SciELO - Scientific Electronic Library Online

vol.108 issue8Multiple organ failure: death of consumer protection?Requiem for Babinski author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



Related links

  • On index processCited by Google
  • On index processSimilars in Google


SAMJ: South African Medical Journal

On-line version ISSN 2078-5135
Print version ISSN 0256-9574

SAMJ, S. Afr. med. j. vol.108 n.8 Pretoria Aug. 2018 



Cystic fibrosis in South Africa: A changing diagnostic paradigm



J van RensburgI; M AlessandriniII, III; C StewartIV, V; M S PepperVI

IBSc, MSc; South African Medical Research Council Extramural Unit for Stem Cell Research and Therapy and Institute for Cellular and Molecular Medicine, Department of Immunology, School of Medicine, Faculty of Health Sciences, University of Pretoria, South Africa
IIBSc, MSc, PhD; South African Medical Research Council Extramural Unit for Stem Cell Research and Therapy and Institute for Cellular and Molecular Medicine, Department of Immunology, School of Medicine, Faculty of Health Sciences, University of Pretoria, South Africa
IIIBSc, MSc, PhD; Department of Pathology and Immunology, Faculty of Medicine, University of Geneva, Switzerland
IVSc, PhD; South African Medical Research Council Extramural Unit for Stem Cell Research and Therapy and Institute for Cellular and Molecular Medicine, Department of Immunology, School of Medicine, Faculty of Health Sciences, University of Pretoria, South Africa
VDepartment of Basic Medical Sciences, Faculty of Medical Sciences, University of the West Indies, Mona, Jamaica
VIMB ChB, PhD, MD, Privat Docent; South African Medical Research Council Extramural Unit for Stem Cell Research and Therapy and Institute for Cellular and Molecular Medicine, Department of Immunology, School of Medicine, Faculty of Health Sciences, University of Pretoria, South Africa





Cystic fibrosis (CF), one of the most commonly observed and diagnosed fatal monogenic disorders globally, was initially thought to affect individuals of Caucasian/European descent almost exclusively. It is increasingly appreciated, however, that non-Caucasian populations are also affected by this condition. Although this has been known in South Africa (SA) for over two decades, a large disparity still exists in data pertaining to the different population groups in the country. This article seeks to highlight existing published data on CF in SA populations and reflects on the means through which these have been generated over the years. Additionally, the article briefly discusses the consequences of incomplete data and how this could potentially be addressed in the future through innovative and collaborative approaches.



Cystic fibrosis (CF), one of the most commonly diagnosed mono-genic disorders, has been well researched in many nations. Primarily affecting the mucus-secreting organs of the body, such as the lungs, pancreas, liver and intestinal tract, no cure has been developed for this fatal disorder. Nevertheless, assisted by large-scale research efforts and advances in sequencing technologies, several countries, including Australia, Belgium, Canada, France, Germany, the UK, The Netherlands and the USA, have successfully established CF registries. These registries have had a positive impact on the management and therefore on the quality of life of patients with CF and have also provided benefit in terms of reducing the costs associated with their care.[1-3]

In countries in which CF research has been well established and where CF registries and/or newborn screening programmes exist, median survival rates for patients with CF have increased steadily year on year. Currently the median age of survival is 52 years in Canada,[4] 42 years in the USA,[5] 40 years in Europe[6] and 27 years in Australia.[7] In South Africa (SA), the life expectancy of a CF patient, as reported in 2008, was less than 21 years.[8] In comparison, life expectancy for Canadian, American, French, British and Australian CF patients in the same year was approximately 30, 37, 28, 27 and 30 years, respectively.[9-13] Westwood[8] also highlighted the difference that existed between the median age of death in white individuals with CF, i.e. of Caucasian/European descent (25.8 years), and patients of mixed race (20.5 years) in the Western Cape Province of SA. Nevertheless, very little is known about causative CF variants in SA and other African nations.[14,15] This difference is due in part to the widespread and incorrect belief that CF only affects 'white' populations - a notion that is increasingly being shown to be incorrect.[16,17]


Consequences of an age-old problem and potential solutions

The initial assumption that CF could only affect white South Africans was in part based on the observed disparity in mutation detection rates between population groups. Variations in mutation detection rates have been influenced further by the fact that many CF-causing variants are population specific. Currently, more is known about CF mutations found in the well-characterised white SA population than any of the other affected population groups. As a result, causative variants are typically identified in 83% of white SA CF patients, while CF-associated variants have previously only been identified in 55% and 21% of mixed-race and black SA CF patients, respectively. [18] Screening panels initially used to diagnose CF in SA patients were based on variants that are common to European populations, and while attempts have been made to collect larger numbers of CF samples in other patient groups in SA, few publications addressing the chasm in variant data exist.

A lack of CF data in non-Caucasoid population groups is common to SA and other African countries. There are no patient registries for this disease on the African continent, which means that African CF patients cannot benefit from clinical interventions planned on the basis of trends in registry data. Despite the unparalleled genomic diversity that exists in African populations, African genomes have been vastly understudied.[19] This is illustrated in patients in whom genetic testing returns false-negative results because the CF-causing mutations have not been fully characterised in their population(s). In some cases, this problem has been resolved through the application of gene sequencing methods.[20,21] Adding further complexity to existing information is the fact that a significant proportion of reported SA CF data were published over 10 years ago (Table 1). Altogether, when considering the lack of data and the absence of an SA newborn screening programme, making a quick and accurate molecular diagnosis of CF is difficult in many cases, and assessing the health of the local CF population in order to propose and implement the interventions needed to improve prognosis is challenging.

Early detection of CF has repeatedly been shown to be of benefit to patients and public healthcare systems.[30,31] For instance, in 2012, 65%, 63%, and 50% of all new CF cases in Australia, France and The Netherlands, respectively, were detected through neonatal screening

programmes.[12,32,33] In 2011, neonatal screening accounted for the detection of 74% of all new CF cases in the UK.[13] This has been highly beneficial, since early detection of CF can reduce negative nutritional outcomes, general health complications and decline in cognitive capacity, thereby improving the overall health of affected patients.[34, 35] Early diagnosis has also been shown to provide an economic benefit. For example, Dutch patients identified by newborn screening programmes spend about a million euros less on treatment over the course of their lives than patients not discovered through this method.[36] Interestingly, despite the clearly demonstrated benefit of early diagnosis, in studies conducted on SA CF patients there is no correlation between specific CF variants and the severity of lung function decline and associated nutritional status.[37,38]

Based on CF variant data that are currently available, the most common CF variants in SA are AF508, c.3120+1G>A, c.3272-26A>G and 394delTT, which have been identified in 69.8%, 13.2%, 3.4%, and 3.0% of screened patients, respectively (Table 2). However, as reflected in Table 1, different screening methods were used in the detection of these variants. Although not always feasible, especially in early studies, it must also be noted that not a single reported study has made use of an unbiased DNA sequencing approach. For example, many black SA patients are screened only for the presence of the c.3120+1G>A variant in order to make a positive molecular diagnosis of CF.[17,18,39] Novel or SA-specific mutations in the major population groups have therefore gone undiscovered or could not have been detected owing to limited screening capacity. An additional confounding factor, as illustrated in Table 3, is that SA CF data have largely been dominated by white patients, a minority genetic group in the country. Although historical factors are largely responsible for this phenomenon, access to and the cost of sequencing technology now make it possible to obtain new information with relative ease, affordability and speed.[40] Use of advanced sequencing methods, particularly in majority population groups, would be of benefit to SA CF patients, since SA is home to some of the most genetically diverse population groups in the world.[41]

A need for more molecular data to assist with accurately diagnosing SA and African CF patients therefore exists. Nevertheless, as illustrated by existing CF registries, several types of data (and not just causative variant information) are investigated. In the absence of molecular data, developing algorithms that can aid in the diagnosis of CF given limited clinical, biochemical and/or molecular information may be invaluable to SA clinicians in the interim. Although such programmes/tools are only as good as the quality and quantity of available data, they at least have the potential to present baseline probabilities as to a positive CF diagnosis. Such tools might easily serve as a standard by which potential CF patients could be selected for sequencing projects, thereby maximising the odds of identifying previously undescribed CF variants. In so doing, more exact data could be fed back into diagnostic algorithms to improve their accuracy.



The lack of standardised SA CF data is having a negative impact on the longevity of SA CF patients. Driving CF research with the distinct aims of: (i) identifying CF variants relevant to all SA population groups; (ii) establishing and maintaining a country-specific CF database/registry; (iii) establishing a solid foundation for a newborn screening programme; and (iv) exploring novel means through which a positive clinical diagnosis could be made (given limited molecular data) would be of great benefit to the overall care received by many local patients. The first of these points can be achieved through the use of next-generation sequencing methods, whole-exome sequencing, and/or targeted sequencing of the CFTR (cystic fibrosis transmembrane conductance regulator) gene. Although presenting their own unique challenges, sincere, multidisciplinary collaborative efforts that involve stakeholders from academic, private, public and government sectors would be able to address the remaining points.[42] Together, these changes could ensure a healthier and longer future for all SA CF patients.

Acknowledgements. The authors thank colleagues who have contributed to the multiple discussions and feedback sessions held around this topic. They also thank the various institutions and enterprises that have contributed financially towards this research.

Author contributions. All the authors contributed equally to the conception and construction of the article. JvR and MA were responsible for collating SA CF variant data, while CS and MSP were responsible for contributions relating to global incidence data and the economic impact of CF.

Funding. Funding sources include the Institute for Cellular and Molecular Medicine and the Genomics Research Institute of the University of Pretoria, the South African Medical Research Council, and the National Research Foundation of South Africa.

Conflicts of interest. None.



1. Yuanyuan G, García-Pérez S, Massie J, van Gool K. Cost of care for cystic fibrosis: An investigation of cost determinants using national registry data. Eur J Health Econ 2015;16(7):709-717.        [ Links ]

2. Larsson S, Lawyer P. Improving Health Care Value: The Case for Disease Registries 2011. Boston Consulting Group, 2016. (accessed 9 July 2018).         [ Links ]

3. Thomas M, Wanyama SS, Vermeulen F. The Belgian Cystic Fibrosis Registry. Brussels: Scientific Institute of Public Health (WIV-ISP): Registre Belge de la Mucoviscidose, 2011:1-44.         [ Links ]

4. Stephenson A, Mak D, Mahmood A, et al. The Canadian Cystic Fibrosis Registry: 2015 Annual Report. Toronto: Cystic Fibrosis Canada, 2015:1-40.         [ Links ]

5. Marshall BC, Elbert A, Petren K, et al. Cystic Fibrosis Foundation Patient Registry: 2015 Annual Data Report. Bethesda, Md.: Cystic Fibrosis Foundation, 2015:1-49.         [ Links ]

6. Ikpa PT, Bijvelds MJC, de Jonge HR. Cystic fibrosis: Toward personalized therapies. Int J Biochem Cell Biol 2014;52:192-200.        [ Links ]

7. Burke N, Bell S, Bye P, et al. Cystic fibrosis in Australia: 16th Annual Report from the Australian Cystic Fibrosis Data Registry. Baulkham Hills, NSW: Cystic Fibrosis Australia, 2013:1-44.         [ Links ]

8. Westwood AT. The prognosis of cystic fibrosis in the Western Cape Province of South Africa: A 33 year study. J Cyst Fibros 2008;7(S2):458.        [ Links ]

9. Marshall BC, Hazle L. Cystic Fibrosis Foundation Patient Registry: 2008 Annual Data Report. Bethesda, Md.: Cystic Fibrosis Foundation, 2008:1-24.         [ Links ]

10. Stewart T, Bell S, Bye P, et al. Cystic Fibrosis in Australia: 11th Annual Report from the Australian Cystic Fibrosis Data Registry. North Ryde, NSW: Cystic Fibrosis Australia, 2008:1-57.         [ Links ]

11. Stephenson A, Berthiaume Y, Chilvers M, et al. Canadian Cystic Fibrosis Patient Data Registry Report: 2008. Toronto: Cystic Fibrosis Canada, 2015:1-40.         [ Links ]

12. Bellis G, Lemonnier L, Sponga M, Zeghidour N. French CF Registry: Annual Data Report 2012. Paris: Vaincre la Mucoviscidose and Ined, 2014:1-48.         [ Links ]

13. Bilton D, Doull I, Brownlee K, et al. UK CF Registry: Annual Data Report 2011. Bromley, Kent: Cystic Fibrosis Trust, 2013:1-5.         [ Links ]

14. Stewart C, Pepper MS. Cystic fibrosis on the African continent. Genet Med 2016;18(7):653-662.        [ Links ]

15. Stewart C, Pepper MS. Cystic fibrosis in the African diaspora. Ann Am Thorac Soc 2017;14(1):1-7.        [ Links ]

16. Mutesa L, Bours V. Diagnostic challenges of cystic fibrosis in patients of African origin. J Trop Pediatr 2009;55(5):281-286.        [ Links ]

17. Masekela R, Zampoli M, Westwood AT, et al. Phenotypic expression of the 3120+1G>A mutation in non-Caucasian children with cystic fibrosis in South Africa. J Cyst Fibros 2013;12(4):363-366.        [ Links ]

18. Goldman A, Graf C, Ramsay M. Molecular diagnosis of cystic fibrosis in South African populations. S Afr Med J 2003;93(7):518-519.         [ Links ]

19. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature 2016;538(7624):161-164.        [ Links ]

20. Alper ÖM, Wong L-JC, Young S, et al. Identification of novel and rare mutations in California Hispanic and African American cystic fibrosis patients. Hum Mutat 2004;24(4):353.        [ Links ]

21. Sugarman EA, Rohlfs EM, Silverman LM, Allitto BA. CFTR mutation distribution among U.S. Hispanic and African American individuals: Evaluation in cystic fibrosis patient and carrier screening populations. Genet Med 2004;6(5):392-399.        [ Links ]

22. Denter M, Ramsay M, Jenkins T. Cystic fibrosis: Part I. Frequency of the delta F508 mutation in South African families with cystic fibrosis. S Afr Med J 1992;82(1):7-10.         [ Links ]

23. Herbert JS, Retief AE. The frequency of the delta F508 mutation in the cystic fibrosis genes of 71 unrelated South African cystic fibrosis patients. S Afr Med J 1992;82(1):13-15.         [ Links ]

24. Osborne L, Santis G, Schwarz M, et al. Incidence and expression of the N1303K mutation of the cystic fibrosis (CFTR) gene. Hum Genet 1992;89(6):653-658.        [ Links ]

25. Carles S, des Georges M, Goldman A, et al. First report of CFTR mutations in black cystic fibrosis patients of southern African origin. J Med Genet 1996;33(9):802-804.        [ Links ]

26. Padoa C, Goldman A, Jenkins T, Ramsay M. Cystic fibrosis carrier frequencies in populations of African origin. J Med Genet 1999;36(1):41-44.         [ Links ]

27. Romey M-C, Guittard C, Carles S, Demaille J, Claustres M, Ramsay M. First putative sequence alterations in the minimal CFTR promoter region. J Med Genet 1999;36(3):263-264.         [ Links ]

28. Des Georges M, Guittard C, Templin C, et al. WGA allows the molecular characterization of a novel large CFTR rearrangement in a black South African cystic fibrosis patient. J Mol Diagn 2008;10(6):544-548.        [ Links ]

29. De Carvalho CL, Ramsay M. CFTR structural rearrangements are not a major mutational mechanism in black and coloured southern African patients with cystic fibrosis. S Afr Med J 2009;99(10):724.         [ Links ]

30. Nshimyumukiza L, Bois A, Daigneault P, et al. Cost effectivness of newborn screening for cystic fibrosis: A simulation study. J Cyst Fibros 2014;13(3):267-274.        [ Links ]

31. Brice P, Jarrett J, Mugford M. Genetic screening for cystic fibrosis: An overview of the science and the economics. J Cyst Fibros 2007;6(4):255-261.        [ Links ]

32. Jack D, Bell S, Bye P, et al. Cystic fibrosis in Australia: 15th Annual Report from the Australian Cystic Fibrosis Data Registry. Baulkham Hills, NSW: Cystic Fibrosis Australia, 2012:1-44.         [ Links ]

33. Noordhoek-van der Staay JJ, Koppelman GH, Kraan J, et al. Dutch Cystic Fibrosis Registry: Report on the year 2012. Baarn, The Netherlands: Nederlandse Cystic Fibrosis Stichting, 2013:1-33.         [ Links ]

34. Accurso FJ, Sontag MK, Wagener JS. Complications associated with symptomatic diagnosis in infants with cystic fibrosis. J Pediatr 2005;147(3):S37-S41.        [ Links ]

35. Campbell PW, White TB. Newborn screening for cystic fibrosis: An opportunity to improve care and outcomes. J Pediatr 2005;147(3):S2-S5.        [ Links ]

36. Van der Ploeg C, van den Akker-van Marle M, Vernooij-van Langen A, et al. Cost-effectiveness of newborn screening for cystic fibrosis determined with real-life data. J Cyst Fibros 2015;14(2):194-202.        [ Links ]

37. Pentz A, Coetzee O, Masekela R, Green RJ. The impact of chronic pseudomonal infection on pulmonary function testing in individuals with cystic fibrosis in Pretoria, South Africa. S Afr Med J 2014;104(3):191-194.        [ Links ]

38. Masekela R, Olorunju S, Green RJ, Magidimisa NT. Lung function decline is accelerated in South Africans with cystic fibrosis. S Afr Fam Pract 2016;58(1):24-27.        [ Links ]

39. Goldman A, Claustres M, Guittard C, et al. The molecular basis of cystic fibrosis in South Africa. Clin Genet 2001;59(1):37-41.        [ Links ]

40. Goodwin S, McPherson JD, McCombie WR. Coming of age: Ten years of next-generation sequencing technologies. Nat Rev Genet 2016;17(6):333-351.        [ Links ]

41. Schlebusch CM, Lombard M, Soodyall H. MtDNA control region variation affirms diversity and deep sub-structure in populations from southern Africa. BMC Evol Biol 2013;13(1):1-21.        [ Links ]

42. Ramsey BW, Nepom GT, Lonial S. Academic, foundation, and industry collaboration in finding new therapies. N Engl J Med 2017;376(18):1762-1769.        [ Links ]



M S Pepper

Accepted 28 March 2018

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License