Diagnosis of Chronic Granulomatous Disease: Strengths and Challenges in the Genomic Era
Abstract
:1. Introduction
2. Clinical Features and Inheritance
3. Molecular and Cellular Pathophysiology
4. Benefits of Early Diagnosis of CGD
5. When to Suspect and Test for CGD
Histologic features of CGD in the lung are nonspecific, but may include: neutrophil-predominant abscesses or micro-abscesses surrounded by histiocytes; granulomas, which may be suppurative, necrotising or non-necrotising; and chronic diffuse inflammation associated with areas of fibrosis [110,111]. Gastrointestinal tract histology findings in CGD involving the gut are also nonspecific, and may be indistinguishable from IBD [112,113,114,115]. These include mucosal granulomas or microgranulomas and focal inflammation in the form of acute cryptitis, crypt abscess and ulceration, as well as chronic lymphoplasmacytic inflammation and disruption of normal mucosal architecture [113,116]. Eosinophils and pigmented macrophages may be present in inflammatory infiltrates, and the latter are reported to be more suggestive of CGD [112,116]. These findings may occur throughout the gastrointestinal tract, but predominantly affect the lower colorectum and perianal area, with sparing of the upper tract and oesophagus [113,116]. Biopsy findings of CGD-related lesions in skin, lymphoreticular system, liver and bladder may share elements of these nonspecific histologic characteristics of acute and chronic inflammation, with granulomas and occasional visualisation of microorganisms [117].
Radiologic appearances of lung infection in CGD can be varied, and include pulmonary nodules, ground-glass opacities, focal consolidation and masses, with or without cavities, abscesses, effusion or chest wall involvement where infection is invasive [118,119]. Post-infectious and inflammatory complications can also be varied on chest imaging, and may demonstrate fibrosis, septal thickening, bronchiectasis, and emphysema [118,119]. In the gut, patients may again demonstrate nonspecific radiologic findings of wall thickening, dilatation, or mucosal enhancement with a predominance of lower tract and perianal disease (fistulae, fat stranding and abscesses), and endoscopy may or may not show active inflammatory changes [120]. Imaging of CGD lymphadenitis shows nonspecific tomographic appearances of enlarged and contrast-enhanced lymph nodes with or without central necrosis, which sonographically may have thick septations and internal debris; calcification may be seen in chronically inflamed nodes [121]. In the genitourinary tract, wall thickening may be demonstrated in the bladder and ureteric tracts, sometimes with evidence of obstruction (e.g., hydronephrosis) or scarring and calcification [121,122]. Furthermore, complications of CGD in liver, spleen, skin or soft tissue, muscle, bone and central nervous system may demonstrate nonspecific radiologic changes [121]. |
6. Testing of NADPH Oxidase Function
6.1. Measurement of Oxygen Consumption
6.2. Plate-Based Assays
6.3. Nitroblue Tetrazolium (NBT)
6.4. Dihydrorhodamine (DHR)
6.5. Dichlorofluorescein (DCF)
7. Molecular Diagnostics: Protein Assays
8. Molecular Diagnostics: Genetic Testing
Genetic variants, regardless of the method used for their detection, are categorised broadly by the likelihood that they are responsible for an individual’s clinical phenotype. These are summarily termed categories 1 to 5 on the joint recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology [173]. In brief, variants that have previously been confirmed as benign in published literature, curated databases of genetic variants, or unpublished in-house laboratory data are termed category 1 “benign” variants. Those that are predicted by computational (in silico) or other means to be benign are termed category 2 “likely benign” variants. “Variants of uncertain significance” (VUS), which differ from the reference genome but cannot be confirmed or ruled out as responsible for the phenotype in question are classified as category 3 variants. Category 4 “likely pathogenic” variants are predicted computationally or otherwise to be pathogenic, but have not been conclusively proven as such in existing data sources, as listed above. Lastly, category 5 “pathogenic” variants are confirmed to be disease-causing in published literature or databases. For the purposes of clinical practice, category 4 and 5 variants are generally considered diagnostic positive, and category 1 and 2 variants are considered negative. By consensus, category 3 VUS should not be used to guide clinical decision-making for affected individuals [173]. Interpretation of VUS can be aided by trio and segregation studies in individual cases, and functional testing of suspected variants expressed in in vitro systems within experienced research settings [174]. Different labs and genomic testing pipelines may manage VUS differently, e.g., in reporting pre-test probability of finding VUS in their panel, or may not report VUS at all [172]. Of note, reference databases for variant classification are gradually refined over time, and most VUS are eventually reclassified into other categories, prompting many genomic laboratories to periodically re-analyse historic clinical sequencing data, and issue supplementary reports where reclassification impacts the interpretation of genetic findings in individual cases [175]. In the context of CGD, clinical symptoms alone are insufficient to confirm pathogenicity of a novel CGD gene variant without first demonstrating an oxidative burst defect [108]. |
Gene panels have certain advantages over comprehensive testing. Included genes have usually been specifically targeted and validated by the laboratory, allowing greater confidence in complete sequencing of the genes of interest, and often include relevant targeted noncoding regions, which may be missed by exome sequencing [172]. Choosing a narrow phenotype-focussed panel also has the advantages of streamlined analysis, reduced costs, quicker turnaround time, and limited identification of VUS and incidental variants in genes unrelated to the disease phenotype, which may cause further clinical uncertainty or be clinically unactionable [172].
Whole exome sequencing (WES) and whole genome sequencing (WGS) can reliably detect missense or nonsense variants, and small indels (<50 bp) within nonrepetitive coding DNA that are rare in the population and previously reported as pathogenic [172]. WES examines the approximate 180,000 protein-coding segments of the genome (exons), which comprise 1–2% of the genome and account for the majority of recognised pathogenic variants [172]. About 95% of the exome can be sequenced with current NGS methodologies [176,177]. WGS examines the entirety of the approximate 20,000 genes, noncoding RNAs, intronic and intergenic regions of DNA [172]. WGS has the advantages of (1) being able to detect intronic or intergenic variants not covered by WES, (2) simpler sample preparation methods (e.g., no need for sequence enrichment for coding regions), and (3) being able to identify structural variants and chromosomal breakpoints in noncoding regions [172]. Certain regions still remain elusive to standard NGS technologies, and the specific methodology used to target these will vary by laboratory. WGS is slower and more expensive than WES, and yet the majority of pathogenic variants identified by WGS are located within exons [172]. Rapid evolution of WES/WGS sequencing and analysis methods in recent years precludes precise estimation of their diagnostic accuracy for inborn errors of immunity (IEI), but reported estimates of sensitivity range from 83 to 100%, and of specificity range from 45 to 88% [178]. Of note, where more genes are tested at once, there is greater likelihood of finding VUS and incidental pathogenic variants, which may pose difficulties for clinical interpretation and management [179].
Ancillary methods may be used to supplement genetic or genomic results obtained by conventional means. For example, the impact of predicted pathogenic intronic variants (especially those outside of the core or essential splice site) may be confirmed by RNA analysis, as missplicing may lead to complete or partial exon skipping or inclusion of intronic sequence in mature mRNA, with deleterious consequences [170]. |
9. Mutations in CGD
10. Limitations of Genetic Testing for CGD
11. Screening
12. Outlook
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Gene symbol | CYBB | CYBA | NCF1 | NCF2 | NCF4 |
NCBI gene ID | 1536 | 1535 | 653361 | 4688 | 4689 |
Gene name | Cytochrome b558 beta | Cytochrome b558 alpha | Neutrophil cytosolic factor 1 | Neutrophil cytosolic factor 2 | Neutrophil cytosolic factor 4 |
Gene location | Xp21.1-p11.4 | 16q24.2 | 7q11.23 | 1q25.3 | 22q12.3 |
Exon count | 14 | 6 | 11 | 20 | 12 |
Protein | gp91phox/NOX2 | p22phox | p47phox | p67phox | p40phox |
Protein location | Specific granule membrane, plasma membrane | Specific granule membrane, plasma membrane | Cytosol, cytoskeleton | Cytosol, cytoskeleton | Cytosol, cytoskeleton |
Frequency | 65–70% | 5% | 20% | 5% | Rare |
Inheritance | XR | AR | AR | AR | AR |
Clinical severity | Severe Early onset | Severe Early onset | Mild Late onset | Severe Early onset | Mild Atypical |
Mutations | Missense Nonsense Missplicing Large or small deletions Insertions Duplications Transposable elements | Insertions Deletions Missense Nonsense Missplicing | Unequal meiotic crossover events with neighbouring pseudogenes Missense Nonsense Insertions Deletions Missplicing | Insertions Deletions Missense Nonsense Missplicing | Insertions Deletions Missense Nonsense Missplicing |
Pickup on sequence analysis | 85% | 85% | 75% | 85% | 90% |
Pickup on deletion/duplication analysis | 15% | 15% | 25% | 15% | 10% |
Gene symbol | CYBC1 | RAC2 | G6PD | MPO | GSS |
NCBI gene ID | 79415 | 5880 | 2539 | 4353 | 2937 |
Gene name | Cytochrome b558 chaperone 1 | Rac family small GTPase 2 | Glucose-6-phosphate dehydrogenase | Myeloperoxidase | Glutathione synthetase |
Gene location | 17q25.3 | 22q13.1 | Xq28 | 17q22 | 20q11.22 |
Exon count | 8 | 8 | 14 | 12 | 15 |
Protein | CYBC1/Eros | Rac2-GTPase | G6PD | MPO | GSS |
Protein location | Endoplasmic reticulum | Cytosol | Cytosol | Granule lumen | Cytosol, nucleus, mitochondria |
Frequency | Rare | Rare | Severe deficiency is rare | Common but unlikely to cause CGD-like features | Rare |
Inheritance | AR | AD | XR | AR | AR |
Clinical severity | Few cases described | Few cases described | Spectrum from mild to severe | Asymptomatic or susceptible to Candida | Spectrum from mild to severe |
Mutations | Nonsense Missense Missplicing | Nonsense Missense | Deletion Missense | Nonsense Missense Missplicing Deletions | Indels Nonsense Missense Missplicing |
Notes | Also regulates expression of proteins other than gp91phox-p22phox, e.g., P2X7 | Also associated with abnormalities of neutrophil chemotaxis and lymphocyte function | Mild cases: relatively common but lack CGD-like features Severe cases: generally mild CGD features | Rarely solely responsible for immunodeficiency | Mild cases: haemolytic anaemia only Moderate: metabolic acidosis Severe: progressive neurological dysfunction and infection susceptibility |
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O’Donovan, C.J.; Tan, L.T.; Abidin, M.A.Z.; Roderick, M.R.; Grammatikos, A.; Bernatoniene, J. Diagnosis of Chronic Granulomatous Disease: Strengths and Challenges in the Genomic Era. J. Clin. Med. 2024, 13, 4435. https://doi.org/10.3390/jcm13154435
O’Donovan CJ, Tan LT, Abidin MAZ, Roderick MR, Grammatikos A, Bernatoniene J. Diagnosis of Chronic Granulomatous Disease: Strengths and Challenges in the Genomic Era. Journal of Clinical Medicine. 2024; 13(15):4435. https://doi.org/10.3390/jcm13154435
Chicago/Turabian StyleO’Donovan, Conor J., Lay Teng Tan, Mohd A. Z. Abidin, Marion R. Roderick, Alexandros Grammatikos, and Jolanta Bernatoniene. 2024. "Diagnosis of Chronic Granulomatous Disease: Strengths and Challenges in the Genomic Era" Journal of Clinical Medicine 13, no. 15: 4435. https://doi.org/10.3390/jcm13154435
APA StyleO’Donovan, C. J., Tan, L. T., Abidin, M. A. Z., Roderick, M. R., Grammatikos, A., & Bernatoniene, J. (2024). Diagnosis of Chronic Granulomatous Disease: Strengths and Challenges in the Genomic Era. Journal of Clinical Medicine, 13(15), 4435. https://doi.org/10.3390/jcm13154435