Objective
The purpose of this study was to infer causal relationships between 22 previously reported risk factors for Alzheimer's disease (AD) and the “AD phenome”: AD, AD age of onset (AAOS), ...hippocampal volume, cortical surface area and thickness, cerebrospinal fluid (CSF) levels of amyloid‐β (Aβ42), tau, and ptau181, and the neuropathological burden of neuritic plaques, neurofibrillary tangles (NFTs), and vascular brain injury (VBI).
Methods
Polygenic risk scores (PRS) for the 22 risk factors were computed in 26,431 AD cases/controls and the association with AD was evaluated using logistic regression. Two‐sample Mendelian randomization (MR) was used to infer the causal effect of risk factors on the AD phenome.
Results
PRS for increased education and diastolic blood pressure were associated with reduced risk for AD. MR indicated that only education was causally associated with reduced risk of AD, delayed AAOS, and increased cortical surface area and thickness. Total‐ and LDL‐cholesterol levels were causally associated with increased neuritic plaque burden, although the effects were driven by single nucleotide polymorphisms (SNPs) within the APOE locus. Diastolic blood pressure and pulse pressure are causally associated with increased risk of VBI. Furthermore, total cholesterol was associated with decreased hippocampal volume; smoking initiation with decreased cortical thickness; type 2 diabetes with an earlier AAOS; and sleep duration with increased cortical thickness.
Interpretation
Our comprehensive examination of the genetic evidence for the causal relationships between previously reported risk factors in AD using PRS and MR supports a causal role for education, blood pressure, cholesterol levels, smoking, and diabetes with the AD phenome. ANN NEUROL 2021;89:54–65
Alzheimer's disease is a debilitating and highly heritable neurological condition. As such, genetic studies have sought to understand the genetic architecture of Alzheimer's disease since the 1990s, ...with successively larger genome-wide association studies (GWAS) and meta-analyses. These studies started with a small sample size of 1086 individuals in 2007, which was able to identify only the APOE locus. In 2013, the International Genomics of Alzheimer's Project (IGAP) did a meta-analysis of all existing GWAS using data from 74 046 individuals, which stood as the largest Alzheimer's disease GWAS until 2018. This meta-analysis discovered 19 susceptibility loci for Alzheimer's disease in populations of European ancestry.
Three new Alzheimer's disease GWAS published in 2018 and 2019, which used larger sample sizes and proxy phenotypes from biobanks, have substantially increased the number of known susceptibility loci in Alzheimer's disease to 40. The first, an updated GWAS from IGAP, included 94 437 individuals and discovered 24 susceptibility loci. Although IGAP sought to increase sample size by recruiting additional clinical cases and controls, the two other studies used parental family history of Alzheimer's disease to define proxy cases and controls in the UK Biobank for a genome-wide association by proxy, which was meta-analysed with data from GWAS of clinical Alzheimer's disease to attain sample sizes of 388 324 and 534 403 individuals. These two studies identified 27 and 29 susceptibility loci, respectively. However, the three studies were not independent because of the large overlap in their participants, and interpretation can be challenging because different variants and genes were highlighted by each study, even in the same locus. Furthermore, neither the variant with the strongest Alzheimer's disease association nor the nearest gene are necessarily causal. This situation presents difficulties for experimental studies, drug development, and other future research.
The ultimate goal of understanding the genetic architecture of Alzheimer's disease is to characterise novel biological pathways that underly Alzheimer's disease pathogenesis and to identify novel drug targets. GWAS have successfully contributed to the characterisation of the genetic architecture of Alzheimer's disease, with the identification of 40 susceptibility loci; however, this does not equate to the discovery of 40 Alzheimer's disease genes. To identify Alzheimer's disease genes, these loci need to be mapped to variants and genes through functional genomics studies that combine annotation of variants, gene expression, and gene-based or pathway-based analyses. Such studies are ongoing and have validated several genes at Alzheimer's disease loci, but greater sample sizes and cell-type specific data are needed to map all GWAS loci.
Background The risk of atherosclerotic cardiovascular disease (ASCVD) increases sharply with age. Some older individuals, however, remain unaffected despite high predicted risk. These individuals may ...carry cardioprotective genetic variants that contribute to resilience. Our aim was to assess whether asymptomatic older individuals without prevalent ASCVD carry cardioprotective genetic variants that contribute to ASCVD resilience. Methods and Results We performed a genome-wide association study using a 10-year predicted ASCVD risk score as a quantitative trait, calculated only in asymptomatic older individuals aged ≥70 years without prevalent ASCVD. Our discovery genome-wide association study of N=12 031 ASCVD event-free individuals from the ASPREE (Aspirin in Reducing Events in the Elderly) trial identified 2 independent variants, rs9939224 (
<5×10
) and rs56156922 (
<10
), in the
(cholesteryl ester transfer protein) gene. The
gene is a regulator of plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and lipoprotein(a) levels, and it is a therapeutic drug target. The associations were replicated in the UK Biobank (subpopulation of N=13 888 individuals aged ≥69 years without prevalent ASCVD). Carriers of the identified
variants (versus noncarriers) had higher plasma high-density lipoprotein cholesterol levels, lower plasma low-density lipoprotein cholesterol levels, and reduced risk of incident ASCVD events during follow-up. Expression quantitative trait loci analysis predicted the identified
variants reduce
gene expression across various tissues. Previously reported associations between genetic
inhibition and increased risk of age-related macular degeneration were not observed among the 3917 ASPREE trial participants with retinal imaging and genetic data available. Conclusions Common genetic variants in the
gene region are associated with cardiovascular resilience during aging. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01038583.
Alzheimer's disease (AD) is a complex multifactorial neurodegenerative disorder and the most common form of dementia. AD is highly heritable, with heritability estimates of ∼70% from twin studies. ...Progressively larger genome-wide association studies (GWAS) have continued to expand our knowledge of AD/dementia genetic architecture. Until recently these efforts had identified 39 disease susceptibility loci in European ancestry populations.
Two new AD/dementia GWAS have dramatically expanded the sample sizes and the number of disease susceptibility loci. The first increased total sample size to 1,126,563—with an effective sample size of 332,376—by predominantly including new biobank and population-based dementia datasets. The second, expands on an earlier GWAS from the International Genomics of Alzheimer's Project (IGAP) by increasing the number of clinically-defined AD cases/controls in addition to incorporating biobank dementia datasets, resulting in a total sample size to 788,989 and an effective sample size of 382,472. Collectively both GWAS identified 90 independent variants across 75 AD/dementia susceptibility loci, including 42 novel loci. Pathway analyses indicate the susceptibility loci are enriched for genes involved in amyloid plaque and neurofibrillary tangle formation, cholesterol metabolism, endocytosis/phagocytosis, and the innate immune system. Gene prioritization efforts for the novel loci identified 62 candidate causal genes. Many of the candidate genes from known and newly discovered loci play key roles in macrophages and highlight phagocytic clearance of cholesterol-rich brain tissue debris by microglia (efferocytosis) as a core pathogenetic hub and putative therapeutic target for AD.
While GWAS in European ancestry populations have substantially enhanced our understanding of AD genetic architecture, heritability estimates from population based GWAS cohorts are markedly smaller than those from twin studies. While this missing heritability is likely due to a combination of factors, it highlights that our understanding of AD genetic architecture and genetic risk mechanisms remains incomplete. These knowledge gaps result from several underexplored areas in AD research. First, rare variants remain understudied due to methodological issues in identifying them and the cost of generating sufficiently powered whole exome/genome sequencing datasets. Second, sample sizes of non-European ancestry populations in AD GWAS remain small. Third, GWAS of AD neuroimaging and cerebrospinal fluid endophenotypes remains limited due to low compliance and high costs associated with measuring amyloid-β and tau levels and other disease-relevant biomarkers. Studies generating sequencing data, including diverse populations, and incorporating blood-based AD biomarkers are set to substantially improve our knowledge of AD genetic architecture.
INTRODUCTION
Genetic associations with Alzheimer's disease (AD) age at onset (AAO) could reveal genetic variants with therapeutic applications. We present a large Colombian kindred with autosomal ...dominant AD (ADAD) as a unique opportunity to discover AAO genetic associations.
METHODS
A genetic association study was conducted to examine ADAD AAO in 340 individuals with the PSEN1 E280A mutation via TOPMed array imputation. Replication was assessed in two ADAD cohorts, one sporadic early‐onset AD study and four late‐onset AD studies.
RESULTS
13 variants had p<1×10−7 or p<1×10−5 with replication including three independent loci with candidate associations with clusterin including near CLU. Other suggestive associations were identified in or near HS3ST1, HSPG2, ACE, LRP1B, TSPAN10, and TSPAN14.
DISCUSSION
Variants with suggestive associations with AAO were associated with biological processes including clusterin, heparin sulfate, and amyloid processing. The detection of these effects in the presence of a strong mutation for ADAD reinforces their potentially impactful role.
Introduction
Diversity in cognition among apolipoprotein E (APOE) ε4 homozygotes can range from early‐onset Alzheimer's disease (AD) to a lifetime with no symptoms.
Methods
We evaluated a phenotypic ...extreme polygenic risk score (PRS) for AD between cognitively healthy APOE ε4 homozygotes aged ≥75 years (n = 213) and early‐onset APOE ε4 homozygote AD cases aged ≤65 years (n = 223) as an explanation for this diversity.
Results
The PRS for AD was significantly higher in APOE ε4 homozygote AD cases compared to older cognitively healthy APOE ε4/ε4 controls (odds ratio OR 8.39; confidence interval CI 2.0–35.2; P = .003). The difference in the same PRS between APOE ε3/ε3 extremes was not as significant (OR 3.13; CI 0.98–9.92; P = .053) despite similar numbers and power. There was no statistical difference in an educational attainment PRS between these age extreme case‐controls.
Discussion
A PRS for AD contributes to modified cognitive expression of the APOE ε4/ε4 genotype at phenotypic extremes of risk.
Variation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only the hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes ...to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a large, curated reference alignment of complete mtDNA sequences as part of a pipeline for imputing missing mtDNA single nucleotide variants (mtSNVs). We call our reference alignment and pipeline MitoImpute.
We aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1000 Genomes Project and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1000 Genomes samples was 42.7% (Matthew's correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants.
These results show that our reference alignment and panel can be used to impute missing mtSNVs in existing data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
Examining sex differences on the impact of modifiable risk factors in Alzheimer’s disease (AD) risk can help us better understand the mechanisms underlying sex differences in the ...prevalence and incidence of AD. Here, we used polygenic risk scores (PRS) and Mendelian randomization (MR) to investigate sex‐specific effects of sleep duration, insomnia, blood pressure, diabetes, alcohol intake, smoking, body mass index, high cholesterol, and education on AD risk.
Method
We obtained combined and sex‐stratified genome‐wide association study (GWAS) summary statistics for each risk factor from the UK Biobank and used them as the base dataset for constructing PRS and exposure datasets in the MR analysis. Linkage disequilibrium clumping was performed to identify independent genome‐wide significant single nucleotide polymorphisms (SNPs) across the sex‐combined, male‐specific, and female‐specific GWAS. The combined lead SNPs were then weighted by their strata‐specific effect sizes in the stratified PRS and MR analyses. PRS were constructed for each risk factor in participants from the Alzheimer’s Disease Genetics Consortium. Linear regression was used to investigate the association of each PRS with AD risk, adjusting for age, principal components, and cohort. MR was used to estimate sex‐stratified causal effects of each risk factor on AD. Sex differences in PRS associations and MR causal estimates were determined using Fisher’s Z score method.
Results
Association testing of the PRS with AD risk in sex stratified cohorts revealed that the BMI PRS was associated with differential effects in men and women (OR 95%CI: males: 1.05 1.00, 1.10 vs females: 0.96 0.93, 0.99, p = 0.003). Furthermore, the university completion PRS was non‐significant in men but was associated with reduced risk in women (OR 95%CI: males: 0.96 0.92, 1.01 vs females: 0.92 0.89, 0.96, p = 0.12). In the follow‐up MR analysis, university completion was also causally associated with reduced risk in women only (OR 95%CI: males: 1.09 0.77, 1.53 vs females: 0.55 0.42, 0.72, p = 0.002) (Figure 1). No other risk factors showed evidence of sex‐differences.
Conclusion
Our study found sex‐specific effects of genetically predicted BMI and educational attainment on AD risk. These findings suggest the need for sex‐specific approaches to AD prevention and management.
Background
To reduce the population prevalence of Alzheimer’s disease (AD), it is critical to identify risk factors that modify AD risk. Methods of causal inference that exploit genomic information, ...such as genetic correlation (rg), polygenic risk scores (PRS) and Mendelian randomization (MR), can overcome some of the limitations of observational studies such as confounding and reverse causation. Here we use rg, PRS, and MR to investigate causal associations between twenty‐two risk factors and eleven AD outcomes.
Methods
Using GWAS summary statistics, rg was estimated using GNOVA and bidirectional MR causal estimates using LHC‐MR. The exposures included alcohol intake, physical activity, lipid traits, blood pressure traits, diabetes, BMI, depression, insomnia, social isolation, smoking, diet, and education. The outcomes included AD, AD age of onset, hippocampal volume, CSF Aβ42, tau, and Ptau181 levels, and amyloid, tau, cerebrovascular neuropathology. PRS for the exposures were constructed using PRSice in ADGC (n = 25,431), ADNI (nmax = 1,718), and ROSMAP (nmax = 1,675), and their association with AD diagnosis, CSF biomarkers, PET imaging, MRI imaging, and neuropathology was evaluated.
Results
After accounting for multiple testing, 71, 1, and 38 trait pairs were significant in the rg, PRS, MR models respectively. The only significant trait pair identified across all three methods was a protective effect of higher educational attainment on AD (rg = ‐0.161, p = 3.78e‐14; bPRS se = ‐0.07 0.014, p = 8.88e‐7; bMR se = ‐0.21 0.042, p = 2.43e‐7). Seventeen trait pairs had both significant genetic correlations and causal MR estimates. In particular, increased cortical surface area was positively correlated with higher educational attainment (rg = 0.261, p = 1.46e‐18), with MR indicating that genetically predicted cortical surface area was causally associated with higher education (bMR se = 0.27 0.042, p = 3.21e‐10), but not vice versa (bMR se = ‐0.09 0.072, p = 0.224).
Conclusions
We evaluated causal relationships between risk factors and AD endophenotypes using genomic information. The protective effect of education on AD is supported by genetic correlation, PRS and MR, potentially due to increased cognitive resilience resulting from increased cortical surface area.
Background
There is a need to better understand the role of modifiable risk factors in the development of racial/ethnic health disparities in Alzheimer’s disease (AD). In particular, research is ...lacking on how clinical risk scores may interact with genetic liability for dementia in diverse populations. Here, we examined the influence of the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score (CAIDE) and APOE genotype on MCI/Dementia risk in non‐Latinx White (NLW), Black, and Latinx populations.
Method
Participants were from the National Alzheimer’s Coordinating Center Uniform Dataset who self‐reported as NLW (n = 15,296), Black (n = 2,136), or Latinx (n = 955) who were either cognitively normal or had a clinical diagnosis of MCI/Dementia at baseline (Table 1). CAIDE is comprised of age, gender, years of education, hypertension, obesity, and hypercholesteremia with scores ranging from 0‐14. Logistic regression models stratified by race/ethnicity were used to examine the association between CAIDE, APOE genotype, or their combination (9 categories combining favorable, intermediate, and unfavorable CAIDE scores with APOE e3/e3, e2+, and e4+) on MCI/dementia (Fig. 1‐2). Population differences were determined using Fisher’s z‐score method.
Results
APOE e2+ was associated with reduced odds of MCI/dementia in NLW participants, while APOE e4+ was associated with increased risk in Latinx, Black, and NLW participants. Higher CAIDE scores were associated with increased risk of MCI/dementia in Latinx and NLW but were non‐significant in Black participants. The association of CAIDE on MCI/dementia in Black participants was significantly different from that in NLW and Latinx participants. Similarly, the effect of APOE e4+ on the risk of MCI/dementia was weaker in Latinx compared to NLW participants. In NLW, increasingly unfavorable modifiable risk profiles attenuated the protective effect of APOE e2+ and accentuated the deleterious impact of APOE e4+ on MCI/dementia. In Black participants, modifiable risk factors did not significantly affect the relationship between APOE genotype and MCI/dementia; in Latinx participants, there was only a moderate effect.
Conclusion
The risk associated with APOE on MCI/Dementia is moderated by modifiable risk factors with suggestive population‐specific effects. Addressing health disparities will require risk scores that combine clinical, genetic, and social determinants of health and are applicable across diverse populations.
PDF
