Categorizing people with late-onset Alzheimer's disease into biologically coherent subgroups is important for personalized medicine. We evaluated data from five studies (total n = 4050, of whom 2431 ...had genome-wide single-nucleotide polymorphism (SNP) data). We assigned people to cognitively defined subgroups on the basis of relative performance in memory, executive functioning, visuospatial functioning, and language at the time of Alzheimer's disease diagnosis. We compared genotype frequencies for each subgroup to those from cognitively normal elderly controls. We focused on APOE and on SNPs with p < 10
and odds ratios more extreme than those previously reported for Alzheimer's disease (<0.77 or >1.30). There was substantial variation across studies in the proportions of people in each subgroup. In each study, higher proportions of people with isolated substantial relative memory impairment had ≥1 APOE ε4 allele than any other subgroup (overall p = 1.5 × 10
). Across subgroups, there were 33 novel suggestive loci across the genome with p < 10
and an extreme OR compared to controls, of which none had statistical evidence of heterogeneity and 30 had ORs in the same direction across all datasets. These data support the biological coherence of cognitively defined subgroups and nominate novel genetic loci.
Alzheimer's disease (AD) is a complex disorder influenced by environmental and genetic factors. Recent work has identified 11 AD markers in 10 loci. We used Genome-wide Complex Trait Analysis to ...analyze >2 million SNPs for 10,922 individuals from the Alzheimer's Disease Genetics Consortium to assess the phenotypic variance explained first by known late-onset AD loci, and then by all SNPs in the Alzheimer's Disease Genetics Consortium dataset. In all, 33% of total phenotypic variance is explained by all common SNPs. APOE alone explained 6% and other known markers 2%, meaning more than 25% of phenotypic variance remains unexplained by known markers, but is tagged by common SNPs included on genotyping arrays or imputed with HapMap genotypes. Novel AD markers that explain large amounts of phenotypic variance are likely to be rare and unidentifiable using genome-wide association studies. Based on our findings and the current direction of human genetics research, we suggest specific study designs for future studies to identify the remaining heritability of Alzheimer's disease.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits’ ...genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (Ntotal≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD’s correlation with cognitive traits and hints at an autoimmune component for ALS.
Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis ...of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex ...relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.
To better understand clinical and neuropathological features of TDP-43 proteinopathies, data were analyzed from autopsied research volunteers who were followed in the National Alzheimer’s ...Coordinating Center (NACC) data set. All subjects (
n
= 495) had autopsy-proven TDP-43 proteinopathy as an inclusion criterion. Subjects underwent comprehensive longitudinal clinical evaluations yearly for 6.9 years before death on average. We tested whether an unsupervised clustering algorithm could detect coherent groups of TDP-43 immunopositive cases based on age at death and extensive neuropathologic data. Although many of the brains had mixed pathologies, four discernible clusters were identified. Key differentiating features were age at death and the severity of comorbid Alzheimer’s disease neuropathologic changes (ADNC), particularly neuritic amyloid plaque densities. Cluster 1 contained mostly cases with a pathologic diagnosis of frontotemporal lobar degeneration (FTLD-TDP), consistent with enrichment of frontotemporal dementia clinical phenotypes including appetite/eating problems, disinhibition and primary progressive aphasia (PPA). Cluster 2 consisted of elderly limbic-predominant age-related TDP-43 encephalopathy (LATE-NC) subjects without severe neuritic amyloid plaques. Subjects in Cluster 2 had a relatively slow cognitive decline. Subjects in both Clusters 3 and 4 had severe ADNC + LATE-NC; however, Cluster 4 was distinguished by earlier disease onset, swifter disease course, more Lewy body pathology, less neocortical TDP-43 proteinopathy, and a suggestive trend in a subgroup analysis (
n
= 114) for increased
C9orf72
risk SNP rs3849942 T allele (Fisher’s exact test
p
value = 0.095). Overall, clusters enriched with neocortical TDP-43 proteinopathy (Clusters 1 and 2) tended to have lower levels of neuritic amyloid plaques, and those dying older (Clusters 2 and 3) had far less PPA or disinhibition, but more apathy. Indeed, 98% of subjects dying past age 85 years lacked clinical features of the frontotemporal dementia syndrome. Our study revealed discernible subtypes of LATE-NC and underscored the importance of age of death for differentiating FTLD-TDP and LATE-NC.
The objective of the study was to examine variability across multiple prospective cohort studies in level and rate of cognitive decline by race/ethnicity and years of education. We compare data ...across studies, we harmonized estimates of common latent factors representing overall or general cognitive performance, memory, and executive function derived from the: (a) Washington Heights, Hamilton Heights, Inwood Columbia Aging Project (N = 4,115), (b) Spanish and English Neuropsychological Assessment Scales (N = 525), (c) Duke Memory, Health, and Aging study (N = 578), and (d) Neurocognitive Outcomes of Depression in the Elderly (N = 585). We modeled cognitive change over age for cognitive outcomes by race, education, and study. We adjusted models for sex, dementia status, and study-specific characteristics. The results found that for baseline levels of overall cognitive performance, memory, and executive function, differences in race and education tended to be larger than between-study differences and consistent across studies. This pattern did not hold for rate of cognitive decline: effects of education and race/ethnicity on cognitive change were not consistently observed across studies, and when present were small, with racial/ethnic minorities and those with lower education declining at faster rates. In this diverse set of datasets, non-Hispanic Whites and those with higher education had substantially higher baseline cognitive test scores. However, differences in the rate of cognitive decline by race/ethnicity and education did not follow this pattern. This study suggests that baseline test scores and longitudinal change have different determinants, and future studies to examine similarities and differences of causes of cognitive decline in racially/ethnically and educationally diverse older groups is needed.
Alzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology ...of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations.
Building on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal CN controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio OR 95% confidence interval = 1.21 1.08-1.37) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 1.01-1.23) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 1.01-1.15) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale ADAS11 over time p = 0.03, β ± standard error = 0.7 ± 0.3; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time p = 0.02, β ± standard error = -0.2 ± 0.06). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes.
We provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
