Thyroid Function, Diabetes, and Common Age-Related Eye Diseases: A Mendelian Randomization Study

Abstract

Background: Previous Mendelian randomization (MR) studies showed an association between hypothyroidism and cataract and between high-normal free thyroxine (FT4) and late age-related macular degeneration (AMD), but not between FT4, thyroid stimulating hormone (TSH), or hyperthyroidism and diabetic retinopathy or cataract. These studies included a limited number of genetic variants for thyroid function and did not investigate autoimmune thyroid disease (AITD) or glaucoma, include bidirectional and multivariable MR (MVMR), and examine sex differences or potential mediation effects of diabetes. We aimed to address this knowledge gap. Methods: We examined the causality and directionality of the associations of AITD, and FT4 and TSH within the reference range with common age-related eye diseases (diabetic retinopathy, cataract, early and late AMD, and primary open-angle glaucoma). We conducted a bidirectional two-sample MR study utilizing publicly available genome-wide association study (GWAS) summary statistics from international consortia (ThyroidOmics, International AMD Genetics Consortium, deCODE, UK Biobank, FinnGen, and DIAGRAM). Bidirectional MR tested directionality, whereas MVMR estimated independent causal effects. Furthermore, we investigated type 1 diabetes (T1D) and type 2 diabetes (T2D) as potential mediators. Results: Genetic predisposition to AITD was associated with increased risk of diabetic retinopathy (p = 3 × 10^-4), cataract (p = 3 × 10^-3), and T1D (p = 1 × 10^-3), but less likely T2D (p = 0.01). MVMR showed attenuated estimates for diabetic retinopathy and cataract when adjusting for T1D, but not T2D. We found pairwise bidirectional associations between AITD, T1D, and diabetic retinopathy. Genetic predisposition to both T1D and T2D increased the risk of diabetic retinopathy and cataract (p < 4 × 10^-4). Moreover, genetically predicted higher FT4 within the reference range was associated with an increased risk of late AMD (p = 0.01), particularly in women (p = 7 × 10^-3). However, we neither found any association between FT4 and early AMD nor between TSH and early and late AMD. No other associations were observed. Conclusions: Genetic predisposition to AITD is associated with risk of diabetic retinopathy and cataract, mostly mediated through increased T1D risk. Reciprocal associations between AITD, diabetic retinopathy, and T1D imply a shared autoimmune origin. The role of FT4 in AMD and potential sex discrepancies needs further investigation.

Keywords: age-related macular degeneration (AMD); autoimmune thyroid disease; cataract; diabetic retinopathy; glaucoma; thyroid function.

FIG. 1.

Conceptual illustration of the Mendelian randomization (MR) approach with three core assumptions (A) and bidirectional Mendelian randomization analysis (B). MR is a robust approach that combines genetic variant data, usually single nucleotide polymorphisms (SNPs), with observational epidemiological data to strengthen causal inference without intervention. Its name is inspired by Mendel’s laws of heritability and the similarity to randomized controlled trials (RCTs). As per Mendel’s laws of independent assortment and segregation, potential confounders are evenly distributed across genotypes established at conception, thereby largely avoiding confounding and reverse causation, similar to RCTs. Essentially, MR assesses both the direction and magnitude of the effect of genetically predicted life-long exposure on the outcome. The three core MR assumptions (Figure shown in panel A) are: (1) relevance (genetic variants [Z] are robustly associated with the exposure [X]), (2) independence (confounders are not associated with genetic variants [Z] or outcome [Y]), and (3) exclusion restriction (genetic variants are only associated with the outcome [Y] through the exposure [X], and no other pathway). We used genetic variants associated with thyroid function to examine the potential causal effect of thyroid function (thyroid disease as well as thyroid hormones within reference range) on common age-related eye diseases. The summary statistics, comprising β-coefficients and standard errors (SEs), for the SNP-exposure (β_ZX), and the SNP-outcome (β_ZY) associations were publicly available from large genome-wide association studies consortia. The overall causal estimates were calculated by performing meta-analyses across the individual causal estimates (Wald ratio: β_XY = β_ZY / β_ZX) and their SEs. The identified potentially causal associations (of autoimmune thyroid disease [AITD] with diabetic retinopathy and cataract) were tested for bidirectionality with bidirectional MR (Fig. panel 2B). The dashed boxes represent that AITD and eye diseases (diabetic retinopathy and cataract) were considered as exposures as well as outcomes, depending on the direction of the association examined (arrows).

FIG. 2.

Bidirectional Mendelian randomization (MR) analyses between autoimmune thyroid disease (AITD) and diabetic retinopathy. Estimates (odds ratios [ORs] and 95% confidence intervals [CIs]) from the main random-effects inverse variance weighted (IVW), and sensitivity MR analyses (MR-Lasso, weighted median, and MR-Egger) are expressed as ORs for genetic predisposition to the relevant exposure. Note that the estimate sizes do not have a clear interpretation and can only be used to assess the null hypothesis (see Materials and Methods). For each exposure and method, the number of single nucleotide polymorphisms (SNPs) included in the analysis is shown in parenthesis. AITD included 30,234 cases and 755,172 controls from Iceland and UK Biobank (deCODE Consortium) and was based on ICD-10 codes E06.3 (Hashimoto’s thyroiditis), E05.9 (Graves’ disease), E03.9 (other unspecified hypothyroidism) and/or thyroxine treatment, excluding known nonautoimmune causes of hypothyroidism, and consisted therefore predominantly of hypothyroidism. Diabetic retinopathy included 14,584 cases and 202,082 controls from Finland (FinnGen Consortium). Additional sensitivity statistics are shown in Supplementary Tables S3 and Supplementary Table S4.

FIG. 3.

Bidirectional Mendelian randomization (MR) analyses between autoimmune thyroid disease (AITD) and cataract. Estimates (odds ratios [ORs] and 95% confidence intervals [CIs]) from the main random-effects inverse variance weighted (IVW), and sensitivity MR analyses (MR-Lasso, weighted median and MR-Egger) are expressed as ORs for genetic predisposition to the relevant exposure. Note that the estimate sizes do not have a clear interpretation and can only be used to assess the null hypothesis (see Materials and Methods). For each exposure and method, the number of single nucleotide polymorphisms (SNPs) included in the analysis is shown in parenthesis. AITD included 30,234 cases and 755,172 controls from Iceland and UK Biobank (deCODE Consortium) and was based on ICD-10 codes E06.3 (Hashimoto’s thyroiditis), E05.9 (Graves’ disease), E03.9 (other unspecified hypothyroidism), and/or thyroxine treatment, excluding known non-autoimmune causes of hypothyroidism, and consisted therefore predominantly of hypothyroidism. Cataract included 26,758 cases and 189,604 controls from Finland (FinnGen consortium). Additional sensitivity statistics are shown in Supplementary Tables S5 and Supplementary Table S6.

FIG. 4.

Multivariable Mendelian randomization (MVMR) analyses between autoimmune thyroid disease (AITD), diabetic retinopathy, and cataract. Estimates (odds ratios [ORs] and 95% confidence intervals [CIs]) are based on the inverse variance weighted MR method and expressed as ORs for genetic predisposition to the relevant exposure. Note that the estimate sizes do not have a clear interpretation and can only be used to assess the null hypothesis (see Materials and Methods). MVMR estimated the independent (adjusted) causal effects of AITD on diabetic retinopathy and cataract when adjusted for: type 1 diabetes (MVMR, +T1D), type 2 diabetes (MVMR, +T2D), or both T1D and T2D (MVMR, +T1D+T2D). For each exposure and method, the number of single nucleotide polymorphisms (SNPs) included in the analysis is shown in parenthesis. AITD included 30,234 cases and 755,172 controls from Iceland and UK Biobank (deCODE Consortium) and was based on ICD-10 codes E06.3 (Hashimoto’s thyroiditis), E05.9 (Graves’ disease), E03.9 (other unspecified hypothyroidism) and/or thyroxine treatment, excluding known nonautoimmune causes of hypothyroidism, and consisted therefore predominantly of hypothyroidism.Diabetic retinopathy (14,584 cases and 202,082 controls) and cataract (26,758 cases and 189,604 controls) were from Finland (FinnGen Consortium). Corresponding MVMR estimates for T1D and T2D are shown in Supplementary Table S7.

FIG. 5.

Type 1 diabetes (T1D) as a mediator of the autoimmune thyroid disease (AITD) association with diabetic retinopathy and cataract. Estimates (odds ratios [ORs] and 95% confidence intervals [CIs]) are based on the random-effects inverse variance weighted MR method and expressed as ORs for genetic predisposition to the relevant exposure. Note that the estimate sizes do not have a clear interpretation and can only be used to assess the null hypothesis (see Materials and Methods). AITD included 30,234 cases and 755,172 controls from Iceland and UK Biobank (deCODE Consortium) and was based on ICD-10 codes E06.3 (Hashimoto’s thyroiditis), E05.9 (Graves’ disease), E03.9 (other unspecified hypothyroidism), and/or thyroxine treatment, excluding known nonautoimmune causes of hypothyroidism, and consisted therefore predominantly of hypothyroidism. T1D included 7467 cases and 10,218 controls of European ancestry, and did not include UK Biobank participants. Diabetic retinopathy (14,584 cases and 202,082 controls) and cataract (26,758 cases and 189,604 controls) were from Finland (FinnGen Consortium). Additional sensitivity statistics (including type 2 diabetes) are shown in Supplementary Tables S3, Supplementary Table S4, Table and Table S8–S11.

FIG. 6.

Mendelian randomization (MR) estimates for the association of genetically predicted thyroid hormone levels with the risk of late age-related macular degeneration (AMD). Estimates (odds ratios [ORs] and 95% confidence intervals [CIs]) are based on the inverse variance weighted MR method and expressed as ORs per one standard deviation increase in the relevant exposure. For each exposure, the number of single nucleotide polymorphisms (SNPs) included in the analysis is shown in parenthesis. Thyroid hormone levels were from the ThyroidOmics Consortium and included individuals with measurements of free thyroxine (FT4) and thyroid stimulating hormone (TSH) within the (cohort-specific) reference range. FT4, all* was measured in up to 119,120 and TSH, all* in up to 271,040 individuals. However, sex-stratified summary statistics on FT4 and TSH levels were only available in a smaller subset of these individuals (FT4, all: 49,269; FT4, women: 26,954; FT4, men: 22,315; TSH, all: 54,288; TSH, women: 29,670; TSH, men: 24,618). AITD included 30,234 cases and 755,172 controls from Iceland and UK Biobank (deCODE Consortium) and was based on ICD-10 codes E06.3 (Hashimoto’s thyroiditis), E05.9 (Graves’ disease), E03.9 (other unspecified hypothyroidism) and/or thyroxine treatment, excluding known nonautoimmune causes of hypothyroidism, and consisted therefore predominantly of hypothyroidism. Additional sensitivity statistics are shown in Supplementary Tables S3, Supplementary Table S4, Table and Supplementary Table S12.