Estimation of minimal disease prevalence from population genomic data: Application to primary familial brain calcification.
Gaël NicolasCamille CharbonnierDominique CampionJoris A VeltmanPublished in: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2017)
Primary Familial Brain Calcification (PFBC) is a rare calcifying disorder of the brain with autosomal dominant inheritance, of unknown prevalence. Four causal genes have been identified so far: SLC20A2, PDGFB, PDGFRB, and XPR1, with pathogenic, probably pathogenic or missense variants of unknown significance found in 27.7% probands in the French PFBC series. Estimating PFBC prevalence from a clinical input is arduous due to a large diversity of symptoms and ages of onset and to incomplete clinical penetrance. Abnormal calcifications on CT scan can be used as a reliable diagnostic biomarker whatever the clinical status, but differential diagnoses should be ruled out including the challenging exclusion of common basal ganglia calcifications. Our primary aim was to estimate the minimal prevalence of PFBC due to a variant in one of the known genes. We extracted variants from the four known genes present in the gnomAD database gathering genomic data from 138,632 individuals. We interpreted all variants based on their predicted effect, their frequency, and previous studies on PFBC patients. Using the most conservative estimate, the minimal prevalence of PFBC related to a variant in one of the four known genes was 4.5 p. 10,000 (95%CI [3.4-5.5] p. 10,000). We then used variant detection rates in patients to extrapolate an overall minimal prevalence of PFBC to 2.1 p. 1,000 (95%CI [1.9-2.4] p. 1,000). The population-based genomic analysis indicates that PFBC is not an exceptionally rare disorder, still underestimated and underdiagnosed.
Keyphrases
- risk factors
- end stage renal disease
- copy number
- chronic kidney disease
- genome wide
- newly diagnosed
- ejection fraction
- resting state
- white matter
- emergency department
- mitochondrial dna
- machine learning
- magnetic resonance imaging
- electronic health record
- physical activity
- genome wide identification
- functional connectivity
- magnetic resonance
- bioinformatics analysis
- cerebral ischemia
- big data
- depressive symptoms
- positron emission tomography
- deep learning
- transcription factor
- blood brain barrier
- genome wide analysis