and CYP2D6 genes101,102.

Genotyping of CYP2D6, found to metabolize approximately

25% of commonly prescribed drugs, is also clinically useful in

South African breast cancer patients studied in the context of

both anti-cancer and anti-depressant medication use42. As the

use of genetics for discovery of drug targets or improved

treatment strategies increases for both rare monogenic

disorders and complex diseases, the use of appropriate

statistical tools becomes more and more important to prove

the benefit of a pharmacogenomics solution. Massive devi-

ation from the Hardy–Weinberg equilibrium in the Breast

International Group (BIG) I-98 CYP2D6 study recently

revealed genotyping errors103 that led to a request for

retraction of the relevant paper from the scientific literature

due to the inaccurate data published. This is justified by the

fact that the results of the BIG-I-98 CYP2D6 study caused a

delay in resolution of a clinical management question that

affects two-thirds of breast cancer patients worldwide and

could have led to termination of research into CYP2D6 as a

promising biomarker applicable in many clinical domains.

The problem of genotyping errors can also be overcome by

checking for pedigree inconsistencies in family studies, but in

population studies and GWAS generating large numbers of

genotypes, extra caution is required to ensure accurate results.

From genome-wide association studies to nextgeneration clinical sequencing

GWAS identified a large number of genetic variants involved

in disease susceptibility and drug response, but translation

into clinical practice is slow due to lack of proven clinical

utility for the majority of SNPs. While WES/WGS is

considered an important advancement in overcoming the

limitations of GWAS-generated genomic information, it is

imperative that the strengths and weaknesses of next gener-

ation sequencing be objectively assessed.

The growing use of WES/WGS in the research context and

clinical domain represents a robust means of detecting

causative mutations of variable penetrance and high impact

rare variants not possible before. However, the complex nature

and vast scale of both the next-generation sequencing

technologies and bioinformatics systems employed in WES/

WGS-based identification of deleterious genetic variants may

result in many problems. These range from library preparation

and sequencing artifacts, to the data analysis pipelines

employed to filter and annotate potential causative gene

variants. A significant shortcoming of WES in particular is the

fact that this sequencing methodology cannot identify disease-

associated structural genetic abnormalities, trinucleotide repe-

titions and most intronic variants with their potential regula-

tory functions. Another significant limitation is the relatively

high error rate for incorrect base pair identification104.

Genotype and variant inference in the presence of such

misalignment and base-reading sequencing errors, without

confirmation by alternative mutation detection methods, may

therefore lead to the incorrect assignment of risk-allele

carriage with potential downstream implications for patient

management. Any candidate etiological variant detected by

next generation sequencing analysis must be additionally

confirmed by another laboratory technique such as Sanger

sequencing to define the presence of the variant allele with

confidence. Furthermore, the process of identifying candidate

etiological variants from the many private mutations of

unknown clinical significance detected in individuals and

families, especially those of African origin given the vast pool

of undocumented genetic diversity on the continent, is a

complicated and time-consuming process. Given the fact that it

is seldom possible to identify the etiological variant with

absolute certainty without further functional studies, signifi-

cant ethical challenges are posed in the return of especially

novel findings with potential clinical implications to patients.

Clinical application of WES/WGS may further be

complicated by lack of sufficient infrastructure and data

storage systems compatible with the large amount of genetic

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information generated by next generation sequencing tech-

nologies105. The development of enabling computational and

bioinformatics tools are therefore required106,107. Detailed

phenotypic description and characterization of patients sub-

jected to such testing are also required to optimize the use of

next generation sequencing for risk assessment and manage-

ment purposes at the individual level108,109. This requirement

is partly provided by using the PSGT approach that includes

generation of genetic information on a limited number of

founder mutations common in South Africa, where relevant

and/or clinically useful functional polymorphisms implicated

in disease pathways shared by many NCDs. For quality

assurance purposes, the known gene variants covered in the

chronic disease screening program as part of the PSGT

service could be verified by WES/WGS prior to a search for

disease causative mutations in genetically uncharacterized

patients or non-responders to drug treatment. This step serves

to confirm the identity of the patient sample analyzed, while

newly identified gene variants in turn may be validated in an

extended sample of patients and controls from the existing

database resource as illustrated in Figure 1, in order to

exclude genotype errors resulting from the use of WES/WGS

and to validate novel findings in a clinical context.

While most WES studies published in 2013 were per-

formed on the Illumina HiSeq, alternative sequencing

platforms have emerged with the commercial release of the

Personal Genome Machine (PGM). This apparatus is based on

non-optical detection of hydrogen ions released with the

sequential addition of deoxynucleotides to a growing DNA

chain and may offer a faster turn-around time, less costly than

current fluorescent-labeled detection platforms. Despite these

advantages, the PGM apparently does not generate WES data

with adequate high coverage per base. In 2012, the Proton was

released, which is considered the ‘‘next generation’’ of

semiconductor sequencing instrumentation, designed to gen-

erate gigabases of data at a low cost. Compared to the typical

6-day run time of the Illumina HiSeq, the Proton provides

results within one day, with 3.5 h run time and 8 h data

processing time under ideal conditions110. Major discrepan-

cies were identified with both platforms in the detection of

small indels due to the propensity for polymerase slipping

during polymerase chain reaction (PCR), resulting in sequen-

cing artifacts. Since indels are expected to account for a large

fraction of somatic changes in cancer, further refinement of

the technical sequencing and calling algorithms used for

sequencing data generated by both the Illumina and Proton is

required. Boland et al.110 demonstrated that the Proton can

generate high-quality WES data and detect a number of SNPs

and indels not identified by the Ilumina, which in turn

identified variants that were missed by the Proton.

In our experience from previous results obtained from the

first four exomes of MS patients sequenced on the Ilumina

HiSeq2000 next generation sequencing platform20,111, fol-

lowed by repeat sequencing in 2014 using the Proton as

discussed below, more than one next generation sequencing

platform should ideally be used to obtain high-quality data

suitable for clinical application. In addition, the low concord-

ance between variant-calling pipelines poses a significant

potential source of error affecting the accuracy of WES/WGS

sequencing data112.

Exome sequencing in multiple sclerosis research:lessons learned

Extension of PSGT to WES was first applied in adult patients

with MS to further explore the role of genetic risk factors

mediating the apparent interplay between iron metabolism

and inflammation in a subgroup of patients113,114. In accord-

ance with a recent study performed in more than 100 MS

patients115, two adult MS cases were heterozygous for a non-

synonymous (V736A) change in the transmembrane protease,

serine 6 (TMPRSS6) gene. This SNP (rs855791) previously

identified by GWAS reduces the ability of the enzyme to

inhibit the transcription of hepcidin, the main regulator of

iron metabolism116. Since inflammation, implicated in all

NCDs and various other environmental and genetic factors,

also influences hepcidin expression, TMPRSS6 rs855791 is

included as a part of the PSGT gene panel that may be

extended to WES as illustrated in Figure 1. Due to ethical

constraints related to testing of children for genetic risk

factors pre-disposing to adult-onset medical conditions, the

standard PSGT pre-screen step was omitted in two South

African children selected for WES, who were found to be

highly responsive to iron supplementation117. Homozygosity

reported initially for TMPRSS6 A736V (rs855791) using

WES could, however, not be confirmed afterwards by

conventional Sanger sequencing in our laboratory. This

discrepancy was caused by the presence of the risk-associated

minor T-allele of TMPRSS6 rs855791 in the public reference

genome sequence (hg19)121 used for variant calling, instead

of the wild-type major C-allele. This finding also highlighted

the fact that where a major allele is replaced by the minor

allele in the reference genome sequence, true homozygotes

will be missed by WES and most likely filtered out due to an

apparent high population frequency. Fortunately, these prob-

lems were identified prior to return of relevant genetic

findings to MS patients with low iron status.

The unexpected high number of false-positive variants

initially reported in our patient cohort did not only affect

relatively common SNPs as may be expected for TMPRSS6

rs855791, but also rare variants due to incorrect presentation of

the major allele as the minor allele. The presence of minor

alleles in hg19 may negatively affect both the sequence read

alignment and variant calling used in WES. Individuals who

are homozygous for a minor allele listed in the reference

genome will not be identified as having a gene variant at that

locus and the opportunity for interpretation of clinical

relevance will be missed. Both heterozygotes and homozygotes

for major alleles absent in hg19 would furthermore be reported

as potential disease-associated variants at such loci. This

supports the development of a catalog of clinically annotated

variants (SNP knowledge database)118 as an essential element

of the PSGT platform containing information extracted from

the literature on the risk allele and trait/disease associations

previously replicated in different populations. Results from

meta-analyses are freely available online in databases such as

the Single Nucleotide Polymorphism Database of the National

Centre for Biotechnology Information (www.ncbi.nlm.nih.-

gov/SNP) and SNPedia that gathers information from

PubMed on a daily basis to support genome annotation and

interpretation (http://www.snpedia.com/index.php/SNPedia).

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Data retrieved after variant calling are individually evaluated

against these resources to verify their minor/risk allele status,

prior to analytical validation of potentially deleterious gene

variants in the laboratory.

Since a corrected reference genome sequence was not

readily available to solve the variant calling problem follow-

ing WES, we searched the scientific literature for the possible

existence of a major allele reference sequence that can be

used instead of hg19. Such a tool was indeed described by

Dewey et al.119, who reported the critical importance of an

enhanced human reference sequence for accurate disease-,

carrier- and pharmacogenetic-risk assessment using WES/

WGS. These authors reported 10 396 variant alleles using

hg19 in a family study, compared to only 9389 variant alleles

identified when the synthetic ethnically concordant major

allele reference genome was used for variant calling.

The genotyping error rate was 38% higher with use of the

hg19 reference genome (5.8 per 10 000 variants) compared

with the major allele reference genome (4.2 per 10 000

variants). A total of 233 genotype calls at 130 disease-

associated SNPs differed between the hg19 and the major

allele reference genomes. Independent genotyping technology

verified 161/188 genotypes (85.6%) in the major allele call set

compared to 68/188 (36.2%) in the hg19 call set119.

Preliminary findings following variant calling in one of the

above-mentioned South African MS patients revealed dis-

cordance of nearly 20% between use of hg19 and the major

allele reference sequence.

Although not relevant in the case of de novo mutations,

routine inclusion of both affected and unaffected family

members when performing WES is important to exclude

potential errors based on the fact that both parents of

homozygous children would be obligate heterozygotes.

Transmission analysis, physical pair-end sequencing of

libraries and population-based genome phasing analysis

performed in a family quartet studied by Lajugie et al.120

enabled the generation of a more complete list of true variants

and determination of the false-positive and false-negative

variant calling error rates in comparison with hg19. The hg19

reference genome was deduced from a collection of DNA

samples from anonymous individuals121, but when compared

against a large high-quality SNP disease-association database,

3556 disease-associated variants, including 15 rare variants,

were found122. Since the interpretation of personal genome

sequences mainly focuses on the identification and functional

annotation of genetic variants that differ from hg19, these

findings highlighted the fact that the presence of minor alleles

relating to disease-susceptibility in this public reference

human genome should be taken into account during data

interpretation for assessment of personal disease risk.

Next-generation sequencing presents a conundrum to the

field of medical science: while it has the potential to identify

every single causal or contributory gene variant for any

given genetic disorder, every step along the path to this goal

is complicated by technical, clinical and ethico-legal chal-

lenges. These difficulties range from phenotyping and

informed consent for sample collection to discrepancies

between different sequencing platforms and low concordance

among multiple variant-calling pipelines used in WES/

WGS110,111,119.

Ethical considerations

We are rapidly approaching a reality when data interpretation

capacity and ethical concerns rather than cost barriers will be

the main limiting factors in genomic medicine. In the South

African context, fear of genetic discrimination in relation to

life insurance was identified as a major concern upon

completion of the sequencing of the human genome in

2003. To address this issue, three areas of risk were defined at

the time to explain that all genetic tests are not equal123:

(1) Medical conditions transmitted by a single dominant

gene or a pair of recessive genes.

(2) Pre-disposition to a disease or group of diseases with only

a small proportion of the disease burden caused by single

gene defects.

(3) Course of disease is not genetic in nature but is

influenced by genetic variation.

The benefits of genetic testing need to be weighed against

potential harm and would depend on various factors,

including cost, the prevalence and penetrance of a gene

variant, the mortality associated with the mutation/disease

and the potential for effective intervention based on the

additional genetic knowledge gained. Both the emergence of

WES/WGS and a growing proliferation of large-scale genetic

biobanking ventures internationally have further complicated

the ethical landscape of genomics and biomedical research.

These developments magnified existing moral dilemmas

inherent to genetic testing. For example, firmly held beliefs

on what constitutes true voluntary informed consent and the

process by which this should be obtained have effectively

been challenged by the advent of large-scale biobank-

ing124,125. New population-based or context-dependent

models may need to be developed in order to foster research

in previously underrepresented African population groups in

relation to WES/WGS research126,127.

Data security and privacy are important concerns that need

to be carefully considered in relation to the use of an open

innovation platform allowing for sharing of genetic data.

General topics to be considered include accountability,

informed consent, transparency, disclosure and patient de-

identification to ensure privacy. Ideally, the establishment of

an effective data integration system requires (1) standardiza-

tion of genetic information, (2) adequate infrastructure to

facilitate analytical validation of assays and assist in the

interpretation, reporting and follow-up of genetic data, (3) the

development of effective archiving methods as well as (4)

statistical tools to simplify appropriate analysis of data. To

achieve these outcomes, a computer-based data integration

system is continually being developed in our laboratory,

linked to a secure centrally maintained research database and

related software programs. In accordance with these goals, the

PSGT platform enables the documentation of patient infor-

mation collected at different professional levels, for integra-

tion in such a manner as to provide a comprehensive report

with actionable information to the referring clinician.

While it is generally agreed that genetic data may be

returned to individuals under the condition that they are

clinically actionable, results generated in the context of WES/

WGS range in clinical relevance and the extent to which

research and service delivery may impact upon the degree and

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timing of data return. Due to the unknown significance of a

substantial amount of data generated by these technologies,

the legal, and to a lesser extent, moral duty of the researcher

to return such information is limited at this time. The duty to

inform is further influenced by the relationship between

researcher and participants and may vary depending on the

setting, geography and cultural background. Yu et al.128

suggested providing participants with the option of self-

selection of specific results obtained via WES/WGS as a

favorable alternative, which respects the principles of benefi-

cence, non-maleficence and autonomy, as well as allowing for

future access as deemed appropriate. The question also arises

whether data sharing for secondary analysis implies retaining

of responsibilities to return these results to participants. While

it remains unclear how clinicians will disseminate the large

volumes of genetic data generated by WES/WGS, the need for

a greater role of genetic counselors as well as medical

scientists participating in the service delivery process seems

obvious. Pre-test counseling forms an integral part of genetic

research and includes relaying information on the voluntary

nature of the inclusion. However, given the sheer volume of

information generated as a result of WES/WGS, it seems

inconceivable that clinicians will be able to anticipate all the

implications for their patients. For WES/WGS to be success-

fully incorporated as part of clinical practice, it is imperative

that appropriate methods of providing pre-test counseling be

developed, to guide informed decision making, and that

clinicians are equipped to interpret and communicate such

WES/WGS applications to patients.

Our experience in the ethical return of genetic testing results

using a clinician-mediated combined service delivery and

research approach provides a sound basis from which the

ethico-legal challenges posed by next-generation sequencing

can be addressed. Potential concerns are pre-emptively

addressed by positioning the PSGT service as a pre-screening

tool for (1) selection of patients eligible for WES/WGS, and (2)

to extend the current gene panel towards a more comprehen-

sive analysis of clinical and pathology results in the context of

the genetic findings. The ultimate aim is to empower the

clinician to derive the best current, clinically actionable

information for a wide range of clinical applications.

The PSGT approach to genomics-based NCD risk man-

agement (Figure 1) is in many respects similar to the analysis

pipeline applied by Ashley et al.129 for clinical evaluation

incorporating a personal genome. Since both assessments are

capable of identifying multigenic risk factors for heritable

conditions and informing the appropriate pharmacological

treatment, WES/WGS is the logical next step beyond a

limited number of gene variants included in the chronic

disease screening panel8. Specific points of overlap between

the two frameworks include (a) the need for a novel approach

to integrate personalized genomic testing with existing

clinical NCD risk prediction algorithms, (b) a focus on

replication of well-established genotype-phenotype associ-

ations in a specific target population considered in the context

of known non-genetic drivers of clinical expression and (c)

consideration of genetic variant databases for the identifica-

tion of novel causative mutations by means of WES/WGS,

taking into account both the strengths and limitations. PSGT

utilizes an ethically approved process for the return of results

obtained from a range of genetic tests of varying complexity

incorporated into an existing body of knowledge with the aid

of the Gknowmix� interpretation system, where appropriate.

A detailed report is provided to the referring clinician or a

genetic counselor to be relayed to the patient. Feedback after

genetic testing results become available is considered import-

ant when (1) a particular NCD or family history of relevance

to the genetic findings is present, (2) modifiable risk factors

for the development of an avoidable or treatable condition are

reinforced by the presence of a particular genetic susceptibil-

ity as indicated by testing or (3) genetic counseling is

indicated, e.g. when more extensive genetic testing may be

advisable. Interpretation of genetic variants should be in

conjunction with the family history and health status of the

patient, as currently performed using the PSGT strategy that

applies a computer-based program specifically designed for

this purpose. A carefully documented family history as part of

the pre-test counseling process can be performed online for

further verification during the genetic counseling process.

Before any genetic test is performed, the expectations of

patients need to be managed as this paves the way for future

behavioral changes and compliance to treatment.

Conclusions

A history of illness in affected family members as well as

early onset clinical presentation and emergence of complica-

tions have long been considered primary indications of patient

referral for genetic testing. In this overview, we explain how

the consideration of pathological criteria (reflected by

histological or biochemical assessment), alongside clinical

risk factors incorporated in the development of a genomics

pre-screen algorithm, is used to assist clinicians in determin-

ing patient eligibility for genomic testing. Insights gained as a

result of research performed in the diverse South African

population over more than two decades, provide a useful

framework for the positioning of the PSGT service as a pre-

screening tool to facilitate the selection of genetically

uncharacterized patients or non-responders to treatment,

eligible for, and set to benefit from WES/WGS. The addition

of such eligibility guidelines may limit unnecessary patient

referral for next-generation sequencing in cases where

individual disease risk, pathological severity or adverse

clinical or therapeutic outcomes, can be sufficiently explained

by genetic variants incorporated as part of the carefully

selected multi-gene testing assays utilized in the PSGT

approach. Given the finding that the public reference

genome sequence (hg19) contains minor alleles at more

than 1 million positions121, the correct allocation of the minor

allele for each potential risk-associated variant identified after

variant calling presents a critical step for appropriate inter-

pretation of genetic data.

The MammaPrint experience substantiated the value of a

genomics database as a viable alternative to RCTs for

establishing the clinical utility of emerging genomic applica-

tions. A practical approach to personalized genomics was

established, whereby genetic testing performed within a

multidisciplinary clinical framework can help inform clinical

decision making and guide the selection of appropriate

treatment. Follow-up assessment of long-term health

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outcomes in relation to implemented treatment could foster

research translation and provide evidence in support of

clinical utility as an important pre-requisite for the wide-

spread and routine implementation of personalized genetic

testing in the clinical domain. Future studies would be

facilitated by the easily searchable engine of our research

database composed of a growing number of healthy volun-

teers and patient profiles gathered at a clinical, pathological

and genetic testing level. The overall objective is to maximize

the South African PSGT platform designed as a clinical tool

to identify genomic profiles which can be used to improve

risk management.

Despite promising results from on-going research, the

greatest determinant of successful implementation of genomic

medicine will likely be the willingness of healthcare practi-

tioners to apply genetic knowledge in clinical practice. This

necessitates the need for training of a new class of genomic

healthcare professionals and development of novel ways to

integrate and report the information. A collaborative effort

between all stakeholders, including service providers, regu-

latory bodies, ethics boards, health insurers, clinicians,

genetic counselors and patients themselves is thus required

via the common thread of pathology. The PSGT approach has

helped to inform public healthcare policy regarding the value

of microarray-based platforms and is well placed to incorp-

orate next generation sequencing technologies with the

potential to improve the standard of care in Africa and

elsewhere. Human genome sequencing data linked to clinical

information provides a valuable tool for disease prevention,

diagnosis and targeted treatment at an individual level.

Ultimately, the use of genetic testing for individual NCD

risk assessment and management purposes, irrespective of the

number of genes analyzed, will depend on the context within

which the test is performed. The value of personalized

medicine does not necessarily lie in prediction of risk with

100% accuracy, but rather to provide another line of evidence

that can be considered for optimal treatment of patients and to

support wellness and health maintenance.130

Acknowledgements

Dr Lynn Horn at Stellenbosch University is acknowledged for

valuable advice related to the ethical aspects that had to be

taken into account during development of a combined service

and research platform. Dr Ruhan Slabbert and Carel van

Heerden of the Central Analytical Facility, Stellenbosch

University, are thanked for exome sequencing and variant

calling using both the hg19 reference sequence and an

advanced major allele reference sequence on the same

samples. Family practitioner Dr Hein Badenhorst and regis-

tered dietitian Lindiwe Whati are thanked for their valuable

contribution to the development of the questionnaire and

nutrition scores used in the genomics-based chronic disease

screening/wellness program. Roberta Rooney is thanked for

her valuable contribution to the multiple sclerosis study over

many years and Dieter Geiger for research co-ordination.

Lujane Nutt, Theresa Brand and Janine Cronje are thanked for

assistance with the informed consent process, literature

review and administrative support. Dr Mike Urban is

acknowledged for helpful discussions and clinical oversight.

Declaration of interest

Research reported in this publication was supported by the

Strategic Health Innovation Partnerships (SHIP) Unit of the

South African Medical Research Council (MRC) with funds

received from the South African Department of Science and

Technology (Research grant number S003665). The MRC is

also acknowledged for an internship grant awarded to KE

Moremi and a capacity development grant awarded to Y. Y.

Yako towards development of the laboratory standard operat-

ing procedures in the Pathology Research Facility at

Stellenbosch University. This work is also based on the

research supported in part by the National Research

Foundation (NRF) of South Africa (UID 83962). The

Grantholder acknowledges that opinions, findings and conclu-

sions or recommendations expressed in any publication

generated by the NRF supported research are that of the

authors and that the NRF accepts no liability whatsoever in this

regard. The Cancer Association of South Africa is acknowl-

edged for a travel grant awarded to doctoral student N van der

Merwe. Financial support from Winetech and the Technology

for Human Resources and Industry Program (THRIP)

contributed to the development of a Short Course for clinician

education registered at Stellenbosch University in October

2014. M. J. Kotze is a director and shareholder of Gknowmix

(Pty) Ltd. that has developed a database tool for research

translation under the auspices of the Innovation Centre of the

South African Medical Research Council (MRC). The Support

Program for Industry Innovation is gratefully acknowledged for

financial support towards development of the Gknowmix�Genetic Knowledge Integration System (2007–2009) and

Clinical & Scientist Interface Model (2009–2012). In this

context, the Technology Innovation Agency is also acknowl-

edged for internship grants awarded to Leslie Fisher, Nicole

van der Merwe and Jacobus Pretorius (2013–2014). M. J.

Kotze, S. J. van Rensburg, F. J. Cronje and A. V. September are

listed as inventors on patents filed by the MRC and the

Universities of Stellenbosch and Cape Town. The remaining

authors declared no declarations of interest and no writing

assistance was obtained in the preparation of this manuscript.

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