Genetic Testing for Cystic Fibrosis in South Africa: A 10-Year Retrospective Study

Genetic Testing for Cystic Fibrosis in South Africa: A 10-Year Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic Testing for Cystic Fibrosis in South Africa: A 10-Year Retrospective Study Sarah Walters, Colleen Aldous, Helen Malherbe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6247428/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Sep, 2025 Read the published version in Journal of Community Genetics → Version 1 posted 9 You are reading this latest preprint version Abstract Confirming a genetic diagnosis of cystic fibrosis (CF) for clinically affected individuals should be more accessible today, with more laboratories offering testing and improved technologies at lower costs. Instead, diagnostic testing for CF has become more complex due to the variety of genetic testing options available for the one known causative gene ( CFTR ). This article provides an overview of genetic tests currently available for CF in six laboratories in South Africa (SA). Also, it demonstrates the evolution of CF tests used at one private laboratory in the country via a ten-year retrospective study. The findings of this study may serve as a guide for healthcare providers in selecting appropriate testing for CF diagnostic or carrier genetic confirmation. The choice of genetic test and methodology depends on individualised factors such as the ethnic origin of the patient, test availability, advantages and limitations, and cost. The ethnic diversity of SA's populations and probable under-reporting of CF in the country makes the diagnosis of this relatively common genetic condition complex. The actual burden of CF in SA is unknown, and comprehensive genetic testing, with an ongoing compilation of patient data in the SA CF registry, should assist in addressing the genetic diversity of CF-causing variants. Cystic fibrosis genetic testing CFTR recommendations Figures Figure 1 Figure 2 Figure 3 Introduction Cystic Fibrosis and Genetic Testing Cystic fibrosis (CF) is a common, autosomal recessive condition in European-descent individuals with lower frequencies in other populations (World Health Organization, 2004). It can be detected in utero or at birth due to symptoms like meconium ileus or failure to thrive and later in childhood with recurrent respiratory infections and Pseudomonas aeruginosa colonisation. Advances in CF-specific modulator therapies have significantly improved life expectancy, increasing from 17 years in 1970 to 53 years in 2021 (Burgener and Cornfield, 2023). The CF transmembrane conductance regulator ( CFTR ) gene responsible for causing CF was identified in 1989 (Kerem et al., 1989), expanding knowledge of CF genetics. The international CFTR2 database from Johns Hopkins University, USA ([ https://cftr2.org , accessed 13/2/2025]) lists 1085 CF-causing variants, 55 variants of varying clinical consequence, and 27 non-CF-causing variants, while ClinVar ([ https://www.ncbi.nlm.nih.gov/clinvar/ , accessed 13/2/2025]) reports 5435 CFTR variants, including 1165 pathogenic variants plus an additional 500 likely pathogenic variants. Sweat chloride testing remains the global standard for CF screening (Farrell et al., 2017, Gibson and Cooke, 1959), with genetic confirmation recommended after two positive sweat tests on separate occasions (Mishra et al., 2005, Cowling, 2024). Newborn screening (NBS) for CF is available in mainly high-income countries where CF is common but remains largely unavailable in most low- and middle-income countries (LMICs) (da Silva Filho et al., 2021). Treatment for CF has progressed over the decades, focusing on better drugs, nutritional support, and advances in physiotherapy. Genetic confirmation of a CF diagnosis in light of new targeted modulator treatments is essential (de Melo et al., 2022). In South Africa (SA), CF testing by linkage analysis was introduced in 1987 (Hitzeroth et al., 1991). It was replaced by targeted testing for the common European population CF pathogenic variant, Delta F508 (also known as ΔF508, or p.Phe508del), later replaced by targeted CFTR variant testing (Van Rensburg et al., 2018). Whole CFTR sequencing by next-generation sequencing (NGS) and copy number variation (CNV) analysis are now available locally. Families with a history of CF may be offered NBS screening (at their own cost) via the country's private healthcare sector (Malherbe et al., 2024). Modulator therapies were introduced in 2019, dramatically improving clinical outcomes for most patients with CF who are genetically eligible (Graeber and Mall, 2023, de Melo et al., 2022). South Africa's Healthcare Context SA, an upper-middle-income country with a population of 63 million, is ethnically diverse, with 81.7% classified as Black African, 8,5% as Coloured, 7.2% as White, and 2.6% as Indian/Asian (Statistics South Africa, 2024). The country currently operates a dual healthcare system. The government-funded public healthcare sector serves approximately 84% of the population (52 million people), while 16% of the population, equating to 9.7 million people, access private healthcare (Cowling, 2024). CF genetic testing is available through the government-subsidised National Health Laboratory Service (NHLS) (National Department of Health, 2000), catering to the public sector and private pathology laboratories servicing patients on private healthcare insurance. Public sector testing remains limited, leading to result delays due to batching, reagent availability, lack of capacity, and other challenges. Individuals in the public sector may have limited access to CF testing, including sweat tests and genetic testing, thus delaying treatment due to geographical distance, availability of equipment, healthcare provider (HCP) awareness, and expertise. Currently, CF genetic testing in the public sector uses targeted variant kits covering pan-ethnic variants in CFTR , but it is limited to reporting specific pathogenic variants only. While new technology has emerged over the decades globally, recent studies have yet to be published on CF genetic testing currently implemented in SA, and little is known about the CF pathogenic variants tested for in South African healthcare. CF in South Africa—carrier rate and birth prevalence While CF carriers occur in all population groups worldwide in varying frequencies, only data for carriers in European and North American populations have been well documented. In individuals of reproductive age, carrier testing is essential to inform reproductive decision-making. Limited data is available for specific countries or population groups in many LMICs. For example, in India, carrier screening is limited to testing for only one common pathogenic variant. This carrier rate is estimated to be 1 in 238 (Kapoor et al., 2006), while carrier rates for CF in Vietnam were reported as 1 in 23 (To-Mai et al., 2024). The prevalence of CF in all 195 countries worldwide is yet to be documented. Guo et al. (2022) explored the worldwide rate of CF and reported on 94 countries where an estimated 162,428 people live with CF, but a diagnosis was made in only 105,352 of these individuals. These data provide an approximate diagnosed prevalence of between 0.17 and 0.27 affected individuals per 10000 people. In Africa, nine countries provided an estimated number of 1665 affected individuals, with the majority from Egypt and SA, with a prevalence of 0.5 affected individuals per 10000. However, this figure is likely highly under-reported. No information was available in 40 other African countries (primarily LMICs). A review of CF molecular epidemiology in Africa in 2016 showed that 12 of the 49 countries on the African continent have published relevant CF data (Stewart and Pepper, 2016). In SA, CF carrier frequencies vary between ethnic groups and were reported in the late 1990s as approximately 1 in 20 for the Caucasian population, 1 in 55 in the Coloured population, and 1 in 34–90 for the Black populations (Padoa et al., 1999). More recent studies indicate the CF birth prevalence as 1 in 3000 in the Caucasian population, 1 in 10,300 in the Coloured population, and 1 in 784 − 13,924 in the Black population (Zampoli et al., 2021). Both in SA and other countries worldwide, a higher carrier rate of CF and other specific genetic conditions have been documented for the Ashkenazi-Jewish population due to homogeneity and bottlenecks in the population diaspora (Waldman et al., 2022). Newborn screening for CF in SA is currently only available in the private healthcare sector for families with a CF family history. It is not offered in public healthcare (Zampoli M, 2021b) (Malherbe et al., 2024). As a result, a CF diagnosis generally only occurs after the neonatal period, several weeks or months after birth, thus delaying treatment and allowing disease progression. A South African Cystic Fibrosis Patient Registry was established in 2018, with the latest report including 523 affected individuals (Zampoli M, 2021a). Based on the reported carrier rates in the four South African ethnic groups, CF is still thought to be severely underdiagnosed in the country, especially in the Black population, due to confounding conditions such as malnutrition, TB, and HIV, which may mask CF symptoms (Westwood and Brown, 2006). CF may have different disease presentations and phenotypes and may vary between ethnic population groups. Anecdotally, CF is still considered a Caucasian disease in SA. Within this South African context, HCP awareness of current, appropriate CF genetic testing may need improvement due to new and changing testing methodologies. The aims of this study were: 1) To provide an overview of current and historic genetic tests available/implemented for CF in SA across both healthcare sectors; 2) Undertake a ten-year, retrospective study of CF diagnostic testing for private patients undertaken by one of SA's larger private pathology laboratories, and; 3) Undertake an analysis of HCPs requesting these tests. Methods The methodology used in this study was an observational descriptive retrospective review of CF genetic test methodologies, genetic results and HCP categories. Current CF genetic tests used in SA across public and private healthcare Four private and two of the three public NHLS genetics laboratories were contacted telephonically by the first author in 2019. The lead scientist in each molecular genetics laboratory was asked to specify which CF tests and methodology/kits are used in their laboratory. The two NHLS laboratories included (Johannesburg and Cape Town) represented CF testing in the public healthcare sector (the NHLS genetics laboratory offering CF testing in Bloemfontein was excluded), and these were compared with four private laboratories located in Johannesburg, Cape Town, and Centurion. Once these data were received and anonymised, the pathogenic variants included in each CF testing kit were identified using publicly available information for each manufacturer. These data were collated into a data extraction table adapted from the template in the South African 2017 CF consensus guidelines (Zampoli, 2017). See Supplementary File 1 for data points extracted. Retrospective audit of CF tests used in one private genetic laboratory The retrospective review analysed CFTR testing undertaken over ten years (January 2013 to December 2022) from one private laboratory in Gauteng. A ten-year timeframe was chosen to illustrate changes and advances in CFTR testing during this period and the future potential to improve CF testing for all South African ethnic populations. The private laboratory's Chief Executive Officer, Chief Operations Officer, and the Head of the Laboratory's Genetics Department (HOD) granted the gatekeeper permission to access these de-identified data. The HOD internally requested the required data from the laboratory's data officer via email. These data included the year of testing, test code, age, sex, test results (positive/carrier/negative) and cadre of HCP requesting the test. Descriptive statistics were used to interpret the data. Self-identified population grouping (i.e. ethnicity) is not a data point collected on the laboratory's test requisition form and, therefore, could not be included. Analysis of HCPs requesting CF tests The data collected from the 10-year retrospective study (point 2) above included a code for the cadre of HCPs who requested CF testing. This code was converted to the HCP qualifications/speciality. The speciality type was documented using Excel® and plotted on a logarithmic scale. The positive, negative, and carrier results were also documented. Ethical approval for the study was obtained from the UKZN Research Ethics Committee (BFC222/18). De-identified retrospective data were used in compliance with ethical and applicable data protection standards and regulations. No individual could be identified from the anonymised data; therefore, informed consent was deemed unnecessary as per institutional and international ethical frameworks, which permit using anonymised data for research without explicit consent. Results Current and Historic CFTR Genetic Testing Methods Used in South Africa: Data compiled from the six South African laboratories (two public and four private) revealed that four CF kits and whole CFTR sequencing were used in the country during the study period. The CF test kits were: CF30v2 (Elucigene), CFEU2v1 (which replaced CF30v2) CFTR Core (Devyser AB) CF Genotyping Assay (Abbott) Elucigene® CF30v2 is a gel-based assay used in the French national neonatal CF screening programme. It detects 30 pathogenic variants, most common in the French population. Elucigene® CF-EU2v1 is a pan-European CF testing kit to identify 50 pathogenic variants and analyse the poly-T tract. All NHLS laboratories offering kit-based testing utilise the same kit. Devyser® CFTR Core detects the 36 most common pathogenic variants of European origin. The Abbott® CF Genotyping assay detects 33 common pathogenic variants as recommended by the American College of Medical Genetics (ACMG) for the "general population". Table 1 Current and previous CFTR testing methodology implemented at six laboratories in South Africa. Public Private Lab A Lab B Lab C Lab D Lab E Lab F CF30v2 (Elucigene) 1 , CFEU2v1 (Elucigene) 2 CF30v2 (Elucigene), CFEU2v1 (Elucigene) 2 2013–2014: ΔF508 2014–2016: CF30v2 (Elucigene) 2 2016-current: Whole CFTR sequencing + CNV analysis CFTR Core (Devyser) 3 Previously CFTR sequencing, and now outsourced CF Genotyping Assay (Abbott) 4 Fifty-nine pathogenic variants were included in the four kits identified. Information regarding the pathogenic variants in each kit was obtained from the manufacturers (details in Supplementary Table 1). The CF30v2 kit includes three pathogenic variants common in the Afrikaner population, including 3272-26A > G, 394delTT, and G542X. The only known common pathogenic variants in the South African Black (c.2988 + 1G > A) and Indian populations (p.Phe508del) were present in all kits. Both p.Phe508del and c.2988 + 1G > A pathogenic variants are also found in the local Coloured population. Retrospective study: CF audit of one private laboratory Genetic Data and Test Method Evolution The collated data from one private laboratory (Lab C) from 2013–2022 showed how CF testing methodology has changed and evolved (Fig. 1 ). Initially, testing was performed using a kit for a limited number of pathogenic variants sent to a referral laboratory (2013–2014). Subsequently, a kit-based method was performed in-house (2014–2019), as outlined in Table 1 . Finally, next-generation sequencing (NGS) of the CFTR gene (including CNVs) was introduced (2016–2022). In-house whole CFTR sequencing began in 2016 and gradually increased in volume as the benefit of CFTR sequencing was realised by referring HCPs. The use of targeted variant kits was phased out as sample numbers declined in favour of sequencing. Results of patients tested: Over the ten-year study period, 1787 individuals were tested for CF at Laboratory C (Fig. 2 ). Of these, 13 results could not be traced. Twenty-eight results had one variant of uncertain significance (VUS), and two results had two VUSs. These 43 results (2.4%) were excluded from the analysis, as VUSs cannot confirm or refute a CF diagnosis until future possible reclassification. Of the remaining 1744 available patient results, 108 results (6.2%) had two CF-causing variants and 157 (9%) carrier results (Fig. 2 ). The 108 results with two CFTR likely/pathogenic variants were compared with the 50 variants detected by the CFEU2v1 test kit used in the public sector. Of these, 16 patients (14.8%) had pathogenic variants which the CFEU2v1 kit would not detect. Of the 157 with carrier results, 97 patients' carrier results (61.8%) could be identified by the CFEU2v1 test kit. One variant has since been classified as benign, and 15 carrier statuses (15.5%) would not have been detected using the CFEU2v1 test kit methodology. Breakdown of Referring HCPs: Of the 27 different HCP cadres referring the 1787 individuals for CF testing, the majority were paediatricians (1288/1787, 72%), followed by GPs (121/1787, 7%); shown in Fig. 3 and Supplementary File 2. Discussion This study evaluated genetic testing for CF patients in SA across the public and private sectors, analysing CF testing methodologies used in six laboratories and a decade of CF test results from one private laboratory. The detection rate at Lab C was 6%, with paediatricians, GPs, and specialist physicians being the primary test requestors. This study highlights the role of HCPs in making informed decisions when choosing an appropriate CF genetic test for their patients. It emphasises the need for continuous HCP education to stay abreast of new and emerging testing and treatment technologies. Four kit-based methodologies are used, with CFTR sequencing introduced in Lab C in 2016. Public-sector CF kit choices are influenced by cost, available technology, and known CF variant profiles in the population, while private labs likely consider similar factors. Given the incomplete understanding of CF genetics across all South African populations, Lab C continues to offer NGS-based CFTR sequencing. Complete gene sequencing is essential to improve patient outcomes by identifying all variants and assessing the new modulator therapy use. This study confirmed 16 CF diagnoses and the identification of 15 carriers, which are not detectable by the kit-based methodology, aiding in treatment decisions and reproductive decision-making. CFTR sequencing is crucial for identifying CF-causing variants in diverse populations and discovering new pathogenic variants. It could inform a tailored, SA-specific kit-based testing approach. Population-based genetic data is essential for improving public health strategies and early CF management in SA. International recommendations for testing: European recommendations for CF genetic testing at and after birth include primary (population-based targeted testing) and comprehensive (increased number of variants in targeted genetic testing, or CFTR sequencing) screening panels (Dodge, 2002), both of which are available in SA, as shown in Table 1 . The American College of Medical Genetics and Genomics (ACMG) recommends that "screening for all CF pathogenic variants at a carrier frequency of more than 1% of a population group is ideal". This statement also indicates that at least 23 pathogenic variants should be included for CF carrier testing and screening and that comprehensive methods of CFTR testing should be used if necessary (Deignan et al., 2023). The South African setting for testing: Ideally, CF genetic testing in SA should be based on pathogenic variants found in all the SA ethnic population groups. However, like the global situation, the South African Caucasian population has the most CF genetic data currently available since CF has been diagnosed mainly in this population. CF is thought to be uncommon in the Black, Indian, and Coloured populations, and earlier studies show how a CF diagnosis can be missed in Black patients (Westwood and Brown, 2006). CF may also be underdiagnosed in non-Caucasian ethnic groups due to confounding factors, including rare pathogenic variants and varying phenotypes (Westwood ATR, 1996). Following international standards for CF testing, most CF pathogenic variants in the Caucasian population are likely to be detected using the kit-based method. CFTR sequencing would also be required for individuals with only one pathogenic variant, significantly adding to the cost of testing. However, sequencing would be more beneficial as a first-line test in populations with an unknown underlying genetic basis. Molecular basis of CF in South Africa The molecular basis of CF in SA was previously discussed in a 2001 paper (Goldman et al., 2001), including a patient cohort across three of the four ethnic population groups, in which p.Phe508del accounted for 76% of the CF variant of 192 patients, indicating a CF founder effect in the Afrikaner Caucasian population. A further 11 pathogenic variants accounted for 6% of CF chromosomes in the same Afrikaner population. In the same study, approximately 91% of CF-causing pathogenic variants were detected using the CF30v2 kit (based on French population data), also in the Caucasian population (Goldman et al., 2001). Two pathogenic variants, p.Phe508del and c.2988 + 1G > A; p.? (3120 + 1G > A), were found in this South African Coloured population at frequencies of 43% and 29%, respectively. However, only 14 Coloured and 12 Black patients were included in the study, and the South African Indian population was either excluded or testing had not been requested. The c.2988 + 1G > A; p.? (3120 + 1G > A) pathogenic variant accounted for 46% of CF pathogenic variants in the South African Black population (Padoa et al., 1999) and was later confirmed by Goldman et al. (2001). No information could be found on the CF pathogenic variants in the South African Indian population. Prasad et al. (2010) reported that the most frequent CF-causing pathogenic variants in the Indian population in India include p.Phe508del (at 25%, lower than in the European populations), p.Ser549Asn (S549N), c.1525-1G > A, and c.3717 + 12191C > T (3849 + 10kbC > T). Further common pathogenic variants in the Indian population are unknown. Collectively, these studies only include a small number of affected individuals. CF Registry Data: More recent data from the South African CF Registry indicates that 70% of the 523 individuals included are homozygous for the p.Phe508del pathogenic variant, and 32% are heterozygous (Zampoli et al., 2021). However, this dataset is likely skewed towards excess reports in Caucasian patients, with individuals from other ethnic groups collectively contributing only 32% of the registry dataset (Zampoli, 2024). These data may not accurately reflect the CF incidence across the different ethnic groups due to the lack of available, accessible genetic testing or capturing of patient diagnoses from rural areas. Identifying CF carrier frequencies across all population groups is crucial for future screening. South African CF Testing Policy Aside from recommendations included in the CF consensus guidelines (Zampoli, 2017), no equivalent South African governmental nationwide CF testing programme exists compared with those offered in North America, Europe, and other high-income countries. It is recommended that NBS, including screening for CF, is implemented as a starting point to elucidate the CF rate in the South African populations, as detailed in the 2021 Clinical Guidelines for Genetic Services (Department of Health, 2021). The recent World Health Assembly Resolution (WHA) 77.5 of 2024 to accelerate progress towards reducing maternal, newborn, and child mortality in order to achieve Sustainable Development Goal (SDG) targets 3.1 and 3.2 (World Health Assembly, 2024) specifies NBS as a crucial implementation action for all member states. CF screening needs to be prioritised for implementation countrywide across both healthcare sectors. Retrospective study data The results of the retrospective study at a South African private laboratory (Lab C) show the use of three tests over the ten-year study period. Initially, testing was referred out to another laboratory, and then a kit-based test was introduced in-house, which included the most known pathogenic variants found in European-based populations. During this period, it was realised that more comprehensive testing was required to include all ethnic population groups, which led to the expansion of CF diagnostic testing to CFTR sequencing. Sequencing includes screening for all likely/pathogenic variants found across all population groups, including CNVs, and has the potential to identify all CF-causing variants. The CF30v1 kit was introduced in 2014 by Lab C and continued to be used until 2019, overlapping with CFTR sequencing until it was validated in 2016. Identifying unique pathogenic variants and copy number variations in the subsequent test results realises the value of CFTR sequencing. Patients tested elsewhere for CF who were known to be clinically affected but in whom only one pathogenic CF variant was detected were retested using CFTR sequencing. Before introducing CFTR sequencing locally in SA, samples were sent overseas to enable potential participation in CF treatment-related clinical trials ahead of the introduction of CF-modulator therapies. However, since the cost of CFTR sequencing is higher than the CF30V2 kit, it is not always the preferred first-line test. HCP Cadres requesting CF testing in South Africa Unsurprisingly, this study found that paediatricians were the HCP cadre requesting the most (74%) CF genetic testing in this cohort, followed by GPs (7%). In both the public and private healthcare sectors, paediatricians are at the clinical coalface and are often the first to examine children who may be affected by CF. In SA, while genetic counsellors may only request CF genetic testing in collaboration with a clinician, they are a valuable resource for clinicians, patients, and families, advising on appropriate CF genetic testing, taking family histories, and clarifying an individual's ethnic population through self-identity. While previous studies do not specify the ranking of HCP cadres referring patients for CF tests, they indicate that paediatricians, physicians, gynaecologists and medical geneticists contribute to test referrals, as confirmed by the current study (Baars et al., 2004). However, since paediatricians refer the majority of patients for testing, there is a possibility that other HCPs, such as GPs and adult pulmonologists, are unaware of the availability of CF testing and would require further education. Barriers to CF testing in South Africa As for many other LMICs, a common challenge in SA is the cost of genetic testing equipment, imported reagents, infrastructure, and relevant and adequate expertise/capacity. The public healthcare sector laboratories are currently significantly understaffed and underfunded, leaving many public sector-dependent affected individuals struggling to access a diagnosis and appropriate treatment (Malherbe, 2015). Genetic testing is also centralised in three main urban areas: Johannesburg, Cape Town, and Bloemfontein, with limited coverage elsewhere. Continued training of Health Professionals Council of South Africa (HPCSA)-registered medical scientists, renewed political will, and allocation of required resources are necessary. The newly launched Nngwe project (2024) encourages clinicians and scientists to pool rare disease resources (including infrastructure and capacity), data, and knowledge for the greater good of the country's rare disease community. The country urgently needs increased capacity in sparsely populated and rural areas, including improved, expanded infrastructure and greater HCP expertise in primary healthcare to identify CF clinical symptoms and improve CFTR testing referrals. Additionally, wider availability of CF sweat testing is required countrywide, with adequately trained staff to reduce the possibility of false negative and positive results. In SA, a lack of population-specific demographic data may prevent specific CF pathogenic variants from being identified across all ethnic populations when using kit-based methodology for genetic testing. Once a broader knowledge base regarding specific population groups and CF variants is established, it may be possible to custom-design targeted kits for the country's specific sub-populations, similar to the CF30 kit developed for the French population. Alternatively, reducing the cost of CFTR sequencing may alleviate the population-specific issue of CFTR genetic testing, which may be possible through initiatives such as the Nngwe project. Impact of CF therapies on CF testing in South Africa Following the international introduction of CF modulator medications in 2019, HCPs in SA requested CFTR sequencing more frequently to identify pathogenic variants and determine patients' eligibility to access these new treatments. The 2019 spike in testing in Lab C may be ascribed to CF specialist clinics' doctors requesting sequencing for patients who either lacked a paper/electronic copy of previous testing reports confirming their CF genetic diagnosis or for those patients with only one known pathogenic CFTR variant reported at the time of initial diagnosis when CFTR sequencing was unavailable. When CFTR -modulator therapies became accessible to identified "genetically eligible" individuals with specific CF variants, a genetic report demonstrating eligibility was also required to accompany the therapy request. In SA and worldwide, individuals with at least one confirmed p.Phe508del pathogenic variant who are > 2 years old are eligible for triple therapy modulators of elexacaftor-tezacaftor-ivacaftor (Trikafta™) (Vertex Pharmaceuticals Inc, 2024). However, most patients cannot access this therapy due to the high cost and the lack of approved alternative reimbursement methods, making access difficult (da Silva Filho et al., 2021). Since April 2024, eligible private CF patients in SA with medical insurance can access CF modulator benefits up to R400,000 (approximately $ 22,000) annually (Spotlight, 2024). Only 45% of eligible CF patients in SA can access this treatment, excluding most patients (Personal Communication, Dr. M. Zampoli, 28 November 2024). If Trikafta™ becomes more affordable and accessible, there may be an increased demand for CF sequencing in the country to confirm patient eligibility. The most recent FDA-approved modulator therapy, Alyftrek™, also produced by Vertex, has not yet been introduced into the SA market and is not yet available for South African patients. The need for CF sequencing is also highlighted by Amaral and Harrison (2023), who reported that although CFTR modulator therapies are now available, there is a need for further drug development to tackle the basis of CF cellular defects to improve clinical benefits for affected individuals and those with CFTR-related disorders. In this way, novel therapies could potentially treat every CFTR variant. Other prospective CF treatments being trialled globally include gene editing by various methods, such as CRISPR-Cas9, or using gene delivery with various vectors in cell models of CF (Lee et al., 2021). Currently, no known human trials are underway. The global challenge is enabling equitable treatment access for all CF patients, regardless of geography, population demographic grouping, or socioeconomic status. The new modulator treatment (Trikafta™) has been a life-changing medication for many affected individuals, but unfortunately, it leaves those with rare CF variants untreated. The International Cystic Fibrosis Foundation's campaign for CF patients to "leave no patient behind" aligns with the SDG call (World Health Organisation, 2024) and encourages academia and the pharmaceutical industry to continue searching for a cure for all CF patients worldwide (Choi and Engelhardt, 2021). Study Limitations This study included past and current testing methodologies as reported by the six included laboratories only and may not represent all South African laboratories. CF test numbers for the ten-year retrospective audit were restricted to one private pathology group (Lab C), contributing to approximately 40% of the private healthcare market share. While including additional laboratories in the study would offer a more comprehensive overview of testing available today and historically in SA, this study serves as a starting point in building the CF testing landscape in the country. The study's ten-year review of patient results did not include ethnicity/race-specific data, as this is no data indicator requested or captured during sample processing. Statistics SA breaks down the South African population into four ethnic categories; this assists in identifying inequity in healthcare services. This article does not describe the rare combinations of CF pathogenic variants to ensure compliance with the Protection of Personal Information Act (POPIA) (Government of South Africa, 2013). These data are anonymised, as rare combinations of variants may lead to the identification of affected person/s from their genetic data due to the small number of individuals affected. Conclusion The burden of disease attributed to CF in SA remains unquantified to date, with many babies and children remaining undiagnosed or misdiagnosed due to other confounding illnesses that may interfere with CF early detection and referral. This study has provided the current and historic CF testing approaches used in SA for a limited cohort of CF patients. It highlights the role of HCPs in making informed decisions when choosing a CF genetic test for their patients, emphasizing the need for HCPs' continuous education to stay abreast of new emerging technology (Walters et al., 2024). With whole CFTR gene sequencing becoming more affordable in SA, it is hoped that all children and adults suspected of having CF, regardless of geography, demographic population group, or socioeconomic status, can be tested and referred for treatment. CFTR sequencing is a key tool in identifying de novo pathogenic variants in SA's ethnically diverse population. SA has the technology, albeit with limited capacity, to test for all CF-causing pathogenic variants, including carrier testing in both healthcare sectors. A key challenge in the country is to develop more cost-effective CF sequencing testing for widespread roll-out in the public healthcare sector and low-resource settings throughout SA. It is recommended that cascade testing and improved utilisation of genetic counsellors for consultations and interpretation of genetic results should be offered to at-risk family members using targeted testing to identify familial CF carriers. Carrier identification will, in effect, contribute to knowledge of the actual burden of CF in SA and ultimately contribute to more South Africans affected by and at risk of CF being referred for genetic counselling and treatment in the country. Declarations Conflict of interest: Sarah Walters, Colleen Aldous, and Helen Malherbe declare no conflict of interest. Ethical consideration: Ethical clearance was obtained from the University of Kwa-Zulu Natal (BFC222/18). Reconfirmation of the use of anonymised patient data was received from the laboratory's chief operating officer in 2024. Acknowledgements: Ampath Laboratories for data access Funding Ampath Laboratory provided the anonymised data without coercion or specific promotion of any services or products. UKZN for PhD fee remission support. Conflicts of Interest All authors declare that they have no conflicts of interest. Ethics approval UKZN BREC: BFC222/18 Consent for publication The Ampath Laboratories chief operating officer approved the publication. Code availability Not applicable References AMARAL, M. D. & HARRISON, P. T. 2023. Development of novel therapeutics for all individuals with CF (the future goes on). Journal of Cystic Fibrosis , 22, S45-S49. BAARS, M. J. H., HENNEMAN, L. & TEN KATE, L. P. 2004. Preconceptional cystic fibrosis carrier screening: Opinions of general practitioners, gynecologists, and pediatricians in the Netherlands. Genetic Testing , 8, 431–436. BURGENER, E. B. & CORNFIELD, D. N. 2023. Delivering a New Future for People With Cystic Fibrosis. Pediatrics , 152. CHOI, S. H. & ENGELHARDT, J. F. 2021. Gene Therapy for Cystic Fibrosis: Lessons Learned and Paths Forward. Mol Ther , 29, 428–430. COWLING, N. 2024. Private healthcare in South Africa - statistics and facts [Online]. Available: statistica.com/topics/11421/private-healthcare-in-South-Africa/#topicOverview [Accessed 28/04/2024 2024]. DA SILVA FILHO, L., ZAMPOLI, M., COHEN-CYMBERKNOH, M. & KABRA, S. K. 2021. Cystic fibrosis in low and middle-income countries (LMIC): A view from four different regions of the world. Paediatr Respir Rev , 38, 37–44. DE MELO, A. C. V., DE SOUZA, K. S. C., DA SILVA, H. P. V., MAIA, J. M. C., DANTAS, V. M., BEZERRA, J. F. & DE REZENDE, A. A. 2022. Screening by high-throughput sequencing for pathogenic variants in cystic fibrosis: Benefit of introducing personalized therapies. J Cell Mol Med , 26, 5943–5947. DEIGNAN, J. L., GREGG, A. R., GRODY, W. W., GUO, M. H., KEARNEY, H., MONAGHAN, K. G., RARAIGH, K. S., TAYLOR, J., ZEPEDA-MENDOZA, C. J., ZIATS, C. & [email protected] , A. B. O. D. E. A. 2023. Updated recommendations for CFTR carrier screening: A position statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med , 25, 100867. DEPARTMENT OF HEALTH 2021. Clinical Guidelines for Genetics Services 2021. Pretoria. DODGE, J. A. D., E 2002. CF or not CF? That is the question. Journal of Cystic Fibrosis , 1, 3–4. FARRELL, P. M., WHITE, T. B., REN, C. L., HEMPSTEAD, S. E., ACCURSO, F., DERICHS, N., HOWENSTINE, M., MCCOLLEY, S. A., ROCK, M., ROSENFELD, M., SERMET-GAUDELUS, I., SOUTHERN, K. W., MARSHALL, B. C. & SOSNAY, P. R. 2017. Diagnosis of Cystic Fibrosis: Consensus Guidelines from the Cystic Fibrosis Foundation. J Pediatr , 181S, S4-S15 e1. GIBSON, L. E. & COOKE, R. E. 1959. A Test for Concentration of Electrolytes in Sweat in Cystic Fibrosis of the Pancreas Utilizing Pilocarpine by Iontophoresis. Pediatrics , 23, 545–549. GOLDMAN, A., LABRUM, R., CLAUSTRES, M., DESGEORGES, M., GUITTARD, C., WALLACE, A. & RAMSAY, M. 2001. The molecular basis of cystic fibrosis in South Africa. Clin Genet , 59, 37–41. GOVERNMENT OF SOUTH AFRICA 2013. Act 4 of 2013 The Protection of Personal Information Act. Cape Town. GRAEBER, S. Y. & MALL, M. A. 2023. The future of cystic fibrosis treatment: from disease mechanisms to novel therapeutic approaches. The Lancet , 402, 1185–1198. GUO, J., GARRATT, A. & HILL, A. 2022. Worldwide rates of diagnosis and effective treatment for cystic fibrosis. J Cyst Fibros , 21, 456–462. HITZEROTH, H. W., PETERSEN, E. M., HERBERT, J. & DENTER, M. 1991. Preventing cystic fibrosis in the RSA. S Afr Med J , 80, 92 − 8. HPCSA. 2022. Pretoria: HPCSA. Available: https://hpcsaonline.custhelp.com/app/i_reg_form [Accessed 20/06/2022 2022]. KAPOOR, V., SHASTRI, S. S., KABRA, M., KABRA, S. K., RAMACHANDRAN, V., ARORA, S., BALAKRISHNAN, P., DEORARI, A. K. & PAUL, V. K. 2006. Carrier frequency of F508del mutation of cystic fibrosis in Indian population. J Cyst Fibros , 5, 43 − 6. KEREM, B., ROMMENS, J. M., BUCHANAN, J. A., MARKIEWICZ, D., COX, T. K., CHAKRAVARTI, A., BUCHWALD, M. & TSUI, L. C. 1989. Identification of the cystic fibrosis gene: genetic analysis. Science , 245, 1073-80. LEE, J. A., CHO, A., HUANG, E. N., XU, Y., QUACH, H., HU, J. & WONG, A. P. 2021. Gene therapy for cystic fibrosis: new tools for precision medicine. J Transl Med , 19, 452. MALHERBE, C., ALDOUS 2015. Need for services for the care and prevention of congenital disorders in South Africa as the cou. MALHERBE, H. L., BONHAM, J., CARRIHILL, M., CHETTY, K., CONRADIE, E. H., DERCKSEN, M., GOEIMAN, H., GOMES, M. C. M., KLOPPER, B., MCKERROW, N., PADILLA, C., PILLAY, T. S., ROUSSOT, B., SATEKGE, T. M., URBAN, M., VAN DER WATT, G., VREEDE, H., WEBSTER, D., ZAMPOLI, M. & VORSTER, B. C. 2024. Newborn screening in South Africa: the past, present, and plans for the future. Rare Disease and Orphan Drugs Journal , 3. MISHRA, A., GREAVES, R. & MASSIE, J. 2005. The relevance of sweat testing for the diagnosis of cystic fibrosis in the genomic era. Clin Biochem Rev , 26, 135 − 53. NATIONAL DEPARTMENT OF HEALTH 2000. National Health Laboratory Service Act 37 of 2000. Pretoria, South Africa. NNGWE PROJECT. 2024. Nngwe Project - One life matters [Online]. Potchefstroom, South Africa: Nngwe. Available: https://nngwe.org.za/ [Accessed 23/11/2024 2024]. PADOA, C., GOLDMAN, A., JENKINS, T. & RAMSAY, M. 1999. Cystic fibrosis carrier frequencies in populations of African origin. J Med Genet , 36, 41 − 4. PRASAD, R., SHARMA, H. & KAUR, G. 2010. Molecular basis of cystic fibrosis disease: an Indian perspective. Indian J Clin Biochem , 25, 335 − 41. SPOTLIGHT 2024. Fight not yet over as case against Vertex is dropped after cystic fibrosis medicine price cut. In : SECTION 27 (ed.) In-depth, public interest health journalism. South Africa. STATISTICS SOUTH AFRICA 2024. Mid-year population estimates. In : AFRICA, S. S. (ed.). Pretoria, South Africa. STEWART, C. & PEPPER, M. S. 2016. Cystic fibrosis on the African continent. Genet Med , 18, 653 − 62. TO-MAI, X. H., NGUYEN, H. T., NGUYEN-THI, T. T., NGUYEN, T. V., NGUYEN-THI, M. N., THAI, K. Q., LAI, M. T. & NGUYEN, T. A. 2024. Prevalence of common autosomal recessive mutation carriers in women in the Southern Vietnam following the application of expanded carrier screening. Sci Rep , 14, 7461. VAN RENSBURG, J., ALESSANDRINI, M., STEWART, C. & PEPPER, M. S. 2018. Cystic fibrosis in South Africa: A changing diagnostic paradigm. S Afr Med J , 108, 624–628. VERTEX PHARMACEUTICALS INC. 2024. Available: https://www.trikafta.com/ [Accessed 2/12/2024 2024]. WALDMAN, S., BACKENROTH, D., HARNEY, E., FLOHR, S., NEFF, N. C., BUCKLEY, G. M., FRIDMAN, H., AKBARI, A., ROHLAND, N., MALLICK, S., OLALDE, I., COOPER, L., LOMES, A., LIPSON, J., CANO NISTAL, J., YU, J., BARZILAI, N., PETER, I., ATZMON, G., OSTRER, H., LENCZ, T., MARUVKA, Y. E., LAMMERHIRT, M., BEIDER, A., RUTGERS, L. V., RENSON, V., PRUFER, K. M., SCHIFFELS, S., RINGBAUER, H., SCZECH, K., CARMI, S. & REICH, D. 2022. Genome-wide data from medieval German Jews show that the Ashkenazi founder event pre-dated the 14th century. Cell , 185, 4703–4716 e16. WALTERS, S., ALDOUS, C. & MALHERBE, H. 2024. Knowledge, attitudes, and practices of primary healthcare practitioners in low- and middle-income countries: a scoping review on genetics. J Community Genet , 15, 461–474. WESTWOOD ATR, I. J. 1996. Cystic fibrosis and "kwashiorkor". S Afr Med J. WESTWOOD, T. & BROWN, R. 2006. Cystic fibrosis in black patients: Western Cape experiences. S Afr Med J , 96, 288-9. WORLD HEALTH ASSEMBLY 2024. Seventy-seventh World Health Assembly Resolution 77.5. Accelerate progress towards reducing maternal, newborn and child mortality in order to achieve Sustainable Development Goal targets 3.1 and 3.2. WORLD HEALTH ORGANISATION. 2024. Targets of Sustainable Developmental Goal3 to ensure healthy lives and promote well-being for all at all ages [Online]. World Health Organization,. Available: https://www.who.int/europe/about-us/our-work/sustainable-development-goals/targets-of-sustainable-development-goal-3 [Accessed 3/12/2024]. WORLD HEALTH ORGANIZATION 2004. The molecular genetic epidemiology of cystic fibrosis. Report of a joint meeting of WHO/ECFTN/ICF (M) A/ECFS. Geneva, WHO . ZAMPOLI, M., VERSTRAETE, J., FRAUENDORF, M., KASSANJEE, R., WORKMAN, L., MORROW, B. M. & ZAR, H. J. 2021. Cystic fibrosis in South Africa: spectrum of disease and determinants of outcome. ERJ Open Res , 7. ZAMPOLI M, V. J., FRAUENDORF M AND THE CF STEERING COMMITTEE 2021a. South African Cystic Fibrosis Patient Additional Declarations No competing interests reported. Supplementary Files Supplementarytable1ListofCFTRmutationsinkits.docx Supplementarytable2.docx Cite Share Download PDF Status: Published Journal Publication published 25 Sep, 2025 Read the published version in Journal of Community Genetics → Version 1 posted Editorial decision: Revision requested 02 May, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 22 Apr, 2025 Reviews received at journal 26 Mar, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers invited by journal 26 Mar, 2025 Editor assigned by journal 25 Mar, 2025 Submission checks completed at journal 25 Mar, 2025 First submitted to journal 17 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6247428","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436313948,"identity":"fed64f13-dc3c-4824-b68a-138ae66b74bd","order_by":0,"name":"Sarah Walters","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie3RMUvDQBTA8Xc8OJeLrhcEO/gF7ggUxEi/yh2FuAQXl0z1SqFZ8gFSUvAzuLkZOLBLoatulQ5dHDoWVDCNm3CY0eH+48GP944H4PP9w04Qa/v1Gd+R3LQP4k8S5lSvA5MoLGpiOhGxYuciMFYdlaojAcsoDx+Tm2C23W4Y2KhXGbLbw6jnEmQSPHO5jG/DKpWThvTJvMawACqNgyAeJ1zRhDxUKTmQGLmCUwBGXIQi6/OaWvL0unhrCeUKPwD4wEUYskiOp1aPS/hZjDVDmylCuwhHqjewTCJSpHI2F9cR53p6UQg1dJHBytYWsviM5Iv17j27lPfl0L7ss9GVi/yqvcrh4x3O4/P5fD5335XKUflnQzuFAAAAAElFTkSuQmCC","orcid":"","institution":"University of Kwa-Zulu Natal","correspondingAuthor":true,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Walters","suffix":""},{"id":436313949,"identity":"fbded94c-771a-46cf-b4d5-b144be09b6cc","order_by":1,"name":"Colleen Aldous","email":"","orcid":"","institution":"University of Kwa-Zulu Natal","correspondingAuthor":false,"prefix":"","firstName":"Colleen","middleName":"","lastName":"Aldous","suffix":""},{"id":436313950,"identity":"826fc6ee-79bd-49e6-9045-5948aed92a2c","order_by":2,"name":"Helen Malherbe","email":"","orcid":"","institution":"University of the North-West","correspondingAuthor":false,"prefix":"","firstName":"Helen","middleName":"","lastName":"Malherbe","suffix":""}],"badges":[],"createdAt":"2025-03-17 20:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6247428/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6247428/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12687-025-00810-6","type":"published","date":"2025-09-25T15:58:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80051843,"identity":"5bf2ead3-116c-4607-b590-18e6aa70e236","added_by":"auto","created_at":"2025-04-07 10:30:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":197825,"visible":true,"origin":"","legend":"\u003cp\u003eThe use of and timing of three \u003cem\u003eCFTR\u003c/em\u003etesting methodologies in 2013-2022, including the number of samples received for CF testing from Laboratory C (private sector).\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/fc33cb83add898d74d3cbea3.jpg"},{"id":80050934,"identity":"23632921-6193-4d12-a6a7-9fbef72a898e","added_by":"auto","created_at":"2025-04-07 10:22:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":168533,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of negative, positive, and carrier findings across the retrospective study in Laboratory C.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/1fb63ab155678cee9bab58c5.jpg"},{"id":80050928,"identity":"73abef20-cc3d-4220-9f55-c71d9a5bc3a8","added_by":"auto","created_at":"2025-04-07 10:22:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":289846,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart showing the number of tests requested by different HCP cadres from the 2013–2022 dataset from one private laboratory in South Africa. Data were converted to a logarithmic scale to include outliers; data labels are actual numbers. See Supplementary File 2.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/0f10e21c232894f5842926f6.jpg"},{"id":92431337,"identity":"6308e865-9336-4d58-906c-8db89fa664bc","added_by":"auto","created_at":"2025-09-29 16:09:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1141519,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/c0d46856-c73c-4afd-b5fe-7a885fe48209.pdf"},{"id":80050926,"identity":"81f2ab16-cc8b-4528-85af-dd1ac66c0a73","added_by":"auto","created_at":"2025-04-07 10:22:59","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27874,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable1ListofCFTRmutationsinkits.docx","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/9b2487c29510c60166c3458e.docx"},{"id":80053135,"identity":"49d367a0-3ee8-4ef0-b698-9a099eabdfa9","added_by":"auto","created_at":"2025-04-07 10:46:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17939,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6247428/v1/8070fdb2b06f35835196d9c5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic Testing for Cystic Fibrosis in South Africa: A 10-Year Retrospective Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCystic Fibrosis and Genetic Testing\u003c/p\u003e \u003cp\u003eCystic fibrosis (CF) is a common, autosomal recessive condition in European-descent individuals with lower frequencies in other populations (World Health Organization, 2004). It can be detected \u003cem\u003ein utero\u003c/em\u003e or at birth due to symptoms like meconium ileus or failure to thrive and later in childhood with recurrent respiratory infections and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e colonisation. Advances in CF-specific modulator therapies have significantly improved life expectancy, increasing from 17 years in 1970 to 53 years in 2021 (Burgener and Cornfield, 2023).\u003c/p\u003e \u003cp\u003eThe CF transmembrane conductance regulator (\u003cem\u003eCFTR\u003c/em\u003e) gene responsible for causing CF was identified in 1989 (Kerem et al., 1989), expanding knowledge of CF genetics. The international CFTR2 database from Johns Hopkins University, USA ([\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cftr2.org\u003c/span\u003e\u003cspan address=\"https://cftr2.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed 13/2/2025]) lists 1085 CF-causing variants, 55 variants of varying clinical consequence, and 27 non-CF-causing variants, while ClinVar ([\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed 13/2/2025]) reports 5435 \u003cem\u003eCFTR\u003c/em\u003e variants, including 1165 pathogenic variants plus an additional 500 likely pathogenic variants.\u003c/p\u003e \u003cp\u003eSweat chloride testing remains the global standard for CF screening (Farrell et al., 2017, Gibson and Cooke, 1959), with genetic confirmation recommended after two positive sweat tests on separate occasions (Mishra et al., 2005, Cowling, 2024). Newborn screening (NBS) for CF is available in mainly high-income countries where CF is common but remains largely unavailable in most low- and middle-income countries (LMICs) (da Silva Filho et al., 2021).\u003c/p\u003e \u003cp\u003eTreatment for CF has progressed over the decades, focusing on better drugs, nutritional support, and advances in physiotherapy. Genetic confirmation of a CF diagnosis in light of new targeted modulator treatments is essential (de Melo et al., 2022).\u003c/p\u003e \u003cp\u003eIn South Africa (SA), CF testing by linkage analysis was introduced in 1987 (Hitzeroth et al., 1991). It was replaced by targeted testing for the common European population CF pathogenic variant, Delta F508 (also known as ΔF508, or p.Phe508del), later replaced by targeted \u003cem\u003eCFTR\u003c/em\u003e variant testing (Van Rensburg et al., 2018). Whole \u003cem\u003eCFTR\u003c/em\u003e sequencing by next-generation sequencing (NGS) and copy number variation (CNV) analysis are now available locally. Families with a history of CF may be offered NBS screening (at their own cost) via the country's private healthcare sector (Malherbe et al., 2024). Modulator therapies were introduced in 2019, dramatically improving clinical outcomes for most patients with CF who are genetically eligible (Graeber and Mall, 2023, de Melo et al., 2022).\u003c/p\u003e \u003cp\u003eSouth Africa's Healthcare Context\u003c/p\u003e \u003cp\u003eSA, an upper-middle-income country with a population of 63\u0026nbsp;million, is ethnically diverse, with 81.7% classified as Black African, 8,5% as Coloured, 7.2% as White, and 2.6% as Indian/Asian (Statistics South Africa, 2024). The country currently operates a dual healthcare system. The government-funded public healthcare sector serves approximately 84% of the population (52\u0026nbsp;million people), while 16% of the population, equating to 9.7\u0026nbsp;million people, access private healthcare (Cowling, 2024). CF genetic testing is available through the government-subsidised National Health Laboratory Service (NHLS) (National Department of Health, 2000), catering to the public sector and private pathology laboratories servicing patients on private healthcare insurance. Public sector testing remains limited, leading to result delays due to batching, reagent availability, lack of capacity, and other challenges.\u003c/p\u003e \u003cp\u003eIndividuals in the public sector may have limited access to CF testing, including sweat tests and genetic testing, thus delaying treatment due to geographical distance, availability of equipment, healthcare provider (HCP) awareness, and expertise. Currently, CF genetic testing in the public sector uses targeted variant kits covering pan-ethnic variants in \u003cem\u003eCFTR\u003c/em\u003e, but it is limited to reporting specific pathogenic variants only.\u003c/p\u003e \u003cp\u003eWhile new technology has emerged over the decades globally, recent studies have yet to be published on CF genetic testing currently implemented in SA, and little is known about the CF pathogenic variants tested for in South African healthcare.\u003c/p\u003e \u003cp\u003eCF in South Africa\u0026mdash;carrier rate and birth prevalence\u003c/p\u003e \u003cp\u003eWhile CF carriers occur in all population groups worldwide in varying frequencies, only data for carriers in European and North American populations have been well documented. In individuals of reproductive age, carrier testing is essential to inform reproductive decision-making. Limited data is available for specific countries or population groups in many LMICs. For example, in India, carrier screening is limited to testing for only one common pathogenic variant. This carrier rate is estimated to be 1 in 238 (Kapoor et al., 2006), while carrier rates for CF in Vietnam were reported as 1 in 23 (To-Mai et al., 2024).\u003c/p\u003e \u003cp\u003eThe prevalence of CF in all 195 countries worldwide is yet to be documented. Guo et al. (2022) explored the worldwide rate of CF and reported on 94 countries where an estimated 162,428 people live with CF, but a diagnosis was made in only 105,352 of these individuals. These data provide an approximate diagnosed prevalence of between 0.17 and 0.27 affected individuals per 10000 people. In Africa, nine countries provided an estimated number of 1665 affected individuals, with the majority from Egypt and SA, with a prevalence of 0.5 affected individuals per 10000. However, this figure is likely highly under-reported. No information was available in 40 other African countries (primarily LMICs). A review of CF molecular epidemiology in Africa in 2016 showed that 12 of the 49 countries on the African continent have published relevant CF data (Stewart and Pepper, 2016).\u003c/p\u003e \u003cp\u003eIn SA, CF carrier frequencies vary between ethnic groups and were reported in the late 1990s as approximately 1 in 20 for the Caucasian population, 1 in 55 in the Coloured population, and 1 in 34\u0026ndash;90 for the Black populations (Padoa et al., 1999). More recent studies indicate the CF birth prevalence as 1 in 3000 in the Caucasian population, 1 in 10,300 in the Coloured population, and 1 in 784\u0026thinsp;\u0026minus;\u0026thinsp;13,924 in the Black population (Zampoli et al., 2021). Both in SA and other countries worldwide, a higher carrier rate of CF and other specific genetic conditions have been documented for the Ashkenazi-Jewish population due to homogeneity and bottlenecks in the population diaspora (Waldman et al., 2022).\u003c/p\u003e \u003cp\u003eNewborn screening for CF in SA is currently only available in the private healthcare sector for families with a CF family history. It is not offered in public healthcare (Zampoli M, 2021b) (Malherbe et al., 2024). As a result, a CF diagnosis generally only occurs after the neonatal period, several weeks or months after birth, thus delaying treatment and allowing disease progression.\u003c/p\u003e \u003cp\u003eA South African Cystic Fibrosis Patient Registry was established in 2018, with the latest report including 523 affected individuals (Zampoli M, 2021a). Based on the reported carrier rates in the four South African ethnic groups, CF is still thought to be severely underdiagnosed in the country, especially in the Black population, due to confounding conditions such as malnutrition, TB, and HIV, which may mask CF symptoms (Westwood and Brown, 2006). CF may have different disease presentations and phenotypes and may vary between ethnic population groups. Anecdotally, CF is still considered a Caucasian disease in SA.\u003c/p\u003e \u003cp\u003eWithin this South African context, HCP awareness of current, appropriate CF genetic testing may need improvement due to new and changing testing methodologies. The aims of this study were: 1) To provide an overview of current and historic genetic tests available/implemented for CF in SA across both healthcare sectors; 2) Undertake a ten-year, retrospective study of CF diagnostic testing for private patients undertaken by one of SA's larger private pathology laboratories, and; 3) Undertake an analysis of HCPs requesting these tests.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe methodology used in this study was an observational descriptive retrospective review of \u0026nbsp;CF genetic test methodologies, genetic results and HCP categories.\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eCurrent CF genetic tests used in SA across public and private healthcare\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFour private and two of the three public NHLS genetics laboratories were contacted telephonically by the first author in 2019. The lead scientist in each molecular genetics laboratory was asked to specify which CF tests and methodology/kits are used in their laboratory. The two NHLS laboratories included (Johannesburg and Cape Town) represented CF testing in the public healthcare sector (the NHLS genetics laboratory offering CF testing in Bloemfontein was excluded), and these were compared with four private laboratories located in Johannesburg, Cape Town, and Centurion. Once these data were received and anonymised, the pathogenic variants included in each CF testing kit were identified using publicly available information for each manufacturer. These data were collated into a data extraction table adapted from the template in the South African 2017 CF consensus guidelines (Zampoli, 2017). See Supplementary File 1 for data points extracted.\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003eRetrospective audit of CF tests used in one private genetic laboratory\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe retrospective review analysed \u003cem\u003eCFTR\u003c/em\u003e testing undertaken over ten years (January 2013 to December 2022) from one private laboratory in Gauteng. A ten-year timeframe was chosen to illustrate changes and advances in \u003cem\u003eCFTR\u003c/em\u003e testing during this period and the future potential to improve CF testing for all South African ethnic populations. The private laboratory\u0026apos;s Chief Executive Officer, Chief Operations Officer, and the Head of the Laboratory\u0026apos;s Genetics Department (HOD) granted the gatekeeper permission to access these de-identified data. The HOD internally requested the required data from the laboratory\u0026apos;s data officer via email. These data included the year of testing, test code, age, sex, test results (positive/carrier/negative) and cadre of HCP requesting the test. Descriptive statistics were used to interpret the data. Self-identified population grouping (i.e. ethnicity) is not a data point collected on the laboratory\u0026apos;s test requisition form and, therefore, could not be included.\u0026nbsp;\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003eAnalysis of HCPs requesting CF tests\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe data collected from the 10-year retrospective study (point 2) above included a code for the cadre of HCPs who requested CF testing. This code was converted to the HCP qualifications/speciality. The speciality type was documented using Excel\u0026reg; and plotted on a logarithmic scale. The positive, negative, and carrier results were also documented. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthical approval for the study was obtained from the UKZN Research Ethics Committee (BFC222/18). De-identified retrospective data were used in compliance with ethical and applicable data protection standards and regulations. No individual could be identified from the anonymised data; therefore, informed consent was deemed unnecessary as per institutional and international ethical frameworks, which permit using anonymised data for research without explicit consent.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eCurrent and Historic CFTR Genetic Testing Methods Used in South Africa:\u003c/p\u003e \u003cp\u003eData compiled from the six South African laboratories (two public and four private) revealed that four CF kits and whole \u003cem\u003eCFTR\u003c/em\u003e sequencing were used in the country during the study period. The CF test kits were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCF30v2 (Elucigene),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCFEU2v1 (which replaced CF30v2)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCFTR Core (Devyser AB)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCF Genotyping Assay (Abbott)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eElucigene\u0026reg; CF30v2 is a gel-based assay used in the French national neonatal CF screening programme. It detects 30 pathogenic variants, most common in the French population.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eElucigene\u0026reg; CF-EU2v1 is a pan-European CF testing kit to identify 50 pathogenic variants and analyse the poly-T tract. All NHLS laboratories offering kit-based testing utilise the same kit.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDevyser\u0026reg; CFTR Core detects the 36 most common pathogenic variants of European origin.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe Abbott\u0026reg; CF Genotyping assay detects 33 common pathogenic variants as recommended by the American College of Medical Genetics (ACMG) for the \"general population\".\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCurrent and previous \u003cem\u003eCFTR\u003c/em\u003e testing methodology implemented at six laboratories in South Africa.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLab A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLab B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLab C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLab E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLab F\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCF30v2 (Elucigene)\u003csup\u003e1\u003c/sup\u003e,\u003c/p\u003e \u003cp\u003eCFEU2v1 (Elucigene)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCF30v2 (Elucigene),\u003c/p\u003e \u003cp\u003eCFEU2v1 (Elucigene)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2013\u0026ndash;2014: ΔF508\u003c/p\u003e \u003cp\u003e2014\u0026ndash;2016: CF30v2 (Elucigene)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e2016-current:\u003c/p\u003e \u003cp\u003eWhole \u003cem\u003eCFTR\u003c/em\u003e sequencing\u0026thinsp;+\u0026thinsp;CNV analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCFTR Core (Devyser)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePreviously \u003cem\u003eCFTR\u003c/em\u003e sequencing, and now outsourced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCF Genotyping Assay (Abbott)\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFifty-nine pathogenic variants were included in the four kits identified. Information regarding the pathogenic variants in each kit was obtained from the manufacturers (details in Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe CF30v2 kit includes three pathogenic variants common in the Afrikaner population, including 3272-26A\u0026thinsp;\u0026gt;\u0026thinsp;G, 394delTT, and G542X. The only known common pathogenic variants in the South African Black (c.2988\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A) and Indian populations (p.Phe508del) were present in all kits. Both p.Phe508del and c.2988\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A pathogenic variants are also found in the local Coloured population.\u003c/p\u003e \u003cp\u003eRetrospective study: CF audit of one private laboratory\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGenetic Data and Test Method Evolution\u003c/h2\u003e \u003cp\u003eThe collated data from one private laboratory (Lab C) from 2013\u0026ndash;2022 showed how CF testing methodology has changed and evolved (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Initially, testing was performed using a kit for a limited number of pathogenic variants sent to a referral laboratory (2013\u0026ndash;2014). Subsequently, a kit-based method was performed in-house (2014\u0026ndash;2019), as outlined in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Finally, next-generation sequencing (NGS) of the \u003cem\u003eCFTR\u003c/em\u003e gene (including CNVs) was introduced (2016\u0026ndash;2022).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn-house whole \u003cem\u003eCFTR\u003c/em\u003e sequencing began in 2016 and gradually increased in volume as the benefit of \u003cem\u003eCFTR\u003c/em\u003e sequencing was realised by referring HCPs. The use of targeted variant kits was phased out as sample numbers declined in favour of sequencing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResults of patients tested:\u003c/h3\u003e\n\u003cp\u003eOver the ten-year study period, 1787 individuals were tested for CF at Laboratory C (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Of these, 13 results could not be traced. Twenty-eight results had one variant of uncertain significance (VUS), and two results had two VUSs. These 43 results (2.4%) were excluded from the analysis, as VUSs cannot confirm or refute a CF diagnosis until future possible reclassification. Of the remaining 1744 available patient results, 108 results (6.2%) had two CF-causing variants and 157 (9%) carrier results (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 108 results with two \u003cem\u003eCFTR\u003c/em\u003e likely/pathogenic variants were compared with the 50 variants detected by the CFEU2v1 test kit used in the public sector. Of these, 16 patients (14.8%) had pathogenic variants which the CFEU2v1 kit would not detect. Of the 157 with carrier results, 97 patients' carrier results (61.8%) could be identified by the CFEU2v1 test kit. One variant has since been classified as benign, and 15 carrier statuses (15.5%) would not have been detected using the CFEU2v1 test kit methodology.\u003c/p\u003e \u003cp\u003eBreakdown of Referring HCPs:\u003c/p\u003e \u003cp\u003eOf the 27 different HCP cadres referring the 1787 individuals for CF testing, the majority were paediatricians (1288/1787, 72%), followed by GPs (121/1787, 7%); shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary File 2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated genetic testing for CF patients in SA across the public and private sectors, analysing CF testing methodologies used in six laboratories and a decade of CF test results from one private laboratory. The detection rate at Lab C was 6%, with paediatricians, GPs, and specialist physicians being the primary test requestors. This study highlights the role of HCPs in making informed decisions when choosing an appropriate CF genetic test for their patients. It emphasises the need for continuous HCP education to stay abreast of new and emerging testing and treatment technologies.\u003c/p\u003e \u003cp\u003eFour kit-based methodologies are used, with \u003cem\u003eCFTR\u003c/em\u003e sequencing introduced in Lab C in 2016. Public-sector CF kit choices are influenced by cost, available technology, and known CF variant profiles in the population, while private labs likely consider similar factors. Given the incomplete understanding of CF genetics across all South African populations, Lab C continues to offer NGS-based \u003cem\u003eCFTR\u003c/em\u003e sequencing. Complete gene sequencing is essential to improve patient outcomes by identifying all variants and assessing the new modulator therapy use. This study confirmed 16 CF diagnoses and the identification of 15 carriers, which are not detectable by the kit-based methodology, aiding in treatment decisions and reproductive decision-making.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCFTR\u003c/em\u003e sequencing is crucial for identifying CF-causing variants in diverse populations and discovering new pathogenic variants. It could inform a tailored, SA-specific kit-based testing approach. Population-based genetic data is essential for improving public health strategies and early CF management in SA.\u003c/p\u003e \u003cp\u003eInternational recommendations for testing:\u003c/p\u003e \u003cp\u003eEuropean recommendations for CF genetic testing at and after birth include primary (population-based targeted testing) and comprehensive (increased number of variants in targeted genetic testing, or \u003cem\u003eCFTR\u003c/em\u003e sequencing) screening panels (Dodge, 2002), both of which are available in SA, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The American College of Medical Genetics and Genomics (ACMG) recommends that \"screening for all CF pathogenic variants at a carrier frequency of more than 1% of a population group is ideal\". This statement also indicates that at least 23 pathogenic variants should be included for CF carrier testing and screening and that comprehensive methods of \u003cem\u003eCFTR\u003c/em\u003e testing should be used if necessary (Deignan et al., 2023).\u003c/p\u003e \u003cp\u003eThe South African setting for testing:\u003c/p\u003e \u003cp\u003eIdeally, CF genetic testing in SA should be based on pathogenic variants found in all the SA ethnic population groups. However, like the global situation, the South African Caucasian population has the most CF genetic data currently available since CF has been diagnosed mainly in this population. CF is thought to be uncommon in the Black, Indian, and Coloured populations, and earlier studies show how a CF diagnosis can be missed in Black patients (Westwood and Brown, 2006). CF may also be underdiagnosed in non-Caucasian ethnic groups due to confounding factors, including rare pathogenic variants and varying phenotypes (Westwood ATR, 1996). Following international standards for CF testing, most CF pathogenic variants in the Caucasian population are likely to be detected using the kit-based method. \u003cem\u003eCFTR\u003c/em\u003e sequencing would also be required for individuals with only one pathogenic variant, significantly adding to the cost of testing. However, sequencing would be more beneficial as a first-line test in populations with an unknown underlying genetic basis.\u003c/p\u003e \u003cp\u003eMolecular basis of CF in South Africa\u003c/p\u003e \u003cp\u003eThe molecular basis of CF in SA was previously discussed in a 2001 paper (Goldman et al., 2001), including a patient cohort across three of the four ethnic population groups, in which p.Phe508del accounted for 76% of the CF variant of 192 patients, indicating a CF founder effect in the Afrikaner Caucasian population. A further 11 pathogenic variants accounted for 6% of CF chromosomes in the same Afrikaner population. In the same study, approximately 91% of CF-causing pathogenic variants were detected using the CF30v2 kit (based on French population data), also in the Caucasian population (Goldman et al., 2001).\u003c/p\u003e \u003cp\u003eTwo pathogenic variants, p.Phe508del and c.2988\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A; p.? (3120\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A), were found in this South African Coloured population at frequencies of 43% and 29%, respectively. However, only 14 Coloured and 12 Black patients were included in the study, and the South African Indian population was either excluded or testing had not been requested.\u003c/p\u003e \u003cp\u003eThe c.2988\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A; p.? (3120\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A) pathogenic variant accounted for 46% of CF pathogenic variants in the South African Black population (Padoa et al., 1999) and was later confirmed by Goldman et al. (2001).\u003c/p\u003e \u003cp\u003eNo information could be found on the CF pathogenic variants in the South African Indian population. Prasad et al. (2010) reported that the most frequent CF-causing pathogenic variants in the Indian population in India include p.Phe508del (at 25%, lower than in the European populations), p.Ser549Asn (S549N), c.1525-1G\u0026thinsp;\u0026gt;\u0026thinsp;A, and c.3717\u0026thinsp;+\u0026thinsp;12191C\u0026thinsp;\u0026gt;\u0026thinsp;T (3849\u0026thinsp;+\u0026thinsp;10kbC\u0026thinsp;\u0026gt;\u0026thinsp;T). Further common pathogenic variants in the Indian population are unknown. Collectively, these studies only include a small number of affected individuals.\u003c/p\u003e \u003cp\u003eCF Registry Data:\u003c/p\u003e \u003cp\u003eMore recent data from the South African CF Registry indicates that 70% of the 523 individuals included are homozygous for the p.Phe508del pathogenic variant, and 32% are heterozygous (Zampoli et al., 2021). However, this dataset is likely skewed towards excess reports in Caucasian patients, with individuals from other ethnic groups collectively contributing only 32% of the registry dataset (Zampoli, 2024). These data may not accurately reflect the CF incidence across the different ethnic groups due to the lack of available, accessible genetic testing or capturing of patient diagnoses from rural areas. Identifying CF carrier frequencies across all population groups is crucial for future screening.\u003c/p\u003e \u003cp\u003eSouth African CF Testing Policy\u003c/p\u003e \u003cp\u003eAside from recommendations included in the CF consensus guidelines (Zampoli, 2017), no equivalent South African governmental nationwide CF testing programme exists compared with those offered in North America, Europe, and other high-income countries. It is recommended that NBS, including screening for CF, is implemented as a starting point to elucidate the CF rate in the South African populations, as detailed in the 2021 Clinical Guidelines for Genetic Services (Department of Health, 2021). The recent World Health Assembly Resolution (WHA) 77.5 of 2024 to accelerate progress towards reducing maternal, newborn, and child mortality in order to achieve Sustainable Development Goal (SDG) targets 3.1 and 3.2 (World Health Assembly, 2024) specifies NBS as a crucial implementation action for all member states. CF screening needs to be prioritised for implementation countrywide across both healthcare sectors.\u003c/p\u003e \u003cp\u003eRetrospective study data\u003c/p\u003e \u003cp\u003eThe results of the retrospective study at a South African private laboratory (Lab C) show the use of three tests over the ten-year study period. Initially, testing was referred out to another laboratory, and then a kit-based test was introduced in-house, which included the most known pathogenic variants found in European-based populations. During this period, it was realised that more comprehensive testing was required to include all ethnic population groups, which led to the expansion of CF diagnostic testing to \u003cem\u003eCFTR\u003c/em\u003e sequencing. Sequencing includes screening for all likely/pathogenic variants found across all population groups, including CNVs, and has the potential to identify all CF-causing variants. The CF30v1 kit was introduced in 2014 by Lab C and continued to be used until 2019, overlapping with \u003cem\u003eCFTR\u003c/em\u003e sequencing until it was validated in 2016. Identifying unique pathogenic variants and copy number variations in the subsequent test results realises the value of \u003cem\u003eCFTR\u003c/em\u003e sequencing.\u003c/p\u003e \u003cp\u003ePatients tested elsewhere for CF who were known to be clinically affected but in whom only one pathogenic CF variant was detected were retested using \u003cem\u003eCFTR\u003c/em\u003e sequencing. Before introducing \u003cem\u003eCFTR\u003c/em\u003e sequencing locally in SA, samples were sent overseas to enable potential participation in CF treatment-related clinical trials ahead of the introduction of CF-modulator therapies. However, since the cost of \u003cem\u003eCFTR\u003c/em\u003e sequencing is higher than the CF30V2 kit, it is not always the preferred first-line test.\u003c/p\u003e \u003cp\u003eHCP Cadres requesting CF testing in South Africa\u003c/p\u003e \u003cp\u003eUnsurprisingly, this study found that paediatricians were the HCP cadre requesting the most (74%) CF genetic testing in this cohort, followed by GPs (7%). In both the public and private healthcare sectors, paediatricians are at the clinical coalface and are often the first to examine children who may be affected by CF. In SA, while genetic counsellors may only request CF genetic testing in collaboration with a clinician, they are a valuable resource for clinicians, patients, and families, advising on appropriate CF genetic testing, taking family histories, and clarifying an individual's ethnic population through self-identity. While previous studies do not specify the ranking of HCP cadres referring patients for CF tests, they indicate that paediatricians, physicians, gynaecologists and medical geneticists contribute to test referrals, as confirmed by the current study (Baars et al., 2004). However, since paediatricians refer the majority of patients for testing, there is a possibility that other HCPs, such as GPs and adult pulmonologists, are unaware of the availability of CF testing and would require further education.\u003c/p\u003e \u003cp\u003eBarriers to CF testing in South Africa\u003c/p\u003e \u003cp\u003eAs for many other LMICs, a common challenge in SA is the cost of genetic testing equipment, imported reagents, infrastructure, and relevant and adequate expertise/capacity. The public healthcare sector laboratories are currently significantly understaffed and underfunded, leaving many public sector-dependent affected individuals struggling to access a diagnosis and appropriate treatment (Malherbe, 2015). Genetic testing is also centralised in three main urban areas: Johannesburg, Cape Town, and Bloemfontein, with limited coverage elsewhere. Continued training of Health Professionals Council of South Africa (HPCSA)-registered medical scientists, renewed political will, and allocation of required resources are necessary. The newly launched Nngwe project (2024) encourages clinicians and scientists to pool rare disease resources (including infrastructure and capacity), data, and knowledge for the greater good of the country's rare disease community. The country urgently needs increased capacity in sparsely populated and rural areas, including improved, expanded infrastructure and greater HCP expertise in primary healthcare to identify CF clinical symptoms and improve \u003cem\u003eCFTR\u003c/em\u003e testing referrals. Additionally, wider availability of CF sweat testing is required countrywide, with adequately trained staff to reduce the possibility of false negative and positive results.\u003c/p\u003e \u003cp\u003eIn SA, a lack of population-specific demographic data may prevent specific CF pathogenic variants from being identified across all ethnic populations when using kit-based methodology for genetic testing. Once a broader knowledge base regarding specific population groups and CF variants is established, it may be possible to custom-design targeted kits for the country's specific sub-populations, similar to the CF30 kit developed for the French population. Alternatively, reducing the cost of \u003cem\u003eCFTR\u003c/em\u003e sequencing may alleviate the population-specific issue of \u003cem\u003eCFTR\u003c/em\u003e genetic testing, which may be possible through initiatives such as the Nngwe project.\u003c/p\u003e \u003cp\u003eImpact of CF therapies on CF testing in South Africa\u003c/p\u003e \u003cp\u003eFollowing the international introduction of CF modulator medications in 2019, HCPs in SA requested \u003cem\u003eCFTR\u003c/em\u003e sequencing more frequently to identify pathogenic variants and determine patients' eligibility to access these new treatments. The 2019 spike in testing in Lab C may be ascribed to CF specialist clinics' doctors requesting sequencing for patients who either lacked a paper/electronic copy of previous testing reports confirming their CF genetic diagnosis or for those patients with only one known pathogenic \u003cem\u003eCFTR\u003c/em\u003e variant reported at the time of initial diagnosis when \u003cem\u003eCFTR\u003c/em\u003e sequencing was unavailable. When \u003cem\u003eCFTR\u003c/em\u003e-modulator therapies became accessible to identified \"genetically eligible\" individuals with specific CF variants, a genetic report demonstrating eligibility was also required to accompany the therapy request.\u003c/p\u003e \u003cp\u003eIn SA and worldwide, individuals with at least one confirmed p.Phe508del pathogenic variant who are \u0026gt;\u0026thinsp;2 years old are eligible for triple therapy modulators of elexacaftor-tezacaftor-ivacaftor (Trikafta\u0026trade;) (Vertex Pharmaceuticals Inc, 2024). However, most patients cannot access this therapy due to the high cost and the lack of approved alternative reimbursement methods, making access difficult (da Silva Filho et al., 2021). Since April 2024, eligible private CF patients in SA with medical insurance can access CF modulator benefits up to R400,000 (approximately \u003cspan\u003e$\u003c/span\u003e22,000) annually (Spotlight, 2024). Only 45% of eligible CF patients in SA can access this treatment, excluding most patients (Personal Communication, Dr. M. Zampoli, 28 November 2024). If Trikafta\u0026trade; becomes more affordable and accessible, there may be an increased demand for CF sequencing in the country to confirm patient eligibility. The most recent FDA-approved modulator therapy, Alyftrek\u0026trade;, also produced by Vertex, has not yet been introduced into the SA market and is not yet available for South African patients.\u003c/p\u003e \u003cp\u003eThe need for CF sequencing is also highlighted by Amaral and Harrison (2023), who reported that although \u003cem\u003eCFTR\u003c/em\u003e modulator therapies are now available, there is a need for further drug development to tackle the basis of CF cellular defects to improve clinical benefits for affected individuals and those with CFTR-related disorders. In this way, novel therapies could potentially treat every CFTR variant.\u003c/p\u003e \u003cp\u003eOther prospective CF treatments being trialled globally include gene editing by various methods, such as CRISPR-Cas9, or using gene delivery with various vectors in cell models of CF (Lee et al., 2021). Currently, no known human trials are underway. The global challenge is enabling equitable treatment access for all CF patients, regardless of geography, population demographic grouping, or socioeconomic status. The new modulator treatment (Trikafta\u0026trade;) has been a life-changing medication for many affected individuals, but unfortunately, it leaves those with rare CF variants untreated. The International Cystic Fibrosis Foundation's campaign for CF patients to \"leave no patient behind\" aligns with the SDG call (World Health Organisation, 2024) and encourages academia and the pharmaceutical industry to continue searching for a cure for all CF patients worldwide (Choi and Engelhardt, 2021).\u003c/p\u003e \u003cp\u003eStudy Limitations\u003c/p\u003e \u003cp\u003eThis study included past and current testing methodologies as reported by the six included laboratories only and may not represent all South African laboratories. CF test numbers for the ten-year retrospective audit were restricted to one private pathology group (Lab C), contributing to approximately 40% of the private healthcare market share. While including additional laboratories in the study would offer a more comprehensive overview of testing available today and historically in SA, this study serves as a starting point in building the CF testing landscape in the country.\u003c/p\u003e \u003cp\u003eThe study's ten-year review of patient results did not include ethnicity/race-specific data, as this is no data indicator requested or captured during sample processing. Statistics SA breaks down the South African population into four ethnic categories; this assists in identifying inequity in healthcare services.\u003c/p\u003e \u003cp\u003eThis article does not describe the rare combinations of CF pathogenic variants to ensure compliance with the Protection of Personal Information Act (POPIA) (Government of South Africa, 2013). These data are anonymised, as rare combinations of variants may lead to the identification of affected person/s from their genetic data due to the small number of individuals affected.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe burden of disease attributed to CF in SA remains unquantified to date, with many babies and children remaining undiagnosed or misdiagnosed due to other confounding illnesses that may interfere with CF early detection and referral. This study has provided the current and historic CF testing approaches used in SA for a limited cohort of CF patients. It highlights the role of HCPs in making informed decisions when choosing a CF genetic test for their patients, emphasizing the need for HCPs' continuous education to stay abreast of new emerging technology (Walters et al., 2024).\u003c/p\u003e \u003cp\u003eWith whole \u003cem\u003eCFTR\u003c/em\u003e gene sequencing becoming more affordable in SA, it is hoped that all children and adults suspected of having CF, regardless of geography, demographic population group, or socioeconomic status, can be tested and referred for treatment. \u003cem\u003eCFTR\u003c/em\u003e sequencing is a key tool in identifying \u003cem\u003ede novo\u003c/em\u003e pathogenic variants in SA's ethnically diverse population. SA has the technology, albeit with limited capacity, to test for all CF-causing pathogenic variants, including carrier testing in both healthcare sectors. A key challenge in the country is to develop more cost-effective CF sequencing testing for widespread roll-out in the public healthcare sector and low-resource settings throughout SA.\u003c/p\u003e \u003cp\u003eIt is recommended that cascade testing and improved utilisation of genetic counsellors for consultations and interpretation of genetic results should be offered to at-risk family members using targeted testing to identify familial CF carriers. Carrier identification will, in effect, contribute to knowledge of the actual burden of CF in SA and ultimately contribute to more South Africans affected by and at risk of CF being referred for genetic counselling and treatment in the country.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflict of interest:\u003c/p\u003e\n\u003cp\u003eSarah Walters, Colleen Aldous, and Helen Malherbe declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003eEthical consideration:\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from the University of Kwa-Zulu Natal (BFC222/18). Reconfirmation of the use of anonymised patient data was received from the laboratory\u0026apos;s chief operating officer in 2024. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmpath Laboratories for data access\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmpath Laboratory provided the anonymised data without coercion or specific promotion of any services or products. UKZN for PhD fee remission support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUKZN BREC: BFC222/18\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ampath Laboratories chief operating officer approved the publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAMARAL, M. D. \u0026amp; HARRISON, P. T. 2023. 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Report of a joint meeting of WHO/ECFTN/ICF (M) A/ECFS. \u003cem\u003eGeneva, WHO\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZAMPOLI, M., VERSTRAETE, J., FRAUENDORF, M., KASSANJEE, R., WORKMAN, L., MORROW, B. M. \u0026amp; ZAR, H. J. 2021. Cystic fibrosis in South Africa: spectrum of disease and determinants of outcome. \u003cem\u003eERJ Open Res\u003c/em\u003e, 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZAMPOLI M, V. J., FRAUENDORF M AND THE CF STEERING COMMITTEE 2021a. South African Cystic Fibrosis Patient\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-community-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocg","sideBox":"Learn more about [Journal of Community Genetics](http://link.springer.com/journal/12685)","snPcode":"12687","submissionUrl":"https://submission.nature.com/new-submission/12687/3","title":"Journal of Community Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cystic fibrosis, genetic testing, CFTR, recommendations","lastPublishedDoi":"10.21203/rs.3.rs-6247428/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6247428/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eConfirming a genetic diagnosis of cystic fibrosis (CF) for clinically affected individuals should be more accessible today, with more laboratories offering testing and improved technologies at lower costs. Instead, diagnostic testing for CF has become more complex due to the variety of genetic testing options available for the one known causative gene (\u003cem\u003eCFTR\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThis article provides an overview of genetic tests currently available for CF in six laboratories in South Africa (SA). Also, it demonstrates the evolution of CF tests used at one private laboratory in the country via a ten-year retrospective study. The findings of this study may serve as a guide for healthcare providers in selecting appropriate testing for CF diagnostic or carrier genetic confirmation.\u003c/p\u003e \u003cp\u003eThe choice of genetic test and methodology depends on individualised factors such as the ethnic origin of the patient, test availability, advantages and limitations, and cost. The ethnic diversity of SA's populations and probable under-reporting of CF in the country makes the diagnosis of this relatively common genetic condition complex. The actual burden of CF in SA is unknown, and comprehensive genetic testing, with an ongoing compilation of patient data in the SA CF registry, should assist in addressing the genetic diversity of CF-causing variants.\u003c/p\u003e","manuscriptTitle":"Genetic Testing for Cystic Fibrosis in South Africa: A 10-Year Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-07 10:22:55","doi":"10.21203/rs.3.rs-6247428/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-02T13:38:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T13:56:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215714997398810330657638109196538680933","date":"2025-04-22T07:53:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-26T18:09:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166445446579924178214179505551321136557","date":"2025-03-26T14:31:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-26T07:37:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-25T20:39:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-25T20:38:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Community Genetics","date":"2025-03-17T19:54:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-community-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocg","sideBox":"Learn more about [Journal of Community Genetics](http://link.springer.com/journal/12685)","snPcode":"12687","submissionUrl":"https://submission.nature.com/new-submission/12687/3","title":"Journal of Community Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1df76e1b-6ec5-4e43-a650-0efbb12c11fb","owner":[],"postedDate":"April 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T16:08:20+00:00","versionOfRecord":{"articleIdentity":"rs-6247428","link":"https://doi.org/10.1007/s12687-025-00810-6","journal":{"identity":"journal-of-community-genetics","isVorOnly":false,"title":"Journal of Community Genetics"},"publishedOn":"2025-09-25 15:58:00","publishedOnDateReadable":"September 25th, 2025"},"versionCreatedAt":"2025-04-07 10:22:55","video":"","vorDoi":"10.1007/s12687-025-00810-6","vorDoiUrl":"https://doi.org/10.1007/s12687-025-00810-6","workflowStages":[]},"version":"v1","identity":"rs-6247428","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6247428","identity":"rs-6247428","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}