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Assessing Discrepancies Between Genetic Variants and Clinical Diagnosis in Marfan Syndrome through All of Us

Clinical Genetics and Therapeutics
  • Primary Categories:
    • Clinical Genetics
  • Secondary Categories:
    • Clinical Genetics
Introduction:
Marfan syndrome, a rare autosomal dominant connective tissue disorder, primarily affects the cardiovascular, musculoskeletal, and sensory systems with variable clinical phenotypes. It is largely caused by variants in fibrillin 1 (FBN1), though 25% of cases are de novo and <10% of cases lack FBN1 mutations or exhibit recessive inheritance. Similarities with other disorders, such as Loeys-Dietz syndrome, complicate accurate diagnosis. To alleviate this, the 2010 Revised Ghent Nosology emphasizes certain clinical symptoms, such as aortic root dilation and ectopia lentis as key criteria for Marfan diagnosis. The All of Us Research Program offers an extensive biobank of genetic and electronic health record (EHR) data. This study leveraged All of Us to explore discrepancies between participants with FBN1 genetic variants and clinical Marfan diagnoses.

Methods:
Three cohorts were analyzed using All of Us data (v7): the diagnosis only cohort with Marfan ICD-9 and ICD-10 diagnosis but no pathogenic/likely pathogenic (PLP) FBN1 variants; the genetic only cohort with a PLP FBN1 variant but no Marfan diagnosis; and the overlapping cohort with both a Marfan diagnosis and a PLP variant. Phenome-wide association studies (PheWAS) were conducted on each cohort, mapping clinical Marfan ICD codes from Online Mendelian Inheritance in Man (OMIM) to broader phecodes using the PheWAS catalog. A phenotype risk score (PheRS) was developed based on negative log-transformed phenotype frequency in relation to All of Us population data. Additional cohort analysis utilized clinical laboratory measurements, physical measurements, procedures, and survey data from All of Us.

Results:
We identified n=98 participants in the diagnosis only cohort, n=178 in the genetic only cohort, and n=22 in the overlapping cohort. Demographic and biological factors, including drug use, sleep, race, sex, height, and weight, were not significantly different across cohorts. PheWASes for the diagnosis only and overlapping cohorts revealed significant associations with Marfan-related phenotypes. For example, the diagnosis only cohort showed significant enrichments of aortic dissection (OR=47.0, p=2.56e-13), mitral valve prolapse (OR=17.5, p=3.14e-15), pneumothorax (OR=7.54, p=1.49e-5), and joint hypermobility (OR=27.9, p=2.18e-15). These associations were absent in the genetic only cohort, which instead displayed a significant association with congenital lens dislocation (OR=23.2, p=1.56e-5), shared with the overlapping cohort. Individual EHR data highlighted that cardiovascular and musculoskeletal phenotypes, such as aortic aneurysms and scoliosis, were enriched in cohorts with Marfan diagnosis compared to the genetic only cohort, at increases of 39.3% and 14.8%, respectively. Other phecode categories, such as congenital deformations or sensory organs, did not show any enrichment.  PheRS scores differed significantly among cohorts (ANOVA: p=4.91e-24), with mean scores of 6.30 (SD=6.88) for the diagnosis only cohort, 13.3 (SD=8.08) for the overlapping cohort, and 1.69 (SD=3.13) for the genetic only cohort, confirmed by Tukey’s HSD test. However, the Marfan-diagnosis cohorts had up to 28 more individuals with echocardiogram, cardiac MRI, or CT angiography scans than the genetic only cohort.

Conclusion:
Our study highlights discrepancies between genetic FBN1 causality and Marfan clinical diagnosis. Marfan-diagnosis cohorts showed enriched cardiovascular and musculoskeletal phenotypes, consistent with diagnostic criteria, while genetic cohorts displayed other congenital associations, such as lens dislocation, consistent with criteria. This suggested reliance on cardiovascular manifestations for diagnosis underscores the importance of genetic testing in Marfan's preventative care. The low rates of workup procedures in the genetic only cohort suggest a lack of clinical vigilance. This study demonstrated that EHR data, PheWAS, and PheRS is a useful resource in assessing diagnosis of individuals with rare disease. Our future work will also include an investigation of 96 connective tissue disorder genes across the diagnosis only cohort and an exploration of temporal links between procedures and diagnosis across all three cohorts.

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