Family-Specific Variants and the Limits of Human Genetics

Abstract

Every single-nucleotide change compatible with life is present in the human population today. Understanding these rare human variants defines an extraordinary challenge for genetics and medicine. The new clinical practice of sequencing many genes for hereditary cancer risk has illustrated the utility of clinical next-generation sequencing in adults, identifying more medically actionable variants than single-gene testing. However, it has also revealed a linear relationship between the length of DNA evaluated and the number of rare 'variants of uncertain significance' reported. We propose that careful approaches to phenotype-genotype inference, distinguishing between diagnostic and screening intent, in conjunction with expanded use of family-scale genetics studies as a source of information on family-specific variants, will reduce variants of uncertain significance reported to patients.

Figure 1. The Proportion of all Possible Single Nucleotide Genetic Variants Present in the Human Population

This proportion is related to the population size in relation to the size of the genome. Over 99% of all single nucleotide substitutions compatible with life have been present in at least one living human for about 200 years.

Figure 2. Key Figure. Average Number of Variants of Uncertain Significance Relative to Number of Genes Sequenced

The graph presents the linear relationship between the average number of variants of uncertain significance reported per patient tested for hereditary cancer risk, and the number of genes sequenced at most commercial laboratories. Data were collected from published manuscripts by clinical laboratories performing sequence interpretation. (Kwong et al., 2016, Laduca et al., 2014, Lincoln et al., 2015, Mannan et al., 2016, Maxwell et al., 2014, Shirts et al., 2016, Susswein et al., 2015, Tung et al., 2014)

Figure 3. Co-segregation Analysis in Breast Cancer

Examples of co-segregation analysis in two example families with a history of breast cancer are shown. Individuals analyzed are in colored boxes and the likelihood ratios (LR) corresponding to co-segregation analysis of just those individuals are in colored text. Circles represent women, squares men, and lines indicate relationships. Filled circles indicate breast cancer diagnosis with the age at diagnosis listed below (BrCa ‘age’). “+” indicates a tested individual with the VUS, “-” indicates a tested individual without the VUS. (a) Example family with a hypothetical pathogenic BRCA1 variant. LR >20 is usually sufficient to classify a variant as likely pathogenic and LR >100 is usually classifies a variant as pathogenic. b) Example family with a hypothetical benign BRCA1 variant. LR <0.05 is usually sufficient to classify a variant as likely benign and LR < 0.01 strongly suggests a variant as benign. Including more relatives with a variant increases the probability that a variant will be classified. Figure modified with permission from findmyvariant.org.

Figure 3. Co-segregation Analysis in Breast Cancer

Examples of co-segregation analysis in two example families with a history of breast cancer are shown. Individuals analyzed are in colored boxes and the likelihood ratios (LR) corresponding to co-segregation analysis of just those individuals are in colored text. Circles represent women, squares men, and lines indicate relationships. Filled circles indicate breast cancer diagnosis with the age at diagnosis listed below (BrCa ‘age’). “+” indicates a tested individual with the VUS, “-” indicates a tested individual without the VUS. (a) Example family with a hypothetical pathogenic BRCA1 variant. LR >20 is usually sufficient to classify a variant as likely pathogenic and LR >100 is usually classifies a variant as pathogenic. b) Example family with a hypothetical benign BRCA1 variant. LR <0.05 is usually sufficient to classify a variant as likely benign and LR < 0.01 strongly suggests a variant as benign. Including more relatives with a variant increases the probability that a variant will be classified. Figure modified with permission from findmyvariant.org.