Investigation of discordant sibling pairs from hereditary breast cancer families and analysis of a rare PMS1 variant

BACKGROUND

It is likely that additional genes for hereditary breast cancer can be identified using a discordant sib pair design. Using this design we identified individuals harboring a rare PMS1 c.605G>A variant previously predicted to result in loss of function.

OBJECTIVES

A family-based design and predictive algorithms were used to prioritize candidate variants possibly associated with an increased risk of hereditary breast cancer. Functional analyses were performed for one of the candidate variants, PMS1 c.605G>A.

METHODS

1) 14 discordant sister-pairs from hereditary breast cancer families were identified. 2) Whole exome sequencing was performed and candidate risk variants identified. 3) A rare PMS variant was identified in 2 unrelated affected sisters but no unaffected siblings. 4) Functional analysis of this variant was carried out using targeted mRNA sequencing.

RESULTS

Genotype-phenotype correlation did not demonstrate tracking of the variant with cancer in the family. Functional analysis revealed no difference in exon 6 incorporation, which was validated by analyzing PMS1 allele specific expression.

CONCLUSIONS

The PMS1 c.605G>A variant did not segregate with disease, and there was no variant-dependent impact on PMS1 exon 6 splicing, supporting this variant is likely benign. Functional analyses are imperative to understanding the clinical significance of predictive algorithms.

Natural genetic variation profoundly regulates gene expression in immune cells and dictates susceptibility to CNS autoimmunity

Regulation of gene expression in immune cells is known to be under genetic control, and likely contributes to susceptibility to autoimmune diseases such as multiple sclerosis (MS). How this occurs in concert across multiple immune cell types is poorly understood. Using a mouse model that harnesses the genetic diversity of wild-derived mice, more accurately reflecting genetically diverse human populations, we provide an extensive characterization of the genetic regulation of gene expression in five different naive immune cell types relevant to MS. The immune cell transcriptome is shown to be under profound genetic control, exhibiting diverse patterns: global, cell-specific and sex-specific. Bioinformatic analysis of the genetically controlled transcript networks reveals reduced cell type specificity and inflammatory activity in wild-derived PWD/PhJ mice, compared with the conventional laboratory strain C57BL/6J. Additionally, candidate MS-GWAS (genome-wide association study candidate genes for MS susceptibility) genes were significantly enriched among transcripts overrepresented in C57BL/6J cells compared with PWD. These expression level differences correlate with robust differences in susceptibility to experimental autoimmune encephalomyelitis, the principal model of MS, and skewing of the encephalitogenic T-cell responses. Taken together, our results provide functional insights into the genetic regulation of the immune transcriptome, and shed light on how this in turn contributes to susceptibility to autoimmune disease.