Challenges in providing residual risks in carrier testing

The probability an individual is a carrier for a recessive disorder despite a negative carrier test, referred to as residual risk, has been part of carrier screening for over 2 decades. Residual risks are calculated by subtracting the frequency of carriers of pathogenic variants detected by the test from the carrier frequency in a population, estimated from the incidence of the disease. Estimates of the incidence (and therefore carrier frequency) of many recessive disorders differ among different population groups and are inaccurate or unavailable for many genes on large carrier screening panels for most of the world's populations. The pathogenic variants detected by the test and their frequencies also vary across groups and over time as variants are newly discovered or reclassified, which requires today's residual carrier risks to be continually updated. Even when a residual carrier risk is derived using accurate data obtained in a particular group, it may not apply to many individuals in that group because of misattributed ancestry or unsuspected admixture. Missing or inaccurate data, the challenge of determining meaningful ancestry-specific risks and applying them appropriately, and a lack of evidence they impact management, suggest that patients be counseled that although carrier screening may miss a small fraction of carriers, residual risks with contemporary carrier screening are well below the risk posed by invasive prenatal diagnosis, even if one member of the couple is a carrier, and that efforts to provide precise residual carrier risks are unnecessary.     

Influence of groundwater recharge and well characteristics on dissolved arsenic concentrations in southeastern Michigan groundwater

Arsenic concentrations exceeding 10 μg/l, the United States maximum contaminant level and the World Health Organization guideline value, are frequently reported in groundwater from bedrock and unconsolidated aquifers of southeastern Michigan. Although arsenic-bearing minerals (including arsenian pyrite and oxide/hydroxide phases) have been identified in Marshall Sandstone bedrock of the Mississippian aquifer system and in tills of the unconsolidated aquifer system, mechanisms responsible for arsenic mobilization and subsequent transport in groundwater are equivocal. Recent evidence has begun to suggest that groundwater recharge and characteristics of well construction may affect arsenic mobilization and transport. Therefore, we investigated the relationship between dissolved arsenic concentrations, reported groundwater recharge rates, well construction characteristics, and geology in unconsolidated and bedrock aquifers. Results of multiple linear regression analyses indicate that arsenic contamination is more prevalent in bedrock wells that are cased in proximity to the bedrock-unconsolidated interface; no other factors were associated with arsenic contamination in water drawn from bedrock or unconsolidated aquifers. Conditions appropriate for arsenic mobilization may be found along the bedrock-unconsolidated interface, including changes in reduction/oxidation potential and enhanced biogeochemical activity because of differences between geologic strata. These results are valuable for understanding arsenic mobilization and guiding well construction practices in southeastern Michigan, and may also provide insights for other regions faced with groundwater arsenic contamination.     

Evaluation and classification of severity for 176 genes on an expanded carrier screening panel

Background

Disease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG).

Methods

Eight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene.

Results

Upon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four.

Conclusion

This study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation.