Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.