Nigel G. Laing

To the Editor: Kirk et al. (Nov. 21 issue)1 describe a study of couple-based genetic carrier screening. Cancer-associated genes, such as BRCA1, BRCA2, and those linked to the Lynch syndrome (MLH1, MSH2, MSH6, and PMS2), were excluded from the 1281 genes studied.2 Biallelic loss-of-function variants in these genes lead to very high rates of cancer in childhood. Biallelic loss of the Lynch syndrome genes results in constitutional mismatch-repair deficiency,3 whereas biallelic loss of BRCA1 or BRCA2 results in Fanconi’s anemia.4 These conditions are associated with aggressive cancers with high mortality, and therefore close surveillance is recommended in childhood.

In September 2021, the Royal College of Pathologists of Australasia (RCPA) and the Human Genetics Society of Australasia (HGSA) convened a joint working party to develop guidelines for reproductive genetic carrier screening (RGCS) for cystic fibrosis (CF), spinal muscular atrophy (SMA), and fragile X syndrome (FXS) (three-condition RGCS). This paper is an abbreviated version of the full guidelines, which have been endorsed by the RCPA and HGSA and published on the RCPA website, where they can be accessed freely.1 These guidelines contain statements of reasonable practice for pathology and clinical genetic service providers on how to manage three-condition RGCS. In Australia, these guidelines are relevant to the implementation of testing in the context of the Medicare Benefits Schedule (MBS) item numbers for carrier testing for these conditions. Although these guidelines have been developed in the context of public funding in Australia, they are relevant independent of any funding mechanism, and to laboratories and clinical services in New Zealand. These guidelines have been developed to facilitate the implementation of three-condition RGCS in ways that provide equitable, high-quality testing whilst maximising benefits and minimising harm. These guidelines do not provide clinical guidance for couples with a family history of a monogenic condition. RGCS designed for population-based testing may not be appropriate for people with a history of an affected family member/pregnancy. People with a family history should be referred directly to a genetics service by their primary healthcare provider for individualised assessment. The scope of these guidelines does not extend to screening for large panels of genes (sometimes referred to as expanded carrier screening) nor for carrier testing for other conditions, although some of the principles discussed here may be relevant to the implementation of such tests. Note that the term ‘reproductive couple’ used in this document represents the people who will be the genetic parents for the pregnancy or planned pregnancy. These individuals may not always be the people who are making reproductive decisions about a pregnancy, for example, in the context of the use of donor gametes. The term ‘reproductive partner’ is used to refer to a member of the reproductive couple who will be a genetic parent of the pregnancy or planned pregnancy. Reproductive couples include the two people of male and female chromosomal sex who are/will be the genetic parents of the pregnancy. As the testing approach and management of results are impacted by the chromosomal sex of the person tested, we use the terms ‘female’ and ‘male’ as necessary.

Background Genomic sequencing technology allows for identification of reproductive couples with an increased chance, as compared with that in the general population, of having a child with an autosomal recessive or X-linked genetic condition. Methods We investigated the feasibility, acceptability, and outcomes of a nationwide, couple-based genetic carrier screening program in Australia as part of the Mackenzie’s Mission project. Health care providers offered screening to persons before pregnancy or early in pregnancy. The results obtained from testing at least 1281 genes were provided to the reproductive couples. We aimed to ascertain the psychosocial effects on participants, the acceptability of screening to all participants, and the reproductive choices of persons identified as having an increased chance of having a child with a condition for which we screened. Results Among 10,038 reproductive couples enrolled in the study, 9107 (90.7%) completed screening, and 175 (1.9%) were newly identified as having an increased chance of having a child with a genetic condition for which we screened. These conditions involved pathogenic variants in 90 different genes; 74.3% of the conditions were autosomal recessive. Three months after receiving the results, 76.6% of the couples with a newly identified increased chance had used or planned to use reproductive interventions to avoid having an affected child. Those newly identified as having an increased chance had greater anxiety than those with a low chance. The median level of decisional regret was low in all result groups, and 98.9% of participants perceived screening to be acceptable. Conclusions Couple-based reproductive genetic carrier screening was largely acceptable to participants and was used to inform reproductive decision making. The delivery of screening to a diverse and geographically dispersed population was feasible.

Purpose We set out to develop a publicly available tool that could accurately diagnose spinal muscular atrophy (SMA) in exome, genome, or panel sequencing data sets aligned to a GRCh37, GRCh38, or T2T reference genome. Methods The SMA Finder algorithm detects the most common genetic causes of SMA by evaluating reads that overlap the c.840 position of the SMN1 and SMN2 paralogs. It uses these reads to determine whether an individual most likely has 0 functional copies of SMN1. Results We developed SMA Finder and evaluated it on 16,626 exomes and 3911 genomes from the Broad Institute Center for Mendelian Genomics, 1157 exomes and 8762 panel samples from Tartu University Hospital, and 198,868 exomes and 198,868 genomes from the UK Biobank. SMA Finder’s false-positive rate was below 1 in 200,000 samples, its positive predictive value was greater than 96%, and its true-positive rate was 29 out of 29. Most of these SMA diagnoses had initially been clinically misdiagnosed as limb-girdle muscular dystrophy. Conclusion Our extensive evaluation of SMA Finder on exome, genome, and panel sequencing samples found it to have nearly 100% accuracy and demonstrated its ability to reduce diagnostic delays, particularly in individuals with milder subtypes of SMA. Given this accuracy, the common misdiagnoses identified here, the widespread availability of clinical confirmatory testing for SMA, and the existence of treatment options, we propose that it is time to add SMN1 to the American College of Medical Genetics list of genes with reportable secondary findings after genome and exome sequencing.

Using the Australian Census survey 2021 as base population, a microsimulation model, PreconMOD was developed to evaluate the cost-effectiveness of population-based expanded reproductive carrier screening (RCS) for 569 recessive conditions from the health service and societal perspectives. The model simulated the effect of expanded RCS including the downstream interventions for at-risk couples on cost and outcomes. The comparators were (i) no population screening (ii) limited screening for cystic fibrosis, spinal muscular atrophy, and fragile X syndrome and (iii) a 300 conditions screening panel. Averted affected births and health service cost with expanded RCS were projected to year 2061. At a 50% uptake, our model predicts that expanded RCS is cost saving (i.e., higher quality-adjusted life-years and lower costs) compared with other screening strategies in the model from the health service and societal perspectives. The number of affected births averted in a single cohort would increase from 84 [95% confidence interval (CI) 60-116] with limited screening to 2067 (95%CI 1808-2376) with expanded RCS. Expanded RCS was cost-saving compared to the 300-conditions screening panel. Indirect cost accounted for about one-third of the total costs associated with recessive disorders. Our model predicts that the direct treatment cost associated with current limited 3 genes screening would increase by 20% each year to A$73.4 billion to the health system by 2061. Our findings contribute insights on the cost burden of genetic diseases and the economic benefits of expanded RCS to better informed resource allocation decisions.