Assessing the phenotypic effects in the general population of rare variants in genes for a dominant Mendelian form of diabetes

Abstract

Genome sequencing can identify individuals in the general population who harbor rare coding variants in genes for Mendelian disorders and who may consequently have increased disease risk. Previous studies of rare variants in phenotypically extreme individuals display ascertainment bias and may demonstrate inflated effect-size estimates. We sequenced seven genes for maturity-onset diabetes of the young (MODY) in well-phenotyped population samples (n = 4,003). We filtered rare variants according to two prediction criteria for disease-causing mutations: reported previously in MODY or satisfying stringent de novo thresholds (rare, conserved and protein damaging). Approximately 1.5% and 0.5% of randomly selected individuals from the Framingham and Jackson Heart Studies, respectively, carry variants from these two classes. However, the vast majority of carriers remain euglycemic through middle age. Accurate estimates of variant effect sizes from population-based sequencing are needed to avoid falsely predicting a substantial fraction of individuals as being at risk for MODY or other Mendelian diseases.

Figures

Figure 1. Description of low frequency non-synonymous variants

Shown is a summary of all low frequency (MAFlow frequency non-synonymous (black, magenta, orange, or green), possibly pathogenic (orange or green), HGMD MODY (magenta or green), and putative pathogenic (green). Twelve low frequency variants fit no annotations. Low frequency non-synonymous is abbreviated to ‘Nonsyn <1%’.

Figure 2. Phenotypic impact of variants in unselected cohorts

Shown is the fraction of variant carriers in the two unselected cohorts with (a) diabetes and (b) IFG or diabetes. Separate fractions are given for each of the four defined variant classes, with the fraction of non-carriers with each phenotype shown as reference. Error bars reflect 68% confidence intervals in the estimated fractions and are computed via the Clopper-Pearson method. The number of analyzed samples is given in Supplementary Table 6. Fewer individuals had FPG measurements than diabetes measurements; thus the number of analyzed individuals for these two phenotypes differs. ‘Nonsyn <1%’ is low frequency non-synonymous, ‘Pos. Pathogenic’ is possibly pathogenic, and ‘Put. Pathogenic’ is putative pathogenic.

Figure 3. Phenotypes of GCK and HNF1A variant carriers

(a) Shown are FPG values for GCK-variant carriers in the FHS cohort (left) and JHS cohort (right). Three dashed lines correspond to defined FPG thresholds: top (solid) line represents diabetes (126 mg/dL), middle (dashed) line IFG (100 mg/dL), bottom (dotted) line GCK-MODY (99mg/dL). A histogram and box plot representing FPG levels in the non-diabetic population (computed separately for each cohort) is shown for comparison. Two GCK variant carriers were on medication for diabetes and are thus excluded from the plot. Tabular form of these results (including the two carriers with diabetes) is shown in Supplementary Table 10. (b) The scatter plot shows fasting-2hr post-OGTT plasma glucose increment (y-axis) and FPG (x-axis) for each HNF1A-variant carrier in the FHS cohort (OGTT information was unavailable for the JHS cohort). Histograms showing FPG and fasting-2hr post-OGTT plasma glucose increments for individuals in the FHS cohort without diabetes are shown on the left and below the scatter plot respectively. FPG values for individuals receiving treatment for diabetes were omitted from the plot. The vertical and horizontal dashed lines represent the IFG threshold (100mg/dL) and a plasma glucose increment consistent with HNF1A-MODY/beta-cell dysfunction (≥90mg/dL) respectively. Points are colored corresponding to the annotation class of the variant; for variants that belong to multiple classes, colors are chosen according to the following precedence: putative pathogenic, HGMD MODY, possibly pathogenic, low frequency non-synonymous.