Alzheimer's Disease Endophenotypes Research Articles

Association of ten VEGF family genes with Alzheimer's disease endophenotypes at single cell resolution.

Using a single-nucleus transcriptome derived from the dorsolateral prefrontal cortex of 424 Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP) participants, we investigated the cell type-specific effect of ten vascular endothelial growth factor (VEGF) genes on Alzheimer's disease (AD) endophenotypes. Negative binomial mixed models were used for differential gene expression and association analysis with AD endophenotypes. VEGF-associated intercellular communication was also profiled. Higher microglia FLT1, endothelial FLT4, and oligodendrocyte VEGFB are associated with greater amyloid beta (Aβ) load, whereas higher VEGFB expression in inhibitory neurons is associated with lower Aβ load. Higher astrocyte NRP1 is associated with lower tau density. Higher microglia and endothelial FLT1 are associated with worse cognition performance. Endothelial and microglial FLT1 expression was upregulated in clinical AD patients compared to cognitively normal controls. Finally, AD cells showed a significant reduction in VEGF signaling compared to controls. Our results highlight key changes in VEGF receptor expression in endothelial and microglial cells during AD, and the potential protective role of VEGFB in neurons. The prefrontal cortical expression of FLT1 and FLT4 was associated with worse cross-sectional global cognitive function, longitudinal cognitive trajectories, and more Alzheimer's disease (AD) neuropathology. The associations between FLT1 or FLT4 and AD endophenotypes appear to be driven by endothelial and microglial cells. VEGFB expression seems to have opposing effects on the Aβ burden in AD depending on cell types, highlighting its potential protective role in neurons.

Genetic insights into the association between inflammatory bowel disease and Alzheimer's disease.

Myeloid cells, including monocytes, macrophages, microglia, dendritic cells and neutrophils are a part of innate immune system, playing a major role in orchestrating innate and adaptive immune responses. Both Alzheimer's disease (AD) and inflammatory bowel disease (IBD) susceptibility loci are enriched for genes expressed in myeloid cells, but it is not clear whether these myeloid risk factors are shared between the two diseases. Leveraging results of genome-wide association studies, we investigated the causal effect of IBD (including ulcerative colitis (UC) and Crohn's disease (CD)) variants on AD and its endophenotypes. Microglia and monocyte expression Quantitative Trait Locus (eQTLs) were used to examine the functional consequences of IBD and AD variants. Our results revealed distinct sets of genes and pathways of AD and IBD susceptibility loci. Specifically, AD loci are enriched for microglial eQTLs, while IBD loci are enriched for monocyte eQTLs. However, we also found that genetically determined IBD is associated with a protective effect against AD (p<0.03). Yet, a genetic propensity for the CD subtype is associated with increased amyloid accumulation (beta=7.14, p-value=0.02) and susceptibility to AD. Susceptibility to UC was associated with increased deposition of TDP-43 (beta=7.58, p-value=6.11×10-4). The relation of these gastrointestinal inflammatory disease to AD is therefore complex; while the different subsets of susceptibility variants preferentially affect different myeloid cell subtypes, there do appear to be certain shared pathways and the possible protective effect of IBD susceptibility on the risk of AD which may provide therapeutic insights.

Proteomic analyses reveal plasma EFEMP1 and CXCL12 as biomarkers and determinants of neurodegeneration.

Plasma proteomic analyses of unique brain atrophy patterns may illuminate peripheral drivers of neurodegeneration and identify novel biomarkers for predicting clinically relevant outcomes. We identified proteomic signatures associated with machine learning-derived aging- and Alzheimer's disease (AD) -related brain atrophy patterns in the Baltimore Longitudinal Study of Aging (n=815). Using data from five cohorts, we examined whether candidate proteins were associated with AD endophenotypes and long-term dementia risk. Plasma proteins associated with distinct patterns of age- and AD-related atrophy were also associated with plasma/cerebrospinal fluid (CSF) AD biomarkers, cognition, AD risk, as well as mid-life (20-year) and late-life (8-year) dementia risk. EFEMP1 and CXCL12 showed the most consistent associations across cohorts and were mechanistically implicated as determinants of brain structure using genetic methods, including Mendelian randomization. Our findings reveal plasma proteomic signatures of unique aging- and AD-related brain atrophy patterns and implicate EFEMP1 and CXCL12 as important molecular drivers of neurodegeneration. Plasma proteomic signatures are associated with unique patterns of brain atrophy. Brain atrophy-related proteins predict clinically relevant outcomes across cohorts. Genetic variation underlying plasma EFEMP1 and CXCL12 influences brain structure. EFEMP1 and CXCL12 may be important molecular drivers of neurodegeneration.

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes.

Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility. We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction. ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS. We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.

Deep causal feature extraction and inference with neuroimaging genetic data.

Alzheimer's disease (AD) is a severe public health issue in the world. Magnetic Resonance Imaging (MRI) offers a way to study brain differences between AD patients and healthy individuals through feature extraction and comparison. However, in most previous works, the extracted features were not aimed to be causal, hindering biological understanding and interpretation. In order to extract causal features, we propose using instrumental variable (IV) regression with genetic variants as IVs. Specifically, we propose Deep Feature Extraction via Instrumental Variable Regression (DeepFEIVR), which uses a nonlinear neural network to extract causal features from three-dimensional neuroimages to predict an outcome (eg, AD status in our application) while maintaining a linear relationship between the extracted features and IVs. DeepFEIVR not only can handle high dimensional individual-level data for model building, but also is applicable to GWAS summary data to test associations of the extracted features with the outcome in subsequent analysis. In addition, we propose an extension of DeepFEIVR, called DeepFEIVR-CA, for covariate adjustment (CA). We apply DeepFEIVR and DeepFEIVR-CA to the Alzheimer's Disease Neuroimaging Initiative (ADNI) individual-level data as training data for model building, then apply to the UK Biobank neuroimaging and the International Genomics of Alzheimer's Project (IGAP) AD GWAS summary data, showcasing how the extracted causal features are related to AD and various brain endophenotypes.

Improving statistical modeling with a neuropathology‐based APOE genetic risk score

AbstractBackgroundThe apolipoprotein E gene (APOE) is the predominant genetic risk factor for late‐onset Alzheimer disease (AD), with three alleles contributing to disease risk and strongly associated with many AD endophenotypes: ε2 (reduced risk), ε3 (reference), and ε4 (increased risk). Researchers often include APOE ε4 carrier status (ε4+/‐) in analyses to account for the genetic effect; however, this does not adequately account for the protective effects of APOE ε2 or the heterogeneous effect of different APOE genotypes (ε2ε2, ε2ε3, ε2ε4, ε3ε3, ε3ε4, and ε4ε4). We hypothesized that accounting for the effect of the full APOE genotype would better recapitulate the influence of APOE in statistical analyses than APOE ε4 status.MethodTo generate a weighted risk score for APOE genotype (APOE‐npscore), we log‐transformed the odds ratios from a recent study reporting APOE genetic risk for neuropathology‐confirmed AD. We regressed cerebrospinal fluid (CSF) AD endophenotypes on the APOE‐npscore using data from the Wisconsin Registry for Alzheimer’s Prevention (WRAP: 233 cognitively unimpaired (CU), 3 mild cognitive impairment (MCI‐AD)) and Wisconsin Alzheimer’s Disease Research Center (WADRC: 287 CU, 42 MCI‐AD, 48 dementia‐AD). In preliminary analyses, APOE‐npscores were tested against CSF amyloid‐beta1‐42 (Aβ42) and phosphorylated tau 181 (pTau181) measured using Elecsys® immunoassays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland).ResultAfter adjusting for sex and age at lumbar puncture, the APOE‐npscore was associated with CSF Aβ42 (β = ‐115.9, p = 5.7e‐17) and pTau181 (β = 2.05, p = 4.7e‐8). APOE ε4 carrier status also associated with CSF Aβ42 (β = ‐238.0, p = 1.9e‐13) and pTau181 (β = 4.25, p = 1.1e‐6); however, models using APOE‐npscore explained 2.4% more variation in CSF Aβ42 and 0.8% more variation in CSF pTau181 than APOE ε4 status. These findings were similar in the subset of cognitively unimpaired participants.ConclusionOur preliminary results demonstrate the benefit of using a pseudo‐continuous variable like the neuropathology‐based APOE risk score instead of binary APOE ε4 status. The APOE‐npscore allows researchers to use a continuous measure to account for APOE genetic risk for AD that does not collapse important genotype categories. This increases statistical power, avoids modeling issues that result from small cell sizes, and allows for a more nuanced interpretation of the genetic effect in analyses.

Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology.

Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologiesfor AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

The associations of APP, PSEN1, and PSEN2 genes with Alzheimer's disease: A large case-control study in Chinese population.

The associations of non-pathogenic variants of APP, PSEN1, and PSEN2 with Alzheimer's disease (AD) remain unclear. This study is aimed at determining the role of these variants in AD. Our study recruited 1154 AD patients and 2403 controls. APP, PSEN1, PSEN2, and APOE were sequenced using a targeted panel. Variants were classified into common or rare variants with the minor allele frequencies (MAF) cutoff of 0.01. Common variant (MAF≥0.01)-based association test was performed by PLINK 1.9, and gene-based (MAF <0.01) association analysis was conducted using Sequence Kernel Association Test-Optimal (SKAT-O test). Additionally, using PLINK 1.9, we performed AD endophenotypes association studies. A common variant, PSEN2 rs11405, was suggestively associated with AD risk (p= 1.08 × 10-2 ). The gene-based association analysis revealed that the APP gene exhibited a significant association with AD (p= 1.43 × 10-2 ). In the AD endophenotypes association studies, APP rs459543 was nominally correlated with CSF Aβ42 level (p= 7.91 × 10-3 ). Our study indicated that non-pathogenic variants in PSEN2 and APP may be involved in AD pathogenesis in the Chinese population.

Leveraging large multi-center cohorts of Alzheimer disease endophenotypes to understand the role of Klotho heterozygosity on disease risk.

Two genetic variants in strong linkage disequilibrium (rs9536314 and rs9527025) in the Klotho (KL) gene, encoding a transmembrane protein, implicated in longevity and associated with brain resilience during normal aging, were recently shown to be associated with Alzheimer disease (AD) risk in cognitively normal participants who are APOE ε4 carriers. Specifically, the participants heterozygous for this variant (KL-SVHET+) showed lower risk of developing AD. Furthermore, a neuroprotective effect of KL-VSHET+ has been suggested against amyloid burden for cognitively normal participants, potentially mediated via the regulation of redox pathways. However, inconsistent associations and a smaller sample size of existing studies pose significant hurdles in drawing definitive conclusions. Here, we performed a well-powered association analysis between KL-VSHET+ and five different AD endophenotypes; brain amyloidosis measured by positron emission tomography (PET) scans (n = 5,541) or cerebrospinal fluid Aβ42 levels (CSF; n = 5,093), as well as biomarkers associated with tau pathology: the CSF Tau (n = 5,127), phosphorylated Tau (pTau181; n = 4,778) and inflammation: CSF soluble triggering receptor expressed on myeloid cells 2 (sTREM2; n = 2,123) levels. Our results found nominally significant associations of KL-VSHET+ status with biomarkers for brain amyloidosis (e.g., CSF Aβ positivity; odds ratio [OR] = 0.67 [95% CI, 0.55-0.78], β = 0.72, p = 0.007) and tau pathology (e.g., biomarker positivity for CSF Tau; OR = 0.39 [95% CI, 0.19-0.77], β = -0.94, p = 0.007, and pTau; OR = 0.50 [95% CI, 0.27-0.96], β = -0.68, p = 0.04) in cognitively normal participants, 60-80 years old, who are APOE e4-carriers. Our work supports previous findings, suggesting that the KL-VSHET+ on an APOE ε4 genotype background may modulate Aβ and tau pathology, thereby lowering the intensity of neurodegeneration and incidence of cognitive decline in older controls susceptible to AD.

Variants in the Niemann-pick type C genes are not associated with Alzheimer's disease: a large case-control study in the Chinese population

Despite the similar clinical and pathological features between Niemann-Pick type C (NPC) disease and Alzheimer's disease (AD), few studies have investigated the role of NPC genes in AD. To elucidate the role of NPC genes in AD, we sequenced NPC1 and NPC2 in 1192 AD patients and 2412 controls. Variants were divided into common variants and rare variants according to minor allele frequency (MAF). Common variant (MAF≥0.01) based association analysis was conducted by PLINK 1.9. Gene-based aggregation testing of rare variants was performed by Sequence Kernel Association Test-Optimal (SKAT-O test), respectively. Age at onset (AAO) and mini-mental state examination (MMSE) association studies were also performed with PLINK 1.9. Six common variants were identified and exhibited no association with AD. Gene-based aggregation testing revealed that both NPC1 and NPC2 were not associated with AD risk. Additionally, AAO and MMSE association studies revealed that no common variants were linked with AD endophenotypes. Taken together, our study indicated that NPC1 and NPC2 may not be implicated in AD pathogenesis in the Chinese population.

Depression contributes to Alzheimer's disease through shared genetic risk.

Depression increases the risk for Alzheimer's disease (AD) in many prospective studies and recent evidence has shown a genetic correlation between these two disorders. Yet, the biological mechanisms underlying this association are unclear. To elucidate molecular mechanisms underlying the association between depression and elevated AD risk. This study used results of the largest published genome-wide association study (GWAS) of depression (N=807,553) and AD (N=455,248), respectively, and human brain transcriptomes (N=580) and proteomes (N=469) profiled from postmortem brains from participants of three prospective cohorts of aging and dementia. First, linkage disequilibrium score regression was performed to assess for genetic correlation between depression and AD. Next, Mendelian randomization was used to test for causality. Subsequently, to resolve the genetic signals to specific genes, quantitative trait locus (QTL) analysis was performed on the significant depression GWAS signals using brain transcriptomic and proteomic profiles. Finally, brain transcripts and proteins identified by the QTL analysis were tested for association with AD endophenotypes and diagnosis.Participants underwent annual clinical examinations, cognitive testing, and post-mortem brain pathological evaluation and RNA-sequencing and proteomic analyses using tandem mass tag mass spectrometry. Approximately 15,800 mRNAs and 8,400 high abundance proteins were included in the analyses after quality control. AD endophenotypes, including longitudinal change of cognitive performance, beta-amyloid, neurofibrillary tangles, and AD clinical diagnosis were assessed. This study confirmed the genetic correlation between depression and AD. Mendelian randomization suggested a significant causal role for depression on AD but no evidence for causal role of AD on depression was found. The QTL analysis found that the depression GWAS variants regulated 62 brain transcripts and 45 brain proteins. Among those, 34 transcripts and 8 proteins were associated with rate of cognitive decline over time, AD pathologies, and AD diagnosis in two separate datasets implicating them in the development of AD. Depression appears to have a causal role in AD. The causal relationship between depression and AD is likely driven, at least in part, by the 42 brain transcripts and proteins identified in this study.

Association of mitochondrial DNA copy number with brain MRI and cognitive function in the TOPMed Program

AbstractBackgroundMitochondria are the main energy source for normal neuronal functions. Mitochondrial DNA (mtDNA) copy number (CN), a measure of mtDNA levels in the cell, correlates with cellular energy generating capacity and metabolic status. Previous studies have observed a significant decrease of circulating cell‐free mtDNA content in the cerebrospinal fluid of patients with Alzheimer's disease (AD). However, it is unknown whether mtDNA CN circulating in the blood is related to AD endophenotypes. We aimed to investigate the cross‐sectional association of mtDNA CN with MRI markers of abnormal brain aging and cognitive function.MethodWe included dementia‐free, multiethnic participants from seven population‐based cohorts with whole‐genome sequencing as part of the Trans‐Omics for Precision Medicine (TOPMed) program. The average mtDNA CN in whole blood was estimated as twice the ratio of the average coverage of mtDNA to the average coverage of the nuclear DNA using fastMitoCalc from mitoAnalyzer. Brain MRI markers included total brain volume, hippocampal volume, and white matter hyperintensities. General cognitive function was derived from at least three distinct cognitive domains using principal component analysis. We related mtDNA CN to AD endophenotypes assessed within 5 years of blood draw per cohort and further performed random‐effects or sample size‐weighted meta‐analyses. Models were adjusted for demographics and vascular risk factors.ResultHigher mtDNA CN was significantly associated with better general cognitive function (P‐values&lt;0.05) in four cohorts after adjusting for age, sex, batch effect, self‐reported race/ethnicity, the time between blood draw and MRI/Cognitive evaluation, cohort‐specific variables, and education (Figure 1). Meta‐analysis across all cohorts confirmed and strengthened the significant association between mtDNA CN and general cognitive function (n=11,021, Beta=0.046, SE=0.01, P‐value=0.0002). Additional adjustment for diabetes, hypertension, hyperlipidemia, and obesity led to similar results (Beta=0.043, SE=0.01, P‐value=0.002). We observed no significant associations between mtDNA CN and brain MRI markers.ConclusionThis study suggests that higher mtDNA CN is cross‐sectionally associated with better general cognitive function in a large sample from diverse communities across the US, providing novel findings that support the role of mtDNA in healthy brain aging. Additional analyses are underway to relate mtDNA CN to AD endophenotypes prospectively and to incident dementia.

APOE*4-stratified genome-wide association study of Alzheimer's disease in over 350,000 individuals.

APOE*4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD) and is highly pleiotropic, such that it may be considered as a biological factor that can affect overall genetic risk for AD. To advance our understanding of the genetic architecture of AD, we sought to perform the largest APOE*4-stratified genome-wide association study (GWAS) of AD. Twenty-five publicly available AD GWAS datasets provided case-control diagnoses for phase-1 samples (imputed to the HRC r1.1 reference panel). The UK Biobank provided subjects with family history of AD status, transformed into an AD phenotype as described previously (Jansen et al., 2019) for phase-2 samples. Linear mixed model regressions were performed on case-control status (LMM-BOLT v.2.3.4), adjusting for age (age-at-onset in cases; age-at-last-exam in controls), sex, APOE*4 and APOE*2 dosage, the first 12 genetic principal components, array/batch, cohort in phase-1, and assessment center in phase-2. In phase-3, phase-1 and phase-2 findings were combined using multivariate genome-wide meta-analysis (Jansen et al., 2019). APOE*4+ heterogeneity tests were evaluated per phase and meta-analyzed in phase-3. Participant demographics are in Table 1. Combining results from both APOE*4-stratified analyses, 106 lead variants across 98 loci passed suggestive significance (p<10-5 ; Figure 1). Although most variants reached only suggestive significance, 28 loci were previously reported at genome-wide significance in large-scale GWAS of AD (Kunkle et al., 2019, Jansen et al., 2019, Bellenguez et al., 2020), supporting that we identified potentially relevant AD loci. APOE*4-stratified effects were observed for 28 variants/loci covered across both phase-1 and phase-2 (NAPOE4+ =19; NAPOE4- =9; Table 2), and 25 variants/loci seen only in phase-2 (NAPOE4+ =17; NAPOE4- =8; Table 3). Notably, a genome-wide significant APOE*4+ heterogeneity effect was observed for the USP17L13 locus (a regulator of deubiquitination), while PPP1R12A, BRINP1, PCBD1, and SESN2 loci passed suggestive significance. Our findings revealed novel AD risk loci/genes and characterized which of these associated with AD risk differentially across APOE*4 status. This contributes highly to personalized genetic medicine and paves the way towards new potential AD drug targets. Ongoing work is adding samples for phase-1 analyses (imputing data to TOPMed) and pursuing both multi-omics and AD endophenotype validation efforts for variant prioritization.

The role of vascular dementia associated genes in patients with Alzheimer's disease: A large case-control study in the Chinese population.

AimThe role of vascular dementia (VaD)‐associated genes in Alzheimer's disease (AD) remains elusive despite similar clinical and pathological features. We aimed to explore the relationship between these genes and AD in the Chinese population.MethodsEight VaD‐associated genes were screened by a targeted sequencing panel in a sample of 3604 individuals comprising 1192 AD patients and 2412 cognitively normal controls. Variants were categorized into common variants and rare variants according to minor allele frequency (MAF). Common variant (MAF ≥ 0.01)‐based association analysis was conducted by PLINK 1.9. Rare variant (MAF < 0.01) association study and gene‐based aggregation testing of rare variants were performed by PLINK 1.9 and Sequence Kernel Association Test‐Optimal (SKAT‐O test), respectively. Age at onset (AAO) and Mini‐Mental State Examination (MMSE) association studies were performed with PLINK 1.9. Analyses were adjusted for age, gender, and APOE ε4 status.ResultsFour common COL4A1 variants, including rs874203, rs874204, rs16975492, and rs1373744, exhibited suggestive associations with AD. Five rare variants, NOTCH3 rs201436750, COL4A1 rs747972545, COL4A1 rs201481886, CST3 rs765692764, and CST3 rs140837441, showed nominal association with AD risk. Gene‐based aggregation testing revealed that HTRA1 was nominally associated with AD. In the AAO and MMSE association studies, variants in GSN, ITM2B, and COL4A1 reached suggestive significance.ConclusionCommon variants in COL4A1 and rare variants in HTRA1, NOTCH3, COL4A1, and CST3 may be implicated in AD pathogenesis. Besides, GSN, ITM2B, and COL4A1 are probably involved in the development of AD endophenotypes.

Sex-driven modifiers of Alzheimer risk: A multimodality brain imaging study.

To investigate sex differences in late-onset Alzheimer disease (AD) risks by means of multimodality brain biomarkers (β-amyloid load via 11C-Pittsburgh compound B [PiB] PET, neurodegeneration via 18F-fluorodeoxyglucose [FDG] PET and structural MRI). We examined 121 cognitively normal participants (85 women and 36 men) 40 to 65 years of age with clinical, laboratory, neuropsychological, lifestyle, MRI, FDG- and PiB-PET examinations. Several clinical (e.g., age, education, APOE status, family history), medical (e.g., depression, diabetes mellitus, hyperlipidemia), hormonal (e.g., thyroid disease, menopause), and lifestyle AD risk factors (e.g., smoking, diet, exercise, intellectual activity) were assessed. Statistical parametric mapping and least absolute shrinkage and selection operator regressions were used to compare AD biomarkers between men and women and to identify the risk factors associated with sex-related differences. Groups were comparable on clinical and cognitive measures. After adjustment for each modality-specific confounders, the female group showed higher PiB β-amyloid deposition, lower FDG glucose metabolism, and lower MRI gray and white matter volumes compared to the male group (p < 0.05, family-wise error corrected for multiple comparisons). The male group did not show biomarker abnormalities compared to the female group. Results were independent of age and remained significant with the use of age-matched groups. Second to female sex, menopausal status was the predictor most consistently and strongly associated with the observed brain biomarker differences, followed by hormone therapy, hysterectomy status, and thyroid disease. Hormonal risk factors, in particular menopause, predict AD endophenotype in middle-aged women. These findings suggest that the window of opportunity for AD preventive interventions in women is early in the endocrine aging process.

The mitochondrial hypothesis: Dysfunction, bioenergetic defects, and the metabolic link to Alzheimer's disease.

Alzheimer's disease (AD) features mitochondrial dysfunction and altered metabolism. Other pathologies could drive these changes, or alternatively these changes could drive other pathologies. In considering this question, it is worth noting that perturbed AD patient mitochondrial and metabolism dysfunction extend beyond the brain and to some extent define a systemic phenotype. It is difficult to attribute this systemic phenotype to brain beta-amyloid or tau proteins. Conversely, mitochondria increasingly appear to play a critical role in cell proteostasis, which suggests that mitochondrial dysfunction may promote protein aggregation. Mitochondrial and metabolism-related characteristics also define AD endophenotypes in cognitively normal middle-aged individuals, which suggests that mitochondrial and metabolism-related AD characteristics precede clinical decline. Genetic analyses increasingly implicate mitochondria and metabolism-relevant genes in AD risk. Collectively these factors suggest that mitochondria are more relevant to the causes of AD than its consequences, and support the view that a mitochondrial cascade features prominently in AD. This chapter reviews the case for mitochondrial and metabolism dysfunction in AD and the challenges of proving that a primary mitochondrial cascade is pertinent to the disease.

Sex differences in the genetic predictors of Alzheimer's pathology.

Autopsy measures of Alzheimer's disease neuropathology have been leveraged as endophenotypes in previous genome-wide association studies (GWAS). However, despite evidence of sex differences in Alzheimer's disease risk, sex-stratified models have not been incorporated into previous GWAS analyses. We looked for sex-specific genetic associations with Alzheimer's disease endophenotypes from six brain bank data repositories. The pooled dataset included 2701 males and 3275 females, the majority of whom were diagnosed with Alzheimer's disease at autopsy (70%). Sex-stratified GWAS were performed within each dataset and then meta-analysed. Loci that reached genome-wide significance (P < 5 × 10-8) in stratified models were further assessed for sex interactions. Additional analyses were performed in independent datasets leveraging cognitive, neuroimaging and CSF endophenotypes, along with age-at-onset data. Outside of the APOE region, one locus on chromosome 7 (rs34331204) showed a sex-specific association with neurofibrillary tangles among males (P = 2.5 × 10-8) but not females (P = 0.85, sex-interaction P = 2.9 × 10-4). In follow-up analyses, rs34331204 was also associated with hippocampal volume, executive function, and age-at-onset only among males. These results implicate a novel locus that confers male-specific protection from tau pathology and highlight the value of assessing genetic associations in a sex-specific manner.

Increased Alzheimer's risk during the menopause transition: A 3-year longitudinal brain imaging study.

Two thirds of all persons with late-onset Alzheimer’s disease (AD) are women. Identification of sex-based molecular mechanisms underpinning the female-based prevalence of AD would advance development of therapeutic targets during the prodromal AD phase when prevention or delay in progression is most likely to be effective. This 3-year brain imaging study examines the impact of the menopausal transition on Alzheimer’s disease (AD) biomarker changes [brain β-amyloid load via 11C-PiB PET, and neurodegeneration via 18F-FDG PET and structural MRI] and cognitive performance in midlife. Fifty-nine 40–60 year-old cognitively normal participants with clinical, neuropsychological, and brain imaging exams at least 2 years apart were examined. These included 41 women [15 premenopausal controls (PRE), 14 perimenopausal (PERI), and 12 postmenopausal women (MENO)] and 18 men. We used targeted minimum loss-based estimation to evaluate AD biomarker and cognitive changes. Older age was associated with baseline Aβ and neurodegeneration markers, but not with rates of change in these biomarkers. APOE4 status influenced change in Aβ load, but not neurodegenerative changes. Longitudinally, MENO and PERI groups showed declines in estrogen-dependent memory tests as compared to men (p < .04). Adjusting for age, APOE4 status, and vascular risk confounds, the MENO and PERI groups exhibited higher rates of CMRglc decline as compared to males (p ≤ .015). The MENO group exhibited the highest rate of hippocampal volume loss (p’s ≤ .001), and higher rates of Aβ deposition than males (p < .01). CMRglc decline exceeded Aβ and atrophy changes in all female groups vs. men. These findings indicate emergence and progression of a female-specific hypometabolic AD-endophenotype during the menopausal transition. These findings suggest that the optimal window of opportunity for therapeutic intervention to prevent or delay progression of AD endophenotype in women is early in the endocrine aging process.

Sex-specific genetic predictors of Alzheimer's disease biomarkers.

Cerebrospinal fluid (CSF) levels of amyloid-β 42 (Aβ42) and tau have been evaluated as endophenotypes in Alzheimer's disease (AD) genetic studies. Although there are sex differences in AD risk, sex differences have not been evaluated in genetic studies of AD endophenotypes. We performed sex-stratified and sex interaction genetic analyses of CSF biomarkers to identify sex-specific associations. Data came from a previous genome-wide association study (GWAS) of CSF Aβ42 and tau (1527 males, 1509 females). We evaluated sex interactions at previous loci, performed sex-stratified GWAS to identify sex-specific associations, and evaluated sex interactions at sex-specific GWAS loci. We then evaluated sex-specific associations between prefrontal cortex (PFC) gene expression at relevant loci and autopsy measures of plaques and tangles using data from the Religious Orders Study and Rush Memory and Aging Project. In Aβ42, we observed sex interactions at one previous and one novel locus: rs316341 within SERPINB1 (p = 0.04) and rs13115400 near LINC00290 (p = 0.002). These loci showed stronger associations among females (β = - 0.03, p = 4.25 × 10-8; β = 0.03, p = 3.97 × 10-8) than males (β = -0.02, p = 0.009; β = 0.01, p = 0.20). Higher levels of expression of SERPINB1, SERPINB6, and SERPINB9 in PFC was associated with higher levels of amyloidosis among females (corrected p values < 0.02) but not males (p > 0.38). In total tau, we observed a sex interaction at a previous locus, rs1393060 proximal to GMNC (p = 0.004), driven by a stronger association among females (β = 0.05, p = 4.57 × 10-10) compared to males (β = 0.02, p = 0.03). There was also a sex-specific association between rs1393060 and tangle density at autopsy (pfemale = 0.047; pmale = 0.96), and higher levels of expression of two genes within this locus were associated with lower tangle density among females (OSTN p = 0.006; CLDN16 p = 0.002) but not males (p ≥ 0.32). Results suggest a female-specific role for SERPINB1 in amyloidosis and for OSTN and CLDN16 in tau pathology. Sex-specific genetic analyses may improve understanding of AD's genetic architecture.

Genome-wide association study of Alzheimer's disease endophenotypes at prediagnosis stages

IntroductionGenetic associations for endophenotypes of Alzheimer's disease (AD) in cognitive stages preceding AD have not been thoroughly evaluated. MethodsWe conducted genome-wide association studies for AD-related endophenotypes including hippocampal volume, logical memory scores, and cerebrospinal fluid Aβ42 and total/phosphorylated tau in cognitively normal (CN), mild cognitive impairment, and AD dementia subjects from the Alzheimer's Disease Neuroimaging Initiative study. ResultsIn CN subjects, study-wide significant (P < 8.3 × 10−9) loci were identified for total tau near SRRM4 and C14orf79 and for hippocampal volume near MTUS1. In mild cognitive impairment subjects, study-wide significant association was found with single nucleotide polymorphisms (SNPs) near ZNF804B for logical memory test of delayed recall scores. We found consistent expression patterns of C14orf40 and MTUS1 in carriers with risk alleles of expression SNPs and in brains of AD patients, compared with in the noncarriers and in brains of controls. DiscussionOur findings for AD-related brain changes before AD provide insight about early AD-related biological processes.