Phenotypic expansion illuminates multilocus pathogenic variation

Abstract

PurposeMultilocus variation-pathogenic variants in two or more disease genes-can potentially explain the underlying genetic basis for apparent phenotypic expansion in cases for which the observed clinical features extend beyond those reported in association with a "known" disease gene.MethodsAnalyses focused on 106 patients, 19 for whom apparent phenotypic expansion was previously attributed to variation at known disease genes. We performed a retrospective computational reanalysis of whole-exome sequencing data using stringent Variant Call File filtering criteria to determine whether molecular diagnoses involving additional disease loci might explain the observed expanded phenotypes.ResultsMultilocus variation was identified in 31.6% (6/19) of families with phenotypic expansion and 2.3% (2/87) without phenotypic expansion. Intrafamilial clinical variability within two families was explained by multilocus variation identified in the more severely affected sibling.ConclusionOur findings underscore the role of multiple rare variants at different loci in the etiology of genetically and clinically heterogeneous cohorts. Intrafamilial phenotypic and genotypic variability allowed a dissection of genotype-phenotype relationships in two families. Our data emphasize the critical role of the clinician in diagnostic genomic analyses and demonstrate that apparent phenotypic expansion may represent blended phenotypes resulting from pathogenic variation at more than one locus.Genetics in Medicine advance online publication, 26 April 2018; doi:10.1038/gim.2018.33.

Missense variants in TAF1 and developmental phenotypes: Challenges of determining pathogenicity

“…Other variants of interest that were found during the course of ES or GS are listed in Table S2, with the most notable among these being: (a) a RAC1 de novo variant, c.116A>G p.(Asn39Ser) in Individual 3, with in silico modeling, mouse fibroblasts spreading assays, and in vivo overexpression assays in zebrafish having demonstrated that this variant functions as a dominant‐negative allele, resulting in microcephaly, reduced neuronal proliferation, and cerebellar abnormalities in vivo (Reijnders et al, ); (b) a HNRNPU de novo c.837_839delAGA variant in Individual 11, leading to deletion of glutamic acid at position 279, with LOF mutations associated with ID (Bramswig et al, ; Hamdan et al, ; Leduc et al, ; Yates et al, ); and (c) a genetically confirmed diagnosis of mucopolysaccharidosis type IIIA—Sanfilippo syndrome due to compound heterozygous mutations in SGSH in Individual 14‐1. It is well known that multiple molecular diagnoses can be found during the course of ES or GS, and it is likely that the clinical presentation is a blended phenotype in any given individual (Karaca et al, ; Posey et al, ). To be conservative in our assignment of “pathogenicity” using the ACMG/AMP framework (Richards et al, ), we have included for these cases the criterion of “BP5‐Variant found in a case with an alternate molecular basis for disease” in Table S1.…”

“…Other variants of interest that were found during the course of ES or GS are listed in Table S2, with the most notable among these being: (a) a heterozygous mutations in SGSH in Individual 14-1. It is well known that multiple molecular diagnoses can be found during the course of ES or GS, and it is likely that the clinical presentation is a blended phenotype in any given individual (Karaca et al, 2018;Posey et al, 2017). To be conservative in our assignment of "pathogenicity"…”

Biallelic GRM7 variants cause epilepsy, microcephaly, and cerebral atrophy

“…Bioinformatic analyses (SIFT, PolyPhen2, MutationTaster, CADD, and PhyloP) were used to predict the potential deleterious or pathogenic effect of variants on protein function and also evolutionary conservation. In four subjects (Family 1 individuals II‐1 and II‐2, Family 5 individual II‐1, and Family 6 individual II‐1), absence of heterozygosity (AOH) was determined based on the calculated B‐allele frequency from exome data using an in‐house developed bioinformatic tool, BafCalculator (https://github.com/BCM-Lupskilab/BafCalculator), as previously described 26 . An arbitrary cutoff point or value of 0.5 Mb was used in calculating the size of the AOH, and unphased data or ROH block around the variant as well as the total genomic AOH/ROH.…”

Biallelic CACNA2D2 variants in epileptic encephalopathy and cerebellar atrophy

“…Exome sequencing (ES) was performed on two affected siblings (BH9685‐1 and BH9685‐4) of Turkish descent who were born to consanguineous parents in Family 1 using our standard sequencing and variant prioritization workflow that has been previously described, including BafCalculator for determination of absence of heterozygosity (AOH), potentially reflecting identity‐by‐descent (IBD), from exome variant data . The proband in Family 2 had commercial panel testing from Invitae (San Francisco, California), the Early Infantile Epileptic Encephalopathy Panel (gene content enumerated alphabetically in Table S1), which includes CACNA2D2 .…”

“…(B) Absence of heterozygosity (AOH) plots for Family 1 show that the CACNA2D2 variant lies in a region of AOH in chromosome 3 that is represented by the gray shaded area for both affected siblings (BH9685‐1 and BH9685‐4). AOH regions are calculated using B‐allele frequency data from exome data . (C) T2‐weighted brain MRI images for affected siblings BH9685‐1 and BH9685‐4 show cerebellar atrophy.…”