Consequences of a Rare Complement Factor H Variant for Age-Related Macular Degeneration in the Amish

PURPOSE. Genetic variants in the complement factor H gene (CFH) have been consistently implicated in age-related macular degeneration (AMD) risk. However, their functional effects are not fully characterized. We previously identified a rare, AMD-associated variant in CFH (P503A, rs570523689) in 19 Amish individuals, but its functional consequences were not investigated. METHODS. We performed genotyping for CFH P503A in 1326 Amish individuals to identify additional risk allele carriers. We examined differences for age at AMD diagnosis between carriers and noncarriers. In blood samples from risk allele carriers and noncarriers, we quantified (i) CFH RNA expression, (ii) CFH protein expression, and (iii) C -reactive protein (CRP) expression. Potential changes to the CFH protein structure were interrogated computationally with Phyre2 and Chimera software programs. RESULTS. We identified 39 additional carriers from Amish communities in Ohio and Indiana. On average, carriers were younger than noncarriers at AMD diagnosis, but this difference was not significant. CFH transcript and protein levels in blood samples from Amish carriers and noncarriers were also not significantly different. CRP levels were also comparable in plasma samples from carriers and noncarriers. Computational protein modeling showed slight changes in the CFH protein conformation that were predicted to alter interactions between the CFH 503 residue and other neighboring residues. CONCLUSIONS. In total, we have identified 58 risk allele carriers for CFH P503A in the Ohio and Indiana Amish. Although we did not detect significant differences in age at AMD diagnosis or expression levels of CFH in blood samples from carriers and noncarriers, we observed modest structural changes to the CFH protein through in silico modeling. Based on our functional and computational observations, we hypothesize that CFH P503A may affect CFH binding or function rather than expression, which would require additional research to confirm

Rare variants and loci for age-related macular degeneration in the Ohio and Indiana Amish

Age-related macular degeneration (AMD) is a leading cause of blindness in the world. While dozens of independent genomic variants are associated with AMD, about one-third of AMD heritability is still unexplained. To identify novel variants and loci for AMD, we analyzed Illumina HumanExome chip data from 87 Amish individuals with early or late AMD, 79 unaffected Amish individuals, and 15 related Amish individuals with unknown AMD affection status. We retained 37,428 polymorphic autosomal variants across 175 samples for association and linkage analyses. After correcting for multiple testing (n = 37,428), we identified four variants significantly associated with AMD: rs200437673 (LCN9, p = 1.50 × 10 ), rs151214675 (RTEL1, p = 3.18 × 10 ), rs140250387 (DLGAP1, p = 4.49 × 10 ), and rs115333865 (CGRRF1, p = 1.05 × 10 ). These variants have not been previously associated with AMD and are not in linkage disequilibrium with the 52 known AMD-associated variants reported by the International AMD Genomics Consortium based on physical distance. Genome-wide significant linkage peaks were observed on chromosomes 8q21.11-q21.13 (maximum recessive HLOD = 4.03) and 18q21.2-21.32 (maximum dominant HLOD = 3.87; maximum recessive HLOD = 4.27). These loci do not overlap with loci previously linked to AMD. Through gene ontology enrichment analysis with ClueGO in Cytoscape, we determined that several genes in the 1-HLOD support interval of the chromosome 8 locus are involved in fatty acid binding and triglyceride catabolic processes, and the 1-HLOD support interval of the linkage region on chromosome 18 is enriched in genes that participate in serine-type endopeptidase inhibitor activity and the positive regulation of epithelial to mesenchymal transition. These results nominate novel variants and loci for AMD that require further investigation

Psychometric Approaches to Defining Cognitive Phenotypes in the Old Order Amish

Memory and cognitive problems are central to the diagnosis of Alzheimer's disease (AD). Psychometric approaches to defining phenotypes can aid in identify genetic variants associated with AD. However, these approaches have mostly been limited to affected individuals. Defining phenotypes of both affected and unaffected individuals may help identify genetic variants associated with both AD and healthy aging. This study compares psychometric methods for developing cognitive phenotypes that are more granular than clinical classifications. 682 older Old Order Amish individuals were included in the analysis. Adjusted Z-scores of cognitive tests were used to create four models including 1) global threshold scores or 2) memory threshold scores, and 3) global clusters and 4) memory clusters. An ordinal regression examined the coherence of the models with clinical classifications [cognitively impaired (CI), mildly impaired (MI), cognitively unimpaired (CU)], APOE-e4, sex, and age. An ANOVA examined the best model phenotypes for differences in clinical classification, APOE-e4, domain Z-scores (memory, language, executive function, and processing speed), sex, and age. The memory cluster identified four phenotypes and had the best fit (χ = 491.66). Individuals in the worse performing phenotypes were more likely to be classified as CI or MI and to have APOE-e4. Additionally, all four phenotypes performed significantly differently from one another on the domains of memory, language, and executive functioning. Memory cluster stratification identified the cognitive phenotypes that best aligned with clinical classifications, APOE-e4, and cognitive performance We predict these phenotypes will prove useful in searching for protective genetic variants. This article is protected by copyright. All rights reserved

Psychometric approaches to defining cognitive phenotypes in the Old Order Amish

Objective: Memory and cognitive problems are central to the diagnosis of Alzheimer's disease (AD). Psychometric approaches to defining phenotypes can aid in identify genetic variants associated with AD. However, these approaches have mostly been limited to affected individuals. Defining phenotypes of both affected and unaffected individuals may help identify genetic variants associated with both AD and healthy aging. This study compares psychometric methods for developing cognitive phenotypes that are more granular than clinical classifications.Methods: 682 older Old Order Amish individuals were included in the analysis. Adjusted Z-scores of cognitive tests were used to create four models including (1) global threshold scores or (2) memory threshold scores, and (3) global clusters and (4) memory clusters. An ordinal regression examined the coherence of the models with clinical classifications (cognitively impaired [CI], mildly impaired [MI], cognitively unimpaired), APOE-e4, sex, and age. An ANOVA examined the best model phenotypes for differences in clinical classification, APOE-e4, domain Z-scores (memory, language, executive function, and processing speed), sex, and age.Results: The memory cluster identified four phenotypes and had the best fit (?(2) = 491.66). Individuals in the worse performing phenotypes were more likely to be classified as CI or MI and to have APOE-e4. Additionally, all four phenotypes performed significantly differently from one another on the domains of memory, language, and executive functioning.Conclusions: Memory cluster stratification identified the cognitive phenotypes that best aligned with clinical classifications, APOE-e4, and cognitive performance We predict these phenotypes will prove useful in searching for protective genetic variants

Examination of candidate exonic variants for association to Alzheimer disease in the Amish.

Alzheimer disease (AD) is the most common cause of dementia. As with many complex diseases, the identified variants do not explain the total expected genetic risk that is based on heritability estimates for AD. Isolated founder populations, such as the Amish, are advantageous for genetic studies as they overcome heterogeneity limitations associated with complex population studies. We determined that Amish AD cases harbored a significantly higher burden of the known risk alleles compared to Amish cognitively normal controls, but a significantly lower burden when compared to cases from a dataset of unrelated individuals. Whole-exome sequencing of a selected subset of the overall study population was used as a screening tool to identify variants located in the regions of the genome that are most likely to contribute risk. By then genotyping the top candidate variants from the known AD genes and from linkage regions implicated previous studies in the full dataset, new associations could be confirmed. The most significant result (p = 0.0012) was for rs73938538, a synonymous variant in LAMA1 within the previously identified linkage peak on chromosome 18. However, this association is specific to the Amish and did not generalize when tested in a dataset of unrelated individuals. These results suggest that additional risk variation in the Amish remains to be identified and likely resides outside of the classical protein coding gene regions

Heritability of Choroidal Thickness in the Amish

To evaluate the heritability of choroidal thickness and its relationship to age-related macular degeneration (AMD). Cohort study. Six hundred eighty-nine individuals from Amish families with early or intermediate AMD. Ocular coherence tomography was used to quantify choroidal thickness, and fundus photography was used to classify eyes into categories using a modified Clinical Age-Related Maculopathy Staging (CARMS) system. Repeatability and heritability of choroidal thickness and its phenotypic and genetic correlations with the AMD phenotype (CARMS category) were estimated using a generalized linear mixed model (GLMM) approach that accounted for relatedness, repeated measures (left and right eyes), and the effects of age, gender, and refraction. Heritability of choroidal thickness and its phenotypic and genetic correlation with the AMD phenotype (CARMS category). Phenotypic correlation between choroidal thickness and CARMS category was moderate (Spearman's rank correlation, r  = -0.24; n = 1313 eyes) and significant (GLMM posterior mean, -4.27; 95% credible interval [CI], -7.88 to -0.79; P = 0.02) after controlling for relatedness, age, gender, and refraction. Eyes with advanced AMD had thinner choroids than eyes without AMD (posterior mean, -73.8; 95% CI, -94.7 to -54.6; P < 0.001; n = 1178 eyes). Choroidal thickness was highly repeatable within individuals (repeatability, 0.78; 95% CI, 0.68 to 0.89) and moderately heritable (heritability, 0.40; 95% CI, 0.14 to 0.51), but did not show significant genetic correlation with CARMS category, although the effect size was moderate (genetic correlation, -0.18; 95% CI, -0.49 to 0.16). Choroidal thickness also varied with age, gender, and refraction. The CARMS category showed moderate heritability (heritability, 0.49; 95% CI, 0.26 to 0.72). We quantify the heritability of choroidal thickness for the first time, highlighting a heritable, quantitative trait that is measurable in all individuals regardless of AMD affection status, and moderately phenotypically correlated with AMD severity. Choroidal thickness therefore may capture variation not captured by the CARMS system. However, because the genetic correlation between choroidal thickness and AMD severity was not significant in our data set, genes associated with the 2 traits may not overlap substantially. Future studies should therefore test for genetic variation associated with choroidal thickness to determine the overlap in genetic basis with AMD