11 research outputs found
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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
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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
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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
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Genetic analysis of cognitive preservation in the midwestern Amish reveals a novel locus on chromosome 2
INTRODUCTIONAlzheimer disease (AD) remains a debilitating condition with limited treatments and additional therapeutic targets needed. Identifying AD protective genetic loci may identify new targets and accelerate identification of therapeutic treatments. We examined a founder population to identify loci associated with cognitive preservation into advanced age.METHODSGenome-wide association and linkage analyses were performed on 946 examined and sampled Amish individuals, aged 76-95, who were either cognitively unimpaired (CU) or impaired (CI).RESULTS12 SNPs demonstrated suggestive association (P≤5x10 -4 ) with cognitive preservation. Genetic linkage analyses identified >100 significant (LOD≥3.3) SNPs, some which overlapped with the association results. Only one locus on chromosome 2 retained significance across multiple analyses.DISCUSSIONA novel significant result for cognitive preservation on chromosome 2 includes the genes LRRTM4 and CTNNA2 . Additionally, the lead SNP, rs1402906, impacts the POU3F2 transcription factor binding affinity, which regulates LRRTM4 and CTNNA2
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Founder population-specific weights yield improvements in performance of polygenic risk scores for Alzheimer’s disease in the Midwestern Amish
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Detecting genetic loci for preservation of cognition in the Midwestern United States Amish
Background
Alzheimer’s Disease (AD) is the most common form of dementia and has limited treatments. While AD risk has a large genetic component, under 50% of the genetic risk has been identified. By focusing on identifying genetic variants that delay or prevent the onset of AD, our goal is to identify new associated genes and variants. To detect such loci, we studied cognitive preservation in the Midwestern Amish, a genetically and culturally isolated population of European descent.
Methods
We studied 946 Amish individuals (ages 76‐95) from Ohio and Indiana. Participants were classified as cognitively impaired (33.8%) or cognitively unimpaired (66.2%) by consensus review of cognitive examinations. These individuals were all connected in a 15‐generation 8,222‐person pedigree. This pedigree was divided into 104 sub‐pedigrees via PedCut for linkage analysis. MERLIN was used for autosomal linkage analysis, while MINX was used for X‐chromosome linkage analysis. The association analysis, corrected for genetic relationship, used GENESIS for autosomes and XWAS for the X chromosome.
Results
Over 250,000 SNPs were used for association and two‐point linkage analyses, and a subset of 5,294 uncorrelated SNPs was used for multipoint linkage analyses. on 15 different chromosomes, with the highest two‐point heterogeneity LOD score (HLOD = 5.85) on chromosome 2 (∼79Mb) and highest multipoint HLOD (3.55) on chromosome 12 (∼25Mb), neither overlapping with known AD genes. Two linkage results overlapped with known AD genes (Chr 6: CD2AP; Chr 11: PICALM) and do not overlap with association results. Significant (p ≤ 6.4x10‐7) and suggestive (p ≤ 1x10‐4) thresholds for association were determined using SimpleM. While no significant associations were found, suggestive associations were found for 103 SNPs (11 loci) across 10 chromosomes. Three of these (chr 11: MS4A2; chr 14: SLC24A4; chr 16: IQCK) fall near known AD genes. These significant and suggestive regions are being followed up currently with fine mapping.
Conclusion
Preliminary analyses suggest that using cognitive preservation as our phenotype of interest identifies both known AD loci and novel regions that warrant further evaluation and may lead to a further understanding of both AD and cognitive preservation
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Detecting Protective Rare Variants for Alzheimer’s Disease from Whole‐Genome Sequencing in the Amish
Abstract Background A shift in focus from risk to resilience for Alzheimer’s disease (AD) encourages efforts to uncover novel AD biological mechanisms. Rare variants identified through whole genome sequencing (WGS) may represent an important and understudied component of complex trait genetics. While population‐based studies are powered to discover associations with common genetic variants, founder populations are better powered for discovery of previously unknown rare alleles that have risen to higher frequency due to genetic drift. Method We examined WGS data from the Mid‐Western Amish population in a genome‐wide search for rare coding variants shared only among cognitively‐unimpaired (CU) individuals. The cognitive status of each individual was assigned via consensus review of medical history and neuropsychological testing. Allele frequencies were calculated across all samples and for CU and cognitively‐impaired (CI) groups separately. We defined rare variants as having an allele frequency 10 in the CU group, and 0 in the CI group were annotated to determine likely loss of function. Result After extensive QC, 1,048 samples were available to estimate overall allele frequency. Allele frequencies of rare variants (n = 11,854,817) within 634 CU (mean age = 81.53±6.10, 60% female) and within 184 CI (mean age = 84.77±6.60, 62% female) individuals were compared and 51,616 variants with MAC >10 were found only in CU. There were 316 unique coding variants (288 missense, 4 inframe_insertion, 6 inframe_deletion, 11 frameshift, 4 stop_gained, 3 splice_donor) and 180 synonymous variants located within 425 unique genes. Among them, 7 missense variants and 7 synonymous variants had MAC >20 and the remaining variants had MAC of 11‐20. The mean allele frequency of the 7 missense variants was 0.0038 in TOPMed compared to 0.0154 in our data. Two synonymous variants were located within proposed AD genes (NYAP1 and ZNF423). Additionally, several untranslated region or nonsense‐mediated decay transcript variants existed within 26 known AD gene regions, among which 8 of them are reported to harbor protective variants for AD. Conclusion Numerous rare variants potentially impacting gene function were found only in CU individuals, providing a rich resource for further investigation of genes that may provide protection from cognitive impairment
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Association of mitochondrial haplogroups and cognitive impairment in the Amish
Background
Mitochondrial dysfunction is an important feature of Alzheimer’s Disease (AD) pathogenesis. Reduced glucose utilization and increased oxidative stress are intermediates through which impaired mitochondria may promote AD‐associated brain changes. Association between groups of variants (“haplogroups”) in the mitochondrial genome and AD have been reported for haplogroups U, J, and K. To test these effects in the Amish, we looked for evidence of association between AD‐associated haplogroups and cognitive impairment in a sample of aged Amish individuals.
Method
Cognitive status in adult Amish participants (n=670) with whole‐genome sequence (WGS) data was determined based on modified mini‐mental status exam results (3MS). An outcome of cognitively impaired (CI) was assigned to individuals with an education‐adjusted 3MS < 87 at any age. A status of cognitively unimpaired (CU) was assigned to those aged ≥ 75 scoring ≥ 87 on the 3MS. Mitochondrial variants detected by WGS were used to derive broad haplogroups for each sample using Haplogrep2. Mixed model association testing was performed in GENESIS with CI as the outcome, and haplogroup (U, J, or K), APOE ε4 carrier status (ε4 vs no ε4), sex, and age as predictors. Based on reports of sex‐specific haplogroup U effects on AD, a sex‐stratified analysis was conducted. A random‐effect kinship matrix was used to account for relationships.
Result
Association between mitochondrial haplogroups U, J, or K and CI was not observed at a 5% significance level. The sex‐stratified analysis showed the strongest association of CI with haplogroup U (OR 1.8, 95% CI 0.92‐3.5) among women. Among men, the estimated effect was 0.77 (95% CI 0.37‐1.62). The overall direction of association was opposite in men and women, though neither was statistically significant at 5%.
Conclusion
Although significant evidence of a haplogroup effect on cognitive status was not observed, the moderate sex‐dependent effect of haplogroup U on impairment warrants further examination in an expanded dataset.Previously, haplogroup U was proposed as an AD risk factor among men, whereas it appears as a risk factor for CI in women in the present study
The genetic architecture of Alzheimer disease risk in the Ohio and Indiana Amish
Alzheimer disease (AD) is the most common type of dementia and is currently estimated to affect 6.2 million Americans. It ranks as the sixth leading cause of death in the United States, and the proportion of deaths due to AD has been increasing since 2000, while the proportion of many other leading causes of deaths have decreased or remained constant. The risk for AD is multifactorial, including genetic and environmental risk factors. Although APOE ε4 remains the largest genetic risk factor for AD, more than 26 other loci have been associated with AD risk. Here, we recruited Amish adults from Ohio and Indiana to investigate AD risk and protective genetic effects. As a founder population that typically practices endogamy, variants that are rare in the general population may be of a higher frequency in the Amish population. Since the Amish have a slightly lower incidence and later age of onset of disease, they represent an excellent and unique population for research on protective genetic variants. We compared AD risk in the Amish and to a non-Amish population through APOE genotype, a non-APOE genetic risk score of genome-wide significant variants, and a non-APOE polygenic risk score considering all of the variants. Our results highlight the lesser relative impact of APOE and differing genetic architecture of AD risk in the Amish compared to a non-Amish, general European ancestry population
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Assessing a Network‐Specific Polygenic Risk Score for Alzheimer’s Disease in the Midwestern Amish and Across Diverse Ancestries
Background
Alzheimer’s disease (AD), the most common type of dementia, has a complex etiology with a strong genetic component. Many genetic risk variants for AD have been identified including APOE, the largest known genetic risk factor. However, most of this research has examined only broad populations of individuals with European ancestry and there is mounting evidence that effect sizes vary by population. Here, we investigate the transferability of polygenic risk scores (PRSs), including a network‐specific PRS, in the midwestern Amish and across diverse ancestries.
Method
Data from 1,091 Amish adults with AD diagnosis by consensus were considered for analysis from the Collaborative Amish Aging & Memory Project. Genotype data (Illumina GSA and MEGAEX) were imputed using the Haplotype Reference Consortium panel. We also analyzed 15,745 individuals from the Alzheimer’s Disease Sequencing Project (ADSP) r3 with three predominant race/ethnicity groups: African American (AA; n=2,937), Hispanic (n=3,047), and non‐Hispanic White (NHW; n=9,708). An AD network‐specific PRS was constructed by including variants from AD‐implicated molecular networks in the Kyoto Encyclopedia of Genes and Genomes. A comprehensive pruning and thresholding PRS considering all variants was calculated for comparison. Effect estimates from Kunkle et al. (2019) were used. PRS‐only models, sex and age covariate‐only, and full models were constructed for each group and the full ADSP data.
Result
We observed that PRS‐only predictive ability was similar between the comprehensive PRS (AUC=0.56) and the network‐specific PRS (AUC=0.55) in the full ADSP r3 data. Network‐specific PRS performance was similar in the Amish (AUC=0.55). However, we observed better predictive ability with the comprehensive PRS compared to the network‐specific PRS in each of the subgroups (Amish AUC: 0.61 vs. 0.55; NHW: 0.70 vs. 0.53; AA: 0.56 vs. 0.53, Hispanic: 0.61 vs. 0.56). These trends were consistent after inclusion of sex and age covariates.
Conclusion
We demonstrated that a network‐specific PRS performed similarly to a comprehensive PRS in a combined diverse population and the Amish but confers less predictive ability when investigating individual subgroups. Thus, the network‐specific PRS has potential as a component of a risk model in diverse populations because it may successfully account for effects that are consistent across subgroups