Diverse clinical features and diagnostic delay in monogenic inborn errors of immunity: A call for access to genetic testing

Monogenic Inborn Errors of Immunity with impaired IgG response to polysaccharide antigens but normal IgG levels and normal IgG response to protein antigens

In patients with severe and recurrent infections, minimal diagnostic workup to test for Inborn Errors of Immunity (IEI) includes a full blood count, IgG, IgA and IgM. Vaccine antibodies against tetanus toxoid are also frequently measured, whereas testing for anti-polysaccharide IgG antibodies and IgG subclasses is not routinely performed by primary care physicians. This basic approach may cause a significant delay in diagnosing monogenic IEI that can present with an impaired IgG response to polysaccharide antigens with or without IgG subclass deficiency at an early stage. Our article reviews genetically defined IEI, that may initially present with an impaired IgG response to polysaccharide antigens, but normal or only slightly decreased IgG levels and normal responses to protein or conjugate vaccine antigens. We summarize clinical, genetic, and immunological findings characteristic for these IEI. This review may help clinicians to identify patients that require extended immunologic and genetic evaluations despite unremarkable basic immunologic findings. We recommend the inclusion of anti-polysaccharide IgG antibodies as part of the initial routine work-up for possible IEI.

Natural language processing of clinical notes enables early inborn error of immunity risk ascertainment

Background

There are now approximately 450 discrete inborn errors of immunity (IEI) described; however, diagnostic rates remain suboptimal. Use of structured health record data has proven useful for patient detection but may be augmented by natural language processing (NLP). Here we present a machine learning model that can distinguish patients from controls significantly in advance of ultimate diagnosis date.

Objective

We sought to create an NLP machine learning algorithm that could identify IEI patients early during the disease course and shorten the diagnostic odyssey.

Methods

Our approach involved extracting a large corpus of IEI patient clinical-note text from a major referral center's electronic health record (EHR) system and a matched control corpus for comparison. We built text classifiers with simple machine learning methods and trained them on progressively longer time epochs before date of diagnosis.

Results

The top performing NLP algorithm effectively distinguished cases from controls robustly 36 months before ultimate clinical diagnosis (area under precision recall curve > 0.95). Corpus analysis demonstrated that statistically enriched, IEI-relevant terms were evident 24+ months before diagnosis, validating that clinical notes can provide a signal for early prediction of IEI.

Conclusion

Mining EHR notes with NLP holds promise for improving early IEI patient detection.

Diagnostic delay in monogenic disease: A scoping review

PURPOSE

Diagnostic delay in monogenic disease is reportedly common. We conducted a scoping review investigating variability in study design, results, and conclusions.

METHODS

We searched the academic literature on January 17, 2023, for original peer reviewed journals and conference articles that quantified diagnostic delay in monogenic disease. We abstracted the reported diagnostic delay, relevant study design features, and definitions.

RESULTS

Our search identified 259 articles quantifying diagnostic delay in 111 distinct monogenetic diseases. Median reported diagnostic delay for all studies collectively in monogenetic diseases was 5.0 years (IQR 2-10). There was major variation in the reported delay within individual monogenetic diseases. Shorter delay was associated with disorders of childhood metabolism, immunity, and development. The majority (67.6%) of articles that studied delay reported an improvement with calendar time. Study design and definitions of delay were highly heterogenous. Three gaps were identified: (1) no studies were conducted in the least developed countries, (2) delay has not been studied for the majority of known, or (3) most prevalent genetic diseases.

CONCLUSION

Heterogenous study design and definitions of diagnostic delay inhibit comparison across studies. Future efforts should focus on standardizing delay measurements, while expanding the research to low-income countries.

Clinical updates in inborn errors of immunity: a focus on the noninfectious clinical manifestations

PURPOSE OF REVIEW

In the last 5 years, several new inborn errors of immunity (IEI) have been described, especially in the areas of immune dysregulation and autoinflammation. As a result, the clinical presentation of IEIs has broadened. We review the heterogeneous presentation of IEIs and detail several of the recently described IEIs with a focus on the noninfectious manifestations commonly seen.

RECENT FINDINGS

IEIs may present with early onset and/or multiple autoimmune manifestations, increased risk for malignancy, lymphoproliferation, severe atopy, autoinflammation and/or hyperinflammation. Because of this, patients can present to a wide array of providers ranging from primary care to various pediatric subspecialists. The International Union of Immunological Societies (IUIS) expert committee has created a phenotypic classification of IEIs in order to help clinicians narrow their evaluation based on the laboratory and clinical findings.

SUMMARY

Both primary care pediatricians and pediatric subspecialists need to be aware of the common clinical features associated with IEI and recognize when to refer to allergy-immunology for further evaluation. Early diagnosis can lead to earlier treatment initiation and improve clinical outcomes for our patients.

Inborn Errors of Immunity Associated With Type 2 Inflammation in the USIDNET Registry

Background

Monogenic conditions that disrupt proper development and/or function of the immune system are termed inborn errors of immunity (IEIs), also known as primary immunodeficiencies. Patients with IEIs often suffer from other manifestations in addition to infection, and allergic inflammation is an increasingly recognized feature of these conditions.

Methods

We performed a retrospective analysis of IEIs presenting with allergic inflammation as reported in the USIDNET registry. Our inclusion criteria comprised of patients with a reported monogenic cause for IEI where reported lab eosinophil and/or IgE values were available for the patient prior to them receiving potentially curative therapy. Patients were excluded if we were unable to determine the defective gene underlying their IEI. Patients were classified as having eosinophilia or elevated IgE when their record included at least 1 eosinophil count or IgE value that was greater than the age stratified upper limit of normal. We compared the proportion of patients with eosinophilia or elevated IgE with the proportion of samples in a reference population that fall above the upper limit of normal (2.5%).

Results

The query submitted to the USIDNET registry identified 1409 patients meeting inclusion criteria with a monogenic cause for their IEI diagnosis, of which 975 had eosinophil counts and 645 had IgE levels obtained prior to transplantation or gene therapy that were available for analysis. Overall, 18.8% (183/975) of the patients evaluated from the USIDNET registry had eosinophilia and 20.9% (135/645) had an elevated IgE. IEIs caused by defects in 32 genes were found to be significantly associated with eosinophilia and/or an elevated IgE level, spanning 7 of the 10 IEI categories according to the International Union of Immunological Societies classification.

Conclusion

Type 2 inflammation manifesting as eosinophilia or elevated IgE is found in a broad range of IEIs in the USIDNET registry. Our findings suggest that allergic immune dysregulation may be more widespread in IEIs than previously reported.