Population-Based Penetrance of Deleterious Clinical Variants

Abstract

IMPORTANCE Population-based assessment of disease risk associated with gene variants informs clinical decisions and risk stratification approaches. OBJECTIVE To evaluate the population-based disease risk of clinical variants in known disease predisposition genes. DESIGN, SETTING, AND PARTICIPANTS This cohort study included 72 434 individuals with 37 780 clinical variants who were enrolled in the BioMe Biobank from 2007 onwards with follow-up until December 2020 and the UK Biobank from 2006 to 2010 with follow-up until June 2020. Participants had linked exome and electronic health record data, were older than 20 years, and were of diverse ancestral backgrounds.EXPOSURES Variants previously reported as pathogenic or predicted to cause a loss of protein function by bioinformatic algorithms (pathogenic/loss-of-function variants). MAIN OUTCOMES AND MEASURESThe primary outcome was the disease risk associated with clinical variants. The risk difference (RD) between the prevalence of disease in individuals with a variant allele (penetrance) vs in individuals with a normal allele was measured. RESULTS Among 72 434 study participants, 43 395 were from the UK Biobank (mean [SD] age, 57 [8.0] years; 24 065 [55%] women; 2948 [7%] non-European) and 29 039 were from the BioMe Biobank (mean [SD] age, 56 [16] years; 17 355 [60%] women; 19 663 [68%]non-European). Of 5360 pathogenic/loss-of-function variants, 4795 (89%) were associated with an RD less than or equal to 0.05. Mean penetrance was 6.9% (95% CI, 6.0%-7.8%) for pathogenic variants and 0.85% (95% CI, 0.76%-0.95%) for benign variants reported in ClinVar (difference, 6.0 [95% CI,] percentage points), with a median of 0% for both groups due to large numbers of nonpenetrant variants. Penetrance of pathogenic/loss-offunction variants for late-onset diseases was modified by age: mean penetrance was 10.3% (95% CI, 9.0%-11.6%) in individuals 70 years or older and 8.5% (95% CI, 7.9%-9.1%) in individuals 20 years or older (difference, 1.8 [95% CI,] percentage points). Penetrance of pathogenic/loss-of-function variants was heterogeneous even in known disease predisposition genes, including BRCA1 (mean [range], 38% [0%-100%]), BRCA2 (mean [range], 38% [0%-100%]), and PALB2 (mean [range], 26% [0%-100%]). CONCLUSIONS AND RELEVANCEIn 2 large biobank cohorts, the estimated penetrance of pathogenic/loss-of-function variants was variable but generally low. Further research of population-based penetrance is needed to refine variant interpretation and clinical evaluation of individuals with these variant alleles.

Principles of molecular testing for hereditary cancer

“…Initial penetrance estimates from family-based studies may over-estimate penetrance in the broader population. 209 Another important consideration is that within a given gene, penetrance can vary for different types of variants (eg, truncating variants and missense variants 22 ). As well, factors such as family history and polygenic background can modify penetrance; risk prediction models exist for some hereditary cancers (eg, CanRisk, BOADICEA), which integrate information on monogenic variants, polygenic risk, family history, and other clinical risk factors to provide personalized risk estimates to guide management.…”

“…The Gene Curation Coalition (GenCC) database contains information about the validity of gene‐disease relationships 206 . The Clinical Genome Resource (ClinGen) is engaged in ongoing efforts to systematically curate evidence on gene‐disease associations 207,208 . They have found that only a subset of genes commonly included on multigene panels for hereditary breast and ovarian cancer 204 and colorectal cancer and polyposis 205 were supported by strong evidence at the time of the analysis, while others were refuted.…”

Stem Cell Theory of Cancer: Implications for Translational Research from Bedside to Bench

“…Except that a vast majority of genetic mutations may be effects rather than causes of cancer. According to Forrest et al [ 16 ], the chance that a genetic variant (euphemism for mutant) will be linked to a disease diagnosis is relatively low—only about 7%. Therefore, it is expected that there will be many passenger mutations and few driver mutations in a malignant tumor.…”

Quo vadis now: Beyond genomics to an era of personalised medicine

“…Incomplete penetrance is well-recognised for many genetic disorders, and may become the rule rather than the exception, even for rare disorders. 4 As is so often the case with technological advances, the obvious benefits must be balanced against new challenges. In the case of DNA sequencing, the identification of sequence changes in trans does not guarantee a diagnosis, unless the functional significance of these changes can be proven.…”

“…Conversely, a single clinical entity may be caused by many different genes, for example more than 100 genes have now been linked to the disease that Denis Leigh described as subacute necrotising encephalomyelopathy in 1951, 3 and which is now known as Leigh syndrome. Incomplete penetrance is well‐recognised for many genetic disorders, and may become the rule rather than the exception, even for rare disorders 4 …”