Genetic Modifiers of Age at Onset in Carriers of the G206A Mutation in PSEN1 With Familial Alzheimer Disease Among Caribbean Hispanics

IMPORTANCE The present study identified potential genetic modifiers that may delay or accelerate age at onset of familial Alzheimer disease (AD) by examining age at onset in PSEN1 mutation carrier families, and further investigation of these modifiers may provide insight into the pathobiology of AD and potential therapeutic measures. DESIGN, SETTING, AND PARTICIPANTS Using a subset of Caribbean Hispanic families that carry the PSEN1 p.G206A mutation, we performed a 2-stage genome study. The mutation carrier families from an ongoing genetic study served as a discovery set, and the cohort of those with LOAD served as a confirmation set. To identify candidate loci, we performed linkage analysis using 5 p.G206A carrier families (n = 56), and we also performed whole-exome association analysis using 31 p.G206A carriers from 26 families. To confirm the genetic modifiers identified from the p.G206A carrier families, we analyzed the GWAS data for 2888 elderly individuals with LOAD. All study participants were Caribbean Hispanics. RESULTS Linkage analysis of AD identified the strongest linkage support at 4q35 (LOD [logarithm of odds] score, 3.69), and the GWAS of age at onset identified variants on 1p13.1, 2q13, 4q25, and 17p11. In the confirmation stage, genewise analysis identified SNX25, PDLIM3, and 3 SH3 domain genes (SORBS2, SH3RF3, and NPHP1) to be significantly associated with LOAD. Subsequent allelic association analysis confirmed SNX25, PDLIM3, and SORBS2 as genetic modifiers of age at onset of EOAD and LOAD and provided modest support for SH3RF3 and NPHP1. CONCLUSIONS AND RELEVANCE Our 2-stage analysis revealed that SNX25, PDLIM3, and SORBS2 may serve as genetic modifiers of age at onset in both EOAD and LOAD

Ultra-rare mutations in SRCAP segregate in Caribbean Hispanic families with Alzheimer disease.

OBJECTIVE: To identify rare coding variants segregating with late-onset Alzheimer disease (LOAD) in Caribbean Hispanic families. METHODS: Whole-exome sequencing (WES) was completed in 110 individuals from 31 Caribbean Hispanic families without APOE ε4 homozygous carriers. Rare coding mutations segregating in families were subsequently genotyped in additional families and in an independent cohort of Caribbean Hispanic patients and controls. SRCAP messenger RNA (mRNA) expression was assessed in whole blood from mutation carriers with LOAD, noncarriers with LOAD, and healthy elderly controls, and also from autopsied brains in 2 clinical neuropathologic cohort studies of aging and dementia. RESULTS: Ten ultra-rare missense mutations in the Snf2-related CREBBP, activator protein (SRCAP), were found in 12 unrelated families. Compared with the frequency in Caribbean Hispanic controls and the Latino population in the Exome Aggregation Consortium, the frequency of SRCAP mutations among Caribbean Hispanic patients with LOAD was significantly enriched (p = 1.19e-16). mRNA expression of SRCAP in whole blood was significantly lower in mutation carriers with LOAD, while the expression in whole blood and in the brain was significantly higher in nonmutation carriers with LOAD. Brain expression also correlated with clinical and neuropathologic endophenotypes. CONCLUSIONS: WES in Caribbean Hispanic families with LOAD revealed ultra-rare missense mutations in SRCAP, a gene expressed in the brain and mutated in Floating-Harbor syndrome. SRCAP is a potent coactivator of the CREB-binding protein and a regulator of DNA damage response involving ATP-dependent chromatin remodeling. We hypothesize that increased expression in LOAD suggests a compensatory mechanism altered in mutation carriers

Rare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools

BackgroundImputation has become a standard approach in genome-wide association studies (GWAS) to infer in silico untyped markers. Although feasibility for common variants imputation is well established, we aimed to assess rare and ultra-rare variants’ imputation in an admixed Caribbean Hispanic population (CH).MethodsWe evaluated imputation accuracy in CH (N = 1,000), focusing on rare (0.1% ≤ minor allele frequency (MAF) ≤ 1%) and ultra-rare (MAF < 0.1%) variants. We used two reference panels, the Haplotype Reference Consortium (HRC; N = 27,165) and 1000 Genome Project (1000G phase 3; N = 2,504) and multiple phasing (SHAPEIT, Eagle2) and imputation algorithms (IMPUTE2, MACH-Admix). To assess imputation quality, we reported: (a) high-quality variant counts according to imputation tools’ internal indexes (e.g., IMPUTE2 “Info” ≥ 80%). (b) Wilcoxon Signed-Rank Test comparing imputation quality for genotyped variants that were masked and imputed; (c) Cohen’s kappa coefficient to test agreement between imputed and whole-exome sequencing (WES) variants; (d) imputation of G206A mutation in the PSEN1 (ultra-rare in the general population an more frequent in CH) followed by confirmation genotyping. We also tested ancestry proportion (European, African and Native American) against WES-imputation mismatches in a Poisson regression fashion.ResultsSHAPEIT2 retrieved higher percentage of imputed high-quality variants than Eagle2 (rare: 51.02% vs. 48.60%; ultra-rare 0.66% vs. 0.65%, Wilcoxon p-value < 0.001). SHAPEIT-IMPUTE2 employing HRC outperformed 1000G (64.50% vs. 59.17%; 1.69% vs. 0.75% for high-quality rare and ultra-rare variants, respectively, Wilcoxon p-value < 0.001). SHAPEIT-IMPUTE2 outperformed MaCH-Admix. Compared to 1000G, HRC-imputation retrieved a higher number of high-quality rare and ultra-rare variants, despite showing lower agreement between imputed and WES variants (e.g., rare: 98.86% for HRC vs. 99.02% for 1000G). High Kappa (K = 0.99) was observed for both reference panels. Twelve G206A mutation carriers were imputed and all validated by confirmation genotyping. African ancestry was associated with higher imputation errors for uncommon and rare variants (p-value < 1e-05).ConclusionReference panels with larger numbers of haplotypes can improve imputation quality for rare and ultra-rare variants in admixed populations such as CH. Ethnic composition is an important predictor of imputation accuracy, with higher African ancestry associated with poorer imputation accuracy

Episodic memory performance in a multi-ethnic longitudinal study of 13,037 elderly

Age-related changes in memory are not uniform, even in the absence of dementia. Characterization of non-disease associated cognitive changes is crucial to gain a more complete understanding of brain aging. Episodic memory was investigated in 13,037 ethnically diverse elderly (ages 72 to 85 years) with two to 15 years of follow-up, and with known dementia status, age, sex, education, and APOE genotypes. Adjusted trajectories of episodic memory performance over time were estimated using Latent Class Mixed Models. Analysis was conducted using two samples at baseline evaluation: i) non-cognitively impaired individuals, and ii) all individuals regardless of dementia status. We calculated the age-specific annual incidence rates of dementia in the non-demented elderly (n = 10,220). Two major episodic memory trajectories were estimated: 1) Stable—consisting of individuals exhibiting a constant or improved memory function, and 2) Decliner—consisting of individuals whose memory function declined. The majority of the study participants maintain their memory performance over time. Compared to those with Stable trajectory, individuals characterized as Decliners were more likely to have non-white ethnic background, fewer years of education, a higher frequency of ε4 allele at APOE gene and five times more likely to develop dementia. The steepest decline in episodic memory was observed in Caribbean-Hispanics compared to non-Hispanic whites (p = 4.3 x 10−15). The highest incident rates of dementia were observed in the oldest age group, among those of Caribbean-Hispanics ancestry and among Decliners who exhibited rates five times higher than those with Stable trajectories (11 per 100 person-years versus 3 per 100 person-years. Age, education, ethnic background and APOE genotype influence the maintenance of episodic memory. Declining memory is one of the strongest predictors of incident dementia

Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.Fil: Keret, Ophir. University of California; Estados UnidosFil: Staffaroni, Adam M.. University of California; Estados UnidosFil: Ringman, John M.. University of Southern California; Estados UnidosFil: Cobigo, Yann. University of California; Estados UnidosFil: Goh, Sheng Yang M.. University of California; Estados UnidosFil: Wolf, Amy. University of California; Estados UnidosFil: Allen, Isabel Elaine. University of California; Estados UnidosFil: Salloway, Stephen. Brown University; Estados UnidosFil: Chhatwal, Jasmeer. Harvard Medical School; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Reyes Dumeyer, Dolly. Columbia University; Estados UnidosFil: Bateman, Randal J.. University of Washington; Estados UnidosFil: Benzinger, Tammie L.S.. University of Washington; Estados UnidosFil: Morris, John C.. University of Washington; Estados UnidosFil: Ances, Beau M.. University of Washington; Estados UnidosFil: Joseph Mathurin, Nelly. University of Washington; Estados UnidosFil: Perrin, Richard J.. University of Washington; Estados UnidosFil: Gordon, Brian A.. University of Washington; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; AlemaniaFil: Vöglein, Jonathan. Ludwig Maximilians Universitat; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Jucker, Mathias. German Center for Neurodegenerative Diseases; Alemania. Eberhard Karls Universität Tübingen; AlemaniaFil: la Fougère, Christian. Eberhard Karls Universität Tübingen; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Martins, Ralph N.. Cooperative Research Centres Australia; Australia. University of Western Australia; Australia. Edith Cowan University; Australia. Australian Alzheimer's Research Foundation; Australia. Macquarie University; AustraliaFil: Sohrabi, Hamid R.. University of Western Australia; Australia. Macquarie University; Australia. Australian Alzheimer's Research Foundation; Australia. Cooperative Research Centres Australia; Australia. Edith Cowan University; AustraliaFil: Taddei, Kevin. Australian Alzheimer's Research Foundation; Australia. Edith Cowan University; AustraliaFil: Villemagne, Victor L.. Austin Health; AustraliaFil: Schofield, Peter R.. Neuroscience Research Australia; Australia. Unsw Medicine; AustraliaFil: Brooks, William S.. Neuroscience Research Australia; Australia. Unsw Medicine; AustraliaFil: Fulham, Michael. Royal Prince Alfred Hospital; AustraliaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: Allegri, Ricardo Francisco. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia. Instituto de Neurociencias - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Neurociencias; Argentin

Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer\u27s disease

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer\u27s disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score\u27s predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials

Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Genomewide analysis of Episodic Memory trajectories in The Mexican Health and Aging Study (MHAS)

Background Genetic characterization of age-related memory changes can help identify population subgroups at-risk of memory decline and dementia. The majority of genetic studies examining memory trajectories in old age have used data from non-Hispanic White populations. To our knowledge, there are no reports of genetic factors underlying memory function over time in the Mexican population. Method Using a previously described latent curve model approach, we estimated episodic memory trajectories in a longitudinal sample from the Mexican Health and Aging Study. We conducted GWAS analyses in a sub-sample of 6,343 participants. Analyses were stratified by memory stability (Stables, n = 4,437) and APOE status. Three independent cohorts were used for replication purposes: two Non-Hispanic White samples from the Alzheimer’s Disease Genetic Consortium and the Religious Orders Study, and a Caribbean-Hispanic sample from the Washington Heights Inwood Community Aging Project. Result The strongest genome-wide significant association was found for an intronic variant in the NR2F1-AS1 gene (rs555528825, p = 1.8×10−9) among APOE non-E4 carriers in the “Stables” group. NR2F1 gene is an evolutionarily conserved long non-coding RNA that enhances neuronal cell maturation and regulates transcription of neuronal genes. SNP variants located less than 50Kb apart from the identified signal showed also nominally significant associations in the three replication datasets (p = 3.9×10−4, p = 1.8×10−4, and p = 0.006 respectively). Additional replication efforts using the UK biobank recourse are ongoing. Conclusion Our study nominates novel genetic variants associated with longitudinal changes in episodic memory performance using data from the Mexican Health and Aging Study, a representative and comprehensive longitudinal study that includes genetic data on a sub-sample of participants 50 years and older

Linkage analysis of multiplex Caribbean Hispanic families loaded for unexplained early-onset cases identifies novel Alzheimer's disease loci

Less than 10% of early-onset Alzheimer's disease (EOAD) is explained by known mutations. We conducted genetic linkage analysis of 68 well-phenotyped Caribbean Hispanic families without clear inheritance patterns or mutations in APP, PSEN1, and PSEN2 and with two or more individuals with EOAD. We identified 16 (logarithm of odds > 3.6) linked regions, including eight novel loci for EOAD (2p15, 5q14.1, 11p15.1, 13q21.22, 13q33.1, 16p12.1, 20p12.1, and 20q11.21) and eight regions previously associated with late-onset Alzheimer's disease. The strongest signal was observed at 16p12.1 (25 cM, 33 Mb; heterogeneity logarithm of odds = 5.3), ∼3 Mb upstream of the ceroid lipofuscinosis 3 (CLN3) gene associated with juvenile neuronal ceroid lipofuscinosis (JNCL), which functions in retromer trafficking and has been reported to alter intracellular processing of the amyloid precursor protein. This study supports the notion that the genetic architectures of unexplained EOAD and late-onset AD overlap partially, but not fully