Rare diseases (RDs) are life-threatening chronic disorders found in small groups of people (MOH, 2023). According to the online database Orphanet, there are more than 7,362–8,120 gene-related to RDs, with a prevalence of one in 2,000 (OMIM, 2023; Orphanet, 2023). A high rate of consanguineous marriages in Saudi Arabia increases the prevalence of autosomal recessive disorders (Alfares et al., 2017; Monies et al., 2017). This consanguinity results in a high level of pathogenic alleles being carried with increasing frequency in the Saudi population (Eissa et al., 2021; Aleissa et al., 2022). The government of Saudi Arabia, represented by the Ministry of Health, has introduced several screening programs to reduce the burden of specific diseases carried by the Saudi population (Saudi Ministry of Health, 2020). However, several studies have reported multiple diseases that share similar phenotypes. For example, a multicenter study of 3,310 clinical exome sequencing (ES) cases performed on 2,219 families characterized several phenotypes. These phenotypes were mainly neurodevelopmental disorders, congenital malformations, dysmorphic features, and neuromuscular dystrophies (Monies et al., 2019). The same phenotypes were also observed in several other studies (Bertoli-Avella et al., 2021a; Bertoli-Avella et al., 2021b; Alotibi et al., 2023) and can still be identified and diagnosed through genetic testing. Other ultra-rare variations are usually challenging to diagnose due to phenotypic variability (Balci et al., 2017; Posey et al., 2017). In ultra-rare cases, it might be associated with an overlap of two phenotypes due to having more genetic associations than a single-gene disorder. In these cases, the diagnosis is a dilemma; practitioners must consider multiple diagnoses as part of an appropriate solution (Armour et al., 2016). However, more than 50% of these cases remain with no diagnosis or treatment, leaving the patients and their families suffering from a prolonged and expensive diagnostic odyssey (Lewis et al., 2010; de Ru et al., 2012). In addition to the frustration caused to patients and their caregivers, this lengthy process also burdens healthcare providers. In the United States, it is estimated that a diagnostic odyssey costs more than US $10,000 for each case (Marshall et al., 2019).

Genomic medicine worldwide has encountered exponential advances in sequencing technology and interpretation tools, accelerating the diagnostic yield for several diseases (Seaby, Rehm, and O’Donnell-Luria, 2021). However, the results remain variants of unknown significance (VUS), and several patients still wait years to be diagnosed genetically (Deignan et al., 2019). Unsolved cases account for two-thirds of all RDs (Tan et al., 2020). While the American College of Medical Genetics and Genomics emphasizes revisiting undiagnosed cases (Deignan et al., 2019), RD patients remain undiagnosed due to limited knowledge of certain variations that might be associated with their phenotypes (Truty et al., 2019). Downstream analysis plays a significant role in variant annotation, data filtering, and technical aspects affecting sequence quality (Tan et al., 2020). This study aims to reclassify VUS and match them with reported phenotypes.

The included participants in this study underwent 186 ES as Solo, two ES as Duo, one ES as Trio, one GS as Trio, eight panels, and three mitochondrial GS (Table 1). Most samples were associated with neurological disorders, accounting for 47% (92 variants); 82% (75 variants) of the neurological disorders were associated with psychomotor impairment, developmental regression, and epilepsy. The second phenotype observed was metabolic disorder (10%; 19 variants), followed by congenital malformation (7%; 13 variants) and bone dysplasia (7%; 14 variants), with a minor representation of other phenotypes, as indicated in Figure 2.

The variants were mainly missense, accounting for 67% of the total single nucleotide variant, followed by 9% splicing and 7% frameshift (Figure 3). Although 90 variants remained VUS out of the original unclassified variants, we reclassified more than half of the original 194 variants. In total, 104 variants were classified with the following reclassifications: nine as benign (B), 30 as likely benign (LB), 16 as pathogenic (P), and 49 as likely pathogenic (LP), as shown in Figure 4.

After we correlated the phenotype with the genotype in each sample, we found that 60% of the phenotypes were related to a genotype (Figure 5). In 13% of the cases, the genotype explained part of the phenotype; in 11% of the cases, it could explain the phenotype; in 10% of the cases, it was not associated with the phenotype; and in 3%, the correlation remained unsure. Among the positive reclassified cases, the genotype was related to the phenotype in 48 cases (77.4%), could explain the phenotype in six cases (9.6%), and was unrelated to the phenotype in four cases (6.4%). The modes of inheritance among the positive reclassified cases were as follows: autosomal recessive (AR) and autosomal dominant (AD) were approximately equal, with 28 (45%) and 27 (43.5%) cases, respectively, X-linked comprised four cases (6.4%), and AR versus AD comprised two cases (3%).

A review of the KFH&RC database illustrated that 11 P, 40 LP, 63 VUS, 17 LB, and 2 B variants had never been previously reported among the Saudi population. In comparison, 5 P, 8 LP, 29 VUS, 13 LB, and 7B variants had been previously noticed in this database. Exploring Azphewas indicated that 12 variants were previously observed; however, there was no strong correlation with a specific phenotype. Details of the 194 variants can be found in Supplementary Tables S1–S4.

According to their relevance, genetic variants can be classified into one of the following categories: P, LP, VUS, LB, and B (Richards et al., 2015). VUS classification has an unknown impact on health, leaving patients and clinicians uncertain about the variant’s pathogenicity (Iancu et al., 2021). Among the 194 reclassified VUS, about 25% were upgraded to LP, and 8% were P. Around 15% of the VUS were downgraded to LB, 5% were B, and the majority remained VUS (49%). Among the VUS variants, six were AD inherited from a healthy parent, which excluded disease associations (Supplementary Table S4). Among the six variants, one was observed to be heterozygous in the KFH&RC database. Exploring the database further revealed that more than 60 VUS variants had never been observed in the Saudi population, and 29 had previously been observed in the dataset.

The reclassifications from VUS to LP and P variants indicated that 51 newly classified variants had never been observed in KFH&RC. Among these 51 variants, 31 had not been observed in ClinVar; thus, they might be novel variants. In all, 13 variants had been previously observed in the KFH&RC database, showing common to rare allele frequencies. The lack of a disease database limits novel variant discovery in Saudi Arabia because the international database lacks Saudi descent (Monies et al., 2019).

Downgrading a VUS to B or LB might concern the requested healthcare provider and/or proband. Hence, further explanation should be provided regarding the variant classification process and the evidence upon which it is based. It may be advantageous to exclude this variant and seek another variation that might not appear in conventional NGS. For instance, identifying new causative variations may require techniques that explore CNVs, including chromosomal microarrays or long-read sequencing (Pauper et al., 2021).

Healthcare providers and patients rely on the accuracy of their variants’ results to make life-changing medical decisions; however, the uncertainty of VUS might create confusion for healthcare providers and patients. Due to a limited understanding of VUS, non-genetics healthcare providers might erroneously interpret and incorporate VUS into management decisions (Kurian et al., 2017). It has been demonstrated that some surgeons have performed bilateral breast mastectomies on patients with unilateral breast cancer with VUS in BRCA1 and BRCA2 without consulting a medical geneticist or a genetic counselor. Furthermore, several studies have indicated that patients and their families do not always fully comprehend the uncertainty of a VUS, which might not have been appropriately communicated to them. This confusion compounds the psychological impact experienced by patients when VUS results are disclosed (Gould et al., 2022). A multidisciplinary team, including board-certified medical geneticists, laboratory molecular geneticists, and bioinformation and genetics counselors, should carefully evaluate the reassessment of VUS. This team should re-evaluate the patient’s phenotypes, conduct clinical investigations, establish genotype–phenotype correlations, and determine whether the associated disorder’s attributed variants and clinical features are linked to the patient’s phenotype (Corominas et al., 2022; Friedman et al., 2020). The reassessment of VUS should reflect the individual/family risks, genetics counseling, and management strategies (Makhnoon et al., 2023).

Although the American College of Medical Genetics and Genomics—Association for Molecular Pathology (ACMG-AMP) (Richards et al., 2015) has established guidelines to create consistency in how laboratories use available evidence to establish a variant’s pathogenicity, not all laboratories classify genetic variants the same way. Another approach would be to implement an artificial intelligence (AI) tool in variant interpretation software for continuous and dynamic classification and prioritization of variants. These AI tools show that data-driven approaches can solve more VUS cases than guideline-based approaches and in silico prediction tools (Lai et al., 2020; Nicora et al., 2022).

It is important to re-evaluate VUS, as future research will improve the understanding of genes and their associated conditions. Laboratories could share data regarding variant classifications in a disease database to improve the understanding of how specific variants impact health. Valuable time could be saved if all testing laboratories were to study variants collaboratively. Furthermore, healthcare institutes should have robust systems and internal guidelines for re-evaluating VUS that reassess frequency and patient follow-up recommendations (Chiang et al., 2021). Evaluating VUS reclassification’s clinical and psychological impacts on the healthcare system and patients/families is also essential (Chiang et al., 2021).

One of the most important recommendations from this study is that all clinical laboratories should implement an internal system to track all sequence variants identified in each gene and clinical evidence when reported. They are also encouraged to contribute to variant databases, such as ClinVar, including clinical evidence used for the variant classification, to aid in the continued understanding of the impact of human variation.

A limitation of this study is that further investigation must be conducted using functional biology to understand the etiology of the disease and its possible target treatments. In summary, most of the reclassified variants were associated with neurological disorders. Revisiting the genetic data and reclassifying the VUS will aid in diagnosis and shorten patients’ diagnostic odyssey. Furthermore, understanding the genetic background of RDs will provide insight into the advancement of gene therapy and precision medicine and accelerate innovations in the pharmaceutical industry.