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

Lower Levels of Education Are Associated with Cognitive Impairment in the Old Order Amish

Background: Lower education has been reported to be associated with dementia. However, many studies have been done in settings where 12 years of formal education is the standard. Formal schooling in the Old Order Amish communities (OOA) ends at 8th grade which, along with their genetic homogeneity, makes it an interesting population to study the effect of education on cognitive impairment. Objective: The objective of this study was to examine the association of education with cognitive function in individuals from the OOA. We hypothesized that small differences in educational attainment at lower levels of formal education were associated with risk for cognitive impairment. Methods: Data of 2,426 individuals from the OOA aged 54–99 were analyzed. The Modified Mini-Mental State Examination (3MS-R) was used to classify participants as CI or normal. Individuals were classified into three education categories: 8 years of education. To measure the association of education with cognitive status, a logistic regression model was performed adding age and sex as covariates. Results: Our results showed that individuals who attained lowest levels of education (8 years (OR = 2.96 and 1.85). Conclusion: Even within a setting of low levels of formal education, small differences in educational attainment can still be associated with the risk of cognitive impairment. Given the homogeneity of the OOA, these results are less likely to be biased by differences in socioeconomic backgrounds

Search for protective genetic variants in Alzheimer disease in the U.S. Midwestern Amish

Background Most genetic studies on Alzheimer’s disease (AD) have focused on finding risk genes and variants. Taking into account the 30+ loci identified to increase risk of AD, still only around 40‐50% of the estimated heritability of AD is explained. Our goal is to identify genetic variants that delay the onset or protect against the development of AD and to find novel gene interactions or pathways associated with AD. Method Our study focuses on the Amish communities in Ohio and Indiana due to their homogeneous genetics and environment. Studying genetics in the Amish increases our ability to find rare protective variants for AD that do not exist at a detectable frequency in the general population. Our focus is to identify individuals who are cognitively normal (CN), but at high risk for developing AD (i.e. have an affected sibling). Each of these individuals is retested every two years to assess their cognition status. Results Using the extensive genealogical data of families in the Amish population, we have generated a large ∼5,000 person, 13‐generation pedigree. As of January 2020, we have ascertained 652 individuals and are examining over 300,000 SNPs that were retained after preliminary QC. Out of the recently adjudicated enrollments, 55 percent are cognitively normal, 33 percent are borderline or cognitively impaired, and the remainder have been sampled and are awaiting a consensus diagnosis. The frequency of the APOE‐e2 allele in our enrollments is at 5%, while the APOE‐e4 allele is at 14%, is lower than the general European population. We are currently using KING and GENESIS software to QC the data since they take into account more relatedness in a population structure, which is needed for working with the Amish. Association and linkage analyses, taking into account the complex pedigree relationships, is ongoing. Conclusion We are using a founder population to have an increased chance of finding protective genetic variants in AD. We are specifically targeting individuals who are at high risk for developing AD, but seem to be resilient. This is important in discovering novel pathways in which AD functions, which can lead to further functional and pharmaceutical studies

Genome-wide association for protective variants in Alzheimer's disease in the Midwestern Amish

Alzheimer's disease (AD) is a progressive neurological disease that leads to atrophy of the brain and cognitive decline. There are many factors that play a role in the risk of AD, such as age, smoking, gender, and genetics. the genetic influence on AD is strong, with heritability estimates between 40-60%. Identifying genetic factors that either increase or decrease AD risk are critical in the understanding of this disease. Here, we studied a homogeneous, isolated population - the Ohio and Indiana Amish - to identify protective genetic factors for AD. Our previous studies in the Amish documented numerous individuals who are cognitively normal at advanced ages. Here, we have completed a genome wide association study (GWAS) on Amish individuals who are at high risk for AD (i.e., have an affected sibling and are over 76 years of age), but are cognitively normal. We have genotypes on 2096 individuals, 921 of which are being analyzed for association, in which we have a complex 5,000-person, 13-generation pedigree to help inform our results. MEGAex and GSA chips were used for genotyping. Both KING and GENESIS software were used for quality control and association analyses since they control for both population structure and kinship in evaluating association via a generalized linear mixed model (GLMM). We included 601 cognitively normal (CN), 320 cognitively impaired (CI) individuals. Association analysis was done on a total of 921 individuals, with 256,978 SNPs. We had a total of four SNPs reach a significance threshold of p ≤ 5 x 10 to also include suggestive association loci in our examination. (Nearest genes: DISC1, IQGAP2, and LOC401478 on chromosomes 1, 5 and 8. One SNP on chromosome 13, rs1556774, has no gene association currently known, and no known gene within 80kb.) These loci are currently under further examination. We studied cognitively resilient individuals from a founder population to identify potential protective genetic variants for AD. We identified four SNPs associated with CN in at-risk adults over 75. These loci might influence cognitive resilience. Here we have shed some light on possible genetic factors that may contribute to protection from cognitive decline

Longitudinal assessment of cognitive decline in the Amish

Background The Modified Mini‐Mental State (3MS) is a widely used measure of global cognition. The Old Order Amish are both genetically and environmentally homogeneous, with similar years of formal education across the population. Here, we investigated the longitudinal course of cognitive function as measured by the distribution of 3MS in the Mid‐Western Amish. Method After extensive QC, the 919 subjects with both baseline 3MS and AD status were analyzed. The change from 1st to 2nd measurement was used as the main longitudinal trait of interest. Mean decline differences in 4 baseline age groups (=90) were assessed. The differences in the average longitudinal decline of 3MS between AD cases and controls was assessed using Kolmogorov‐Smirnov tests and ANCOVA adjusted for age at exam and sibship. Result The overall baseline mean 3MS score was 89.52 [42, 100] at the mean age of exam 75.52 [60, 99]. The overall annual rate of decline was ‐0.3 [‐5, 5] from 1st to 2nd measurement (n=242) and ‐0.6 [‐2.1, 1.3] from 2nd to 3rd measurement (n = 23). The annual rate of decline was ‐0.96 [‐4, 1.7] in AD cases (n=18), ‐0.01 [‐5, 5] in AD controls (n=180) and ‐1.08 [‐5, 0.7] in an ‘Unclear’ group (n = 44). The most rapid annual decline of the 3MS was in age 80 to 90 group and the decline rate was significant (p‐value=0.004) compared to the lowest age group (<70) overall and in AD cases. In the Unclear group, the rate of decline was greatest in age 70 to 80. However, in the control group, cognition improved, with a 1.29 [‐1, 5] annual increase in age 80 to 90. The age and sibship adjusted differences in decline were significant (p‐value<2e‐10) between AD cases vs. controls as well as between Unclear vs. controls. Conclusion We explored the changes of 3MS scores over time and demonstrated different patterns of decline by age and AD status in the Amish. Our study is the first in this homogeneous Amish population, providing a better understanding and insight into the cognitive decline examining the change in 3MS over time

The Genetics of Cognitive Resistance and Resilience in the Ohio and Indiana Amish

Abstract Background Alzheimer’s Disease (AD) is a leading cause of death in the US, with limited treatment options. Most studies assess risk factors for AD; however, protective mechanisms demonstrate higher success rates as therapeutic targets. Here, we examine the genetics of Amish individuals maintaining cognitive preservation into advanced age, aiming to uncover protective mechanisms against AD. Method Our dataset consisted of individuals of Amish descent, between 76 – 95 years of age and cognitively unimpaired (CU) with at least one first‐degree relative determined to be either CU or cognitively impaired (CI). 946 Amish individuals met our criteria, were genotyped across their genomes, and incorporated into a single 13‐generation pedigree containing 8,222 individuals. Their complex familial relationships were considered in linkage and genome‐wide association analyses (GWAS). GENESIS was used for GWAS, with XWAS used for the X chromosome. Several parametric and non‐parametric linkage analyses were also performed utilizing MERLIN software for the autosomes and MINX for the X chromosome. Result 106 SNPs (representing 64 loci) reached an initial significance threshold (LOD≥3.3) in linkage analyses. Adjusting for number of independent SNPs in our dataset, no SNPs reached significance after GWAS (P≤6.4×10 −7 ), but 12 loci were suggestive (P≤5×10 −4 ). No loci were suggestive/significant on the X chromosome. For a locus to be further investigated, 1) a significant or suggestive LOD score was required in two or more linkage analyses or 2) one significant LOD score and a suggestive GWAS association within a 10 Mb region were required. After applying these criteria, 8 loci, on chromosomes 1, 2, 3, 7, 11, and 17, were selected for further evaluation. Loci on chromosomes 7 and 11 are within 10 Mb of known AD risk and protective loci, EPHA1 and PICALM, respectively. Significant LOD score results on chromosomes 7, 11, and 17 overlap with coding regions for TBXAS1, DLG2, and SPNS3, respectively. These three loci have been implicated in cognitive impairment relating to neurological disorders. Conclusion We identified 8 loci potentially harboring genes promoting cognitive preservation. These are under further investigation and represent potential therapeutic targets but require experimental studies identifying their specific mechanisms in relationship to AD

Joint linkage and association mapping of preserved cognition in the old‐order Amish

Background Most studies on Alzheimer Disease (AD) have focused on the identification of variants associated with increased risk. The Amish is a genetically homogeneous population ideal to investigate susceptibility genes for complex traits such as AD. This study aims to use family‐based linkage and association approaches to identify genetic variants that protect against the development of cognitive impairment (CI), the central feature of AD. Method A total of 800 adults from Amish communities in Indiana and Ohio were screened for CI using the 3MS test. Individuals were classified as cognitively normal (CN) if the 3MS score was ≥87 at age 75 and cognitively impaired if < 87 at any age. Samples were genotyped on the Illumina Infinium Global Screening or Expanded Multi‐Ethnic Genotyping Array. Over 7 Million common and rare variants were then imputed using the HRC reference panel. For the linkage analysis 75 nuclear families containing at least two CN individuals were analyzed using Merlin to fit multipoint non‐parametric linkage models and parametric affected‐only (AO) dominant and recessive models using a map of more than 40,000 genotyped markers. The genome‐wide association study (GWAS) of imputed variants utilized the program Genesis to fit a logistic regression model 426 CN to 360 CI, associating each variant with cognitive status while adjusting for sex, pc1, pc2 and relatedness. Result The top linkage peaks were seen in the parametric multipoint AO dominant model: Chr3 (HLOD = 2.6) ∼3.9 mb region (21.0 mb – 24.9 mb) and Chr11 (HLOD 2.1) ∼6.5 mb (11.0 mb – 17.5 mb). In the GWAS analysis, no variants reached genome wide significance (5 × 10−8). However, using a lower significance threshold for regional association under a linkage peak (p < 10−5), 7 associated variants were identified in two regions under the Chr11 peak. Conclusion We identified a 6.5 mb area of interest on chromosome 11 associated with preserved cognitive function in Amish adults over age 75, which is near OTOG a previously reported gene associated with AD. This region merits further investigation for functional variants that might slow or prevent the development of cognitive impairment in older adults