APOE Genotype Research Articles

Generalized Calibrated BOLD fMRI for the Relationship between Cerebral Metabolism and Hypertensive Status

AbstractBackgroundElevated blood pressure levels during mid‐life have been found to be associated with an increased susceptibility to developing dementia later in life, particularly vascular dementia. Quantitative imaging biomarkers, such as Oxygen Extraction Fraction (OEF) and Cerebral Metabolism Rate of Oxygen (CMRO2), can be indicators of impaired cerebral metabolism. Calibrated Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) is a multi‐parametric approach utilizing hyperoxic and hypercapnic gas challenges (Figure 1). The impact of hypertension on OEF and CMRO2 has been investigated.MethodA cohort of 84 participants was recruited from the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core (Table 1). Among all the covariates, participants with prediabetes and diabetes were considered diabetic, and those who exhibited high blood pressure or were using medication to manage hypertension were classified as hypertensive. The MRI was conducted using a 3T Siemens Skyra MRI scanner with a 32‐channel head coil. Dynamic Pseudocontinuous Arterial Spin Labeling (PCASL) was used to acquire cerebral blood flow (CBF) and BOLD images during respiratory challenges with an end‐tidal forcing system. The ROI values in the frontal lobe, temporal lobe, parietal lobe, and occipital lobe regions were chosen. The correlation between hypertensive status and OEF and CMRO2 in the ROI was analyzed with a linear mixed model, with covariates of age, sex, cognitive status, APOE genotype, diabetic status, and hypertensive status.ResultA negative correlation was found between CBF, OEF, and CMRO2 with hypertensive status in frontal lobe region (Figure 2). Statistical significance was observed for OEF and CMRO2 (p = 0.049 and p = 0.028, respectively), indicating the potential influence of hypertensive status on these biomarkers.ConclusionThe study concludes that there is a significant negative association between hypertensive status and both OEF and CMRO2, particularly in the frontal lobe region. The observed reduction in OEF and CMRO2 is not solely due to decreased CBF, but rather complex and multifactorial processes involving vascular remodeling and altered oxygen metabolism. Additional research is necessary to fully understand the underlying pathophysiological mechanisms that link hypertension to decreased OEF and CMRO2, particularly in the context of regional specificity.

CSF ADAM10 levels in AD patients in relationship to ADAM10 gene variants

AbstractBackgroundThe disintegrin metalloproteinase 10 (ADAM10) is the main α‐secretase acting in the non‐amyloidogenic processing of APP. Some ADAM10 gene variants (Q170H, R181G) have been associated with higher susceptibility to develop late‐onset AD and have been shown to promote AD‐type changes in mice models. We tested the hypothesis that some ADAM10 rare variants could increase the risk for AD through conferring an earlier age‐related downregulation of a‐secretase activity.Method ADAM10 gene was sequenced in 103 AD cases (78% with family history) with positive CSF biomarkers, and 96 cognitively preserved nonagenarians. ADAM10 in CSF of the AD cases was analyzed by means of ELISA (total levels) and western blot (segregated by isoforms of 50 kDa, 55 kDa, and 80 kDa) in comparison with controls and non‐AD dementia cases. We examined whether there was an increase of rare gene variants (MAF < 0.01) in the AD group and their potential association with lowers CSF protein levels.ResultRare variants were found in 15,5% of AD cases (in 23% of early‐onset versus 7,8% in late‐onset, p = 0.058) and in 12,5% of nonagenarians, and several of them were exclusive of the group. However, all were intronic variants except the Q170H change found in three AD cases and one nonagenarian. The SNP rs74016945 (3’UTR), with MAF close to 0.01, was found in 6% of the nonagenarians (OR 0.146, Fisher exact test p = 0.057). ELISA ADAM10 levels were not significantly different comparing AD cases with controls, carriers of rare variants versus non‐carriers, and did not differ consistently according to age at onset or APOE genotype. The three ADAM10 species were also similar in AD cases and controls, and did not differ according to genetic variants or age at onset.ConclusionRare ADAM10 exonic variants are uncommon in AD cases and the presence of rare intronic variants (more frequent in early versus late‐onset cases) is not associated with decreased ADAM10 levels in CSF.

Circulating brain‐enriched microRNAs as peripheral biomarkers of neurodegeneration

AbstractBackgroundMinimally invasive diagnostic tools are needed to better characterize heterogeneous groups of patients with mild cognitive impairment (MCI), pre‐MCI, and dementia. At DiamiR, we developed an approach based on targeted selection and quantitative analysis of microRNAs enriched in specific brain regions, present in synapses, and detectable in blood plasma. microRNAs are short, non‐coding regulatory molecules whose levels change in disease.MethodConcentrations of 24 brain‐enriched and inflammation‐associated microRNAs (Table 1) were analyzed in plasma samples of 200 study participants with the following clinical diagnoses at the time of blood draw: 76 cognitively unimpaired (CU), 85 MCI, and 39 Alzheimer’s disease (AD). The demographic characteristics and clinical data of the study participants are summarized in Table 2. The plasma samples were collected at the Penn Alzheimer’s Disease Research Center (ADRC). Based on amyloid status (Abeta+/‐), APOE genotype (APOE4 +/‐), and sex, each sample was assigned to a specific subgroup. RNA from plasma samples was isolated using the MagMAX mirVana kit (ThermoFisher). microRNA concentrations were measured by qPCR using custom plates (Qiagen) pre‐plated with lyophilized miRCURY LNA‐based primers for a 24‐microRNA panel. Differentiation of subgroups by microRNA pairs and their combinations (classifiers) was evaluated using a proprietary software program developed at DiamiR.ResultUsing the ratio between two microRNAs as a biomarker (“pair” approach) reduces variability and enhances specificity and sensitivity. Effective microRNA pairs were combined into classifiers. Data on the differentiation of subgroups using one, two, and three microRNA pairs are presented in Table 3.In line with our prior results, sex‐stratified analysis yielded higher AUC values for females and males as compared to the combined group. Interestingly, microRNAs differ in effective pairs for female and male subgroups. For example, levels of inflammation‐associated miR‐146a were higher in female MCI/AD study participants. However, sex‐stratified groups were relatively small and further assessment is required.ConclusionThese data support the development of assays based on the analysis of circulating brain‐enriched and inflammation‐associated microRNAs for better characterization of MCI/AD patients and understanding of AD‐associated processes. Further, combining these microRNAs with other factors, such as amyloid and APOE, may enhance a biomarker algorithm.

APOE E4 as a moderator for gait speed and executive function

AbstractBackgroundGait speed has been found to be associated with cognitive function (Liu, 2022) with slower walking speed related to poorer cognition (Hoogendijik, 2020). Slower gait speed was found to be associated with poorer global cognitive function, verbal memory and executive function (Watson, 2010). Additionally, APOE E4 carriers with slow gait speed have been found to perform worse on the MMSE than APOE E4 carriers without slow gait and APOE E4 non‐carriers with slow gait (Sakurai, 2017).We aim to evaluate the moderating effects of APOE E4 status on gait speed and cognition in a pre‐dementia community population in Singapore.MethodWe recruited 534 participants from the community who completed a detailed neuropsychological assessment and APOE genotyping. To test for the moderating effects of APOE E4 with gait speed and cognition, we performed a multiple generalized linear model controlling for covariates of age, sex and education.ResultThe cohort included 186 subjects with subjective cognitive decline and 348 mild cognitive impairment subjects from Dementia Research Centre (Singapore). Mean age of the cohort was 62.55, SD = 9.55, mean education years was 13.97, SD = 3.45 and majority were women (57.1%). The presence of slow gait speed among our cohort was 4.7% and there were 12.6% APOE E4 carriers. There were no significant differences in walking gait between APOE E4 carriers and non‐carriers (p = 0.235). APOE E4 moderated the effect of slow gait speed on executive function. APOE E4 non‐carrier interacted with slow gait speed, resulting in worse performance on the trail making task B (β = 71.97, p = 0.003), digit span backwards (β = ‐2.23, p = 0.037), and colour trails 2 (β = 64.01, p<0.001).ConclusionAPOE E4 status moderates the effect of slow gait speed on executive function. APOE E4 non‐carriers with slow gait speed are at risk for poorer executive function.

Differences in metabolomic profiles of APOE4 carrier vs non‐carrier patients undergoing therapeutic plasma exchange with albumin replacement as a treatment for Alzheimer’s disease

AbstractBackgroundApolipoprotein E is the major apolipoprotein found in plasma, involved in lipid transport and metabolism. Carrying the ε4 allele of the APOE gene (ApoE4) is a risk factor for developing Alzheimer’s disease (AD) and is associated with altered plasma lipid levels and lipoprotein particle distribution. The AMBAR phase 2b/3 trial is a therapeutic approach for AD patients (MMSE:18‐26) based on a 14‐month program comprising 18 plasma‐exchange procedures with albumin replacement (PE‐Alb) to remove pathological substances from plasma, slowing AD progression. The aim of this study was to assess PE‐Alb differential effects on metabolites across the AMBAR trial between ApoE4 carriers and non‐carriers.Method442 metabolites were quantified in serum samples of 296 ApoE‐genotyped patients included in the AMBAR trial (225 PE‐Alb‐treated and 71 placebo), at 3 time‐points, using high‐throughput UHPLC‐MS (OWL‐Metabolomics, Spain). Data was stratified by ApoE4 carriers (n = 145) and non‐carriers (n = 151) and analyzed through a mixed model for repeated measures. Differences from placebo were assessed through month*treatment group interaction estimates. Reported p‐values were adjusted by Benjamini‐Hochberg procedure.ResultBaseline differences between ApoE4 carriers and non‐carriers were found according to what has been reported in the literature. In ApoE4 carriers, 29 metabolites significantly changed (Adjusted p‐value<0.05) in PE‐Alb‐treated patients compared to placebo at end of study (month 14). Eleven of them, which were in the free Fatty Acids (FA) class (6 monounsaturated‐FA, 3 polyunsaturated‐FA, 2 saturated‐FA), were down regulated. This would agree with the previously reported finding that free‐FA levels increase in blood from AD patients and participate in the pathogenesis of AD by multiple mechanisms. In Non‐carriers, 19 metabolites showed statistically significant change at month 14, 2 of them being downregulated. In both stratifications, most upregulated metabolites were in the Glycerophospholipid class (21/35) which has been reported to be decreased in AD. All other metabolites were in the Glycerolipids (4), Sphingolipids (4), Sterols (3), Bile acids (2) and Amino Acids (1) classes.ConclusionThese results demonstrate modulation of fatty acid metabolism in PE‐Alb‐treated patients from the AMBAR trial in relation to its ApoE genotype. Furthermore, treatment induced positive metabolite changes compared to placebo. These results deserve further investigation.

Dissociable influences of maternal vs paternal Alzheimer’s risk on neurocognitive and cardiovascular health in men and women

AbstractBackgroundParental history of sporadic Alzheimer’s disease (AD) is considered a prime risk factor since at least the late 1980s. Routinely used clinical samples of at‐risk individuals (8‐16 subjects) may conceal weaker population‐based effects, especially those of paternal inheritance. We performed a phenome‐wide examination of the dissociable influences of maternal vs. paternal AD risk on male vs. female probands in the largest single‐site family‐based at‐risk AD cohort: PREVENT‐AD.MethodWe built sex‐specific PLS‐regression models in which the APOE genotypes (e.g., ɛ3/3, ɛ3/4, ɛ3/2) were estimated based on ∼1,000 patient visits, each covering ∼260 risk indicators, to derive three APOE‐driven intermediate phenotypes (IPs). We examined how much the three IPs vary with regard to sex and maternal vs. paternal AD lineage across the phenome. We assessed the sex‐specific and lineage‐specific variation of the IPs over a 4‐year follow‐up period. Lastly, we examined how matri‐ vs. patrilinear AD risk captured by the IPs were expressed in AD‐vulnerable brain structures.ResultAcross IPs, we linked patrilinear AD risk to verbal‐numerical cognition and cardiovascular health in males. In contrast, we linked matrilinear AD risk to memory performance in both sexes. Over time, the mean difference in cognitive performance decreases with regard to sex but increases with regard to AD lineage. Cis‐ and trans‐generational sex effects in neocortex subregions (e.g., mPFC, PCu) were captured by the first and second IPs, respectively. The third IP mainly captured trans‐generational sex effects in hippocampus subregions (e.g., CA1, CA4).ConclusionWe uncovered IPs of AD susceptibility differently expressed in male and female probands and affected by the diagnosed parent’s sex. Maternal inheritance highlighted memory performance in both sexes, whereas paternal inheritance was particularly linked to cardiovascular health in males. The inheritance of the IPs was reflected in the brain structure at both superficial and deeper layers of the cortex. As the first study of its kind, our cross‐generational analysis of matri‐ vs. patrilinear AD risk bridges the epidemiological and clinical literature by leveraging the power of ∼1,000 patient visits. Our completely data‐driven framework ultimately dissociated phenotypes of maternal and paternal AD risk single‐handedly expressed in male and female probands.

Significance of a positive tau pet scan with a negative amyloid pet scan

AbstractBackgroundThe implications of a positive tau (T) Positron Emission Tomography (PET) with a negative beta amyloid (A) PET are not well understood. We investigated cognitive performance in participants who were positive on tau PET but negative on beta amyloid PET.MethodWe evaluated 98 participants from the Mayo Clinic Study of Aging (MCSA) and the Mayo Clinic Alzheimer’s Disease Research Center (ADRC) who were positive for Flortaucipir (FTP) and negative for PiB PET. Participants were classified as A‐ and T+ based on Standardized Uptake Value Ratios (SUVr) of FTP and PiB PET scans, and were matched 2:1 to amyloid negative and tau negative cognitively unimpaired controls from the MCSA. Cognitive test scores were compared between the combined ADRC/MCSA group and MCSA only group. We also examined clinical diagnoses in our cohort. The most common were Alzheimer’s Disease, mild cognitive impairment (MCI), Dementia with Lewy Bodies (DLB) and Frontotemporal dementia (FTD) amongst others.ResultThere were no significant differences in demographic features or PiB SUVr between groups. There were significant differences in APOE genotype between groups. In the combined ADRC/MCSA group, 25% of A‐T‐ and 13% of A‐T+ were APOE e4 carriers (p = 0.016), and in the MCSA only group, 27% of A‐T‐and 10% of A‐T+ were APOE e4 carriers (p = 0.010). In the combined ADRC/MCSA group, the A‐T+ group demonstrated lower performance than the A‐T‐ group on the Mini Mental Status Exam (MMSE) (p<0.001), Wechsler Memory Scale‐Revised Logical Memory I (p<0.001) and Logical Memory II (p<0.001), Auditory verbal Learning Test Delayed Recall (AVLT) (p = 0.004), Category fluency animals (p = 0.005), Category fluency vegetables (p = 0.021), Trailmaking test A (p<0.001), Trail making test B (p<0.001), Wechsler Adult Intelligence Scale‐IV (WAIS‐IV) (p = 0.002), and Unified Parkinson’s Disease Rating Scale part III (UPDRS III) (p = 0.003). In the MCSA only group, the A‐T+ group had lower scores on Logical Memory II (p = 0.022), AVLT delated recall (p = 0.04), and WAIS‐R block design (p = 0.035) compared to the A‐T‐group.ConclusionPositive tau PET in the absence of beta‐amyloid positivity is associated with lower cognitive performance.

Investigation of neighborhood disadvantage in the context of APOE‐associated amyloid onset age risk

AbstractBackgroundExposome social determinants of health (SDoH), such as neighborhood disadvantage, have shown associations with accelerated cognitive decline, brain volume loss, and postmortem AD pathology. However, associations between neighborhood disadvantage and amyloid biomarker positivity (A+) onset remain understudied. This study uses estimated A+ onset age (EAOA) and the Area Deprivation Index (ADI; an exposome SDoH) to investigate associations between neighborhood disadvantage and A+ risk.MethodsParticipants (n = 599, Table 1) from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) and the Wisconsin Alzheimer’s Disease Research Center (WADRC) with available amyloid PET, address, and APOE genotype were included. EAOA was estimated using sampled iterative local approximation. Neighborhood disadvantage was categorized by national‐rank 2020 ADI (most disadvantaged ≥80th percentile; least disadvantaged <80th percentile). APOE groups were established based on the number of e4 alleles. Cox proportional hazard models assessed A+ risk associated with APOE, ADI, and their interaction. Secondary Cox models used continuous ADI and a lower 70th ADI percentile for neighborhood groups. Kaplan‐Meier curves were generated to depict A‐ probability vs. age for combinations of APOE and ADI groups. A‐ were right censored.ResultsA significant interaction (p = 0.015) between ADI and APOE groups was observed such that APOE‐e4 homozygotes who resided within a highly disadvantaged neighborhood had higher risk of becoming A+, but this group was limited to two participants. Secondary analyses indicated no significant effect of ADI or interaction with APOE on A+ risk (p>0.49). Plots of A+/‐ and EAOA by ADI and APOE group (Figure 1) and Kaplan‐Meier EAOA curves indicated EAOA overlap of ADI groups within APOE strata. A+ risk was significantly higher for APOE‐e4 homozygotes, followed by APOE‐e4 heterozygotes, and then APOE‐e4 non‐carriers.ConclusionsIn this mostly unimpaired, highly educated sample, higher number of APOE‐e4 alleles was associated with higher A+ risk and earlier A+ onset. APOE‐associated A+ risk was similar for all ADI groups, but representation across APOE genotypes for individuals residing within highly disadvantaged neighborhoods was limited. Further work is needed in more diverse samples to investigate the possible influence of ADI and other exposome SDoH factors on AD biomarker timing and trajectories.

Analysis of apoE levels in Alzheimer’s disease patients and control subjects of APOE ε4 variant carriers and non‐carriers

AbstractBackgroundAlzheimer’s disease (AD) is the most common progressive dementia disease in people over 60 years of age. The pathogenesis of AD is thought to be complex and depends on environmental and genetic factors. The most important genetic factors responsible for AD include variants of the APOE gene, which encodes the protein apolipoprotein E (apoE). There are 2 polymorphisms in the APOE, which presence of three alleles: protective ‐ ε2, neutral ‐ ε3, and pathogenic ‐ ε4. On the other hand, the presence of the ε4 allele is associated with an approximately four times higher risk of developing AD in people with a heterozygous system and a twelve times higher risk in ε4/4ε. Disorders of epigenetic mechanisms affecting the concentration of apoE may participate in the development of AD. Disturbed levels of apoE may impair clearance of Aβ from the brain and exacerbate disease progression. It is not known what level of apoE ensures the removal of Aβ and whether genetic and familial predispositions can regulate the efficiency of protective mechanisms. So far, there is little information on the level of apoE in AD patients and controls who are and are not APOE ε4 carriers.The aim was to analyze genetic variants of the APOE gene and apoE protein concentration in AD patients, control subjects related to AD cases (CR), and controls subjects without a family history of AD (CU), carriers and non‐carriers of the APOE ε4 variant.MethodThe studies were conducted on 156 individuals (AD and controls). The APOE genotype was determined by real‐time PCR. The apoE concentration was determined by the ELISA method.ResultThe highest concentration of apoE was found in CR compared to AD and CU (p<0.001). In both APOE ε4 carriers (p<0.05) and non‐carriers (p<0.001), the highest levels of apoE were found in CR. At the same time, in all tested subjects, carriers of APOE ε4, the level of apoE was lower compared to non‐carriers of this pathogenic variant.ConclusionIt seems that the ε4 pathogenic variant of the APOE gene may lead to the development of AD by regulating the level of apoE.

Signatures of abnormal deviations in excitation‐inhibition balance for amyloid positive individuals

AbstractBackgroundDysfunctional excitation‐inhibition balance (EIB) is hypothesized to precede cognitive impairment in Alzheimer’s disease (AD); however, overlapping neuropathology (like amyloid plaques) can develop in cognitively normal (CN) and impaired (CI) individuals. We investigate EIB trajectories for individuals with significant amyloid (Aβ+).MethodMultimodal imaging was used to construct hybrid resting‐state structural connectomes (Fortel, Igor, et al. Network Neuroscience 6.2 (2022): 420‐444.), computing whole‐brain EIB based on 105 ROIs. This cohort (N = 185, 94 Female) aged 55‐90 (μ FEMALES = 74.9, and μ MALES 73) was limited to Aβ+ individuals with APOE genotyping (ε3/ε3, ε3/ε4, ε4/ε4); grouped further by clinical dementia rating (CDR), with CDR > 0 indicating CI. Imaging, Aβ+ classifications, CDR, and APOE were obtained from OASIS‐3: Longitudinal Multimodal Neuroimaging: Principal Investigators: T. Benzinger, D. Marcus, J. Morris; NIH P30 AG066444, P50 AG00561, P30 NS09857781, P01 AG026276, P01 AG003991, R01 AG043434, UL1 TR000448, R01 EB009352. AV‐45 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly.ResultResults presented in Figure 1 suggest whole‐brain EIB in both CN sexes with Aβ+ decreases with increasing age (APOE‐ε4 agnostic). However, sex differences are highlighted with CI; regression analyses produce a marginally significant 4‐way interaction of age, sex, cognitive status, and APOE (P = 0.085, β = ‐0.013). Partial correlation of EIB with age, controlling for sex, APOE and cognitive status is also significant (P = 0.016, r = ‐0.18). Results indicate sex‐mediated EIB differences in individuals with CI, dominated by APOE‐ε4 in women rather than amyloid.ConclusionWe’ve demonstrated EIB deviations in cognitively impaired men and women that may be associated with AD neuropathology. Our findings are consistent with known AD sex differences and suggest novel multimodal connectomics may capture subtle disruptions in brain dynamics that traditional methods may not. Figure. 1. Whole‐brain excitation‐Inhibition balance (EIB) trajectories for amyloid positive (Aβ+) men and women. The cognitively normal (CN) group (rows A‐B) suggests no sex differences in EIB trajectories with age, while the cognitively impaired (CI) group (rows C‐D) begins to reveal distinct patterns of dysfunction (more significantly in women with APOE‐ε4). Note a value of 0.5 indicates perfect balance.

Transition in the cognitive continuum from normal cognition to dementia: the interplay of lifelong cognitive reserve with brain aging and genetic predisposition

AbstractBackgroundHigher cognitive reserve (CR) has been associated with lower risks of cognitive decline and dementia. In this study, we sought to investigate associations of lifelong CR capacity with transitions of cognitive phenotypes in older adults, while accounting for age, sex, APOE genotype, and pathological load of brain aging.MethodThis population‐based Swedish National study on Aging and Care‐Kungsholmen included 2631 participants (age≥60 years, 61.4% female) free of dementia at baseline (2001‐2004); among them 517 had brain MRI. At baseline, lifelong CR capacity was assessed by integrating early‐life education, midlife occupational complexity, later‐life social network and leisure activity. The load of pathological brain aging was assessed using volumes of grey matter (GM), white matter, hippocampus, and white matter hyperintensity, and count of perivascular space and lacunes. Cognitive impairment no dementia (CIND) and dementia were defined at baseline and across up to 15 years until 2016‐2019. Data were analyzed using the Markov multi‐state model.ResultDuring the mean 10.7 years of follow‐up, 9.0% had incident dementia (95%CI: 7.8%–10.3%). Among people free of CIND at baseline (n = 2023), 27.4% had incident CIND during follow‐up (25.3%–29.6%). Higher lifelong CR capacity (mean value of composite CR score = 0.2; range: ‐4.2‐3.6) was associated with a lower risk of direct transitions from non‐dementia (normal or CIND) to dementia (multivariable‐adjusted HR = 0.84; 95% CI 0.73–0.95) and from normal cognition to CIND (0.79; 0.73–0.85), but not with the direct transitions from normal cognition to dementia (0.86; 0.72–1.03), from CIND to dementia (0.93; 0.76–1.14), or from CIND to normal cognition (1.15; 0.98–1.35). Higher lifelong CR capacity was associated with a lower risk of direct transition from normal cognition to dementia in people with APOE‐ε4 and those with high GM volume (2nd‐4th quartiles), but not in those without APOE‐ε4 or with low GM volume (1st quartile) (P‐for‐interaction<0.05). There was no statistical interaction of CR with age, sex, or other brain MRI markers on cognitive transitions.ConclusionHigher lifelong CR capacity may benefit late‐life cognitive status by reducing the risk of cognitive deterioration to dementia, especially in people with genetic predisposition or with low neurodegenerative load.

Performance of Alzheimer’s disease plasma biomarkers in primary care: results from the AgeCoDe study

AbstractBackgroundBlood‐based biomarkers offer a major benefit to Alzheimer’s disease screening because they are less invasive and costly than cerebrospinal fluid or imaging biomarkers, but they have been mainly studied in individuals from memory clinics often exhibiting only mild comorbidities. Therefore, it is necessary to validate plasma biomarkers in more heterogeneous population‐based studies to transfer these results to the general population.MethodPlasma levels of Aβ42/Aβ40, P‐tau181, NfL, and GFAP were measured using Single molecule array (Simoa) technology in samples from 1007 non‐demented participants from the longitudinal population‐based German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe). Participants had a median age of 83 years old and were followed for up to 8 years. We evaluated the association of plasma biomarkers with risk of progression to dementia of the Alzheimer’s type (DAT) and cognitive decline using Cox regressions and linear mixed‐effects models, and their capacity to discriminate between non‐converters and DAT‐converters with logistic regressions.ResultCox regressions adjusted for age and sex in non‐demented participants indicated that higher levels of P‐tau181 (HR = 1.32, p = 2.14×10−5), NfL (HR = 1.15, p = 0.03), and GFAP (HR = 1.33, p = 2.55×10−7), and a lower Aβ42/Aβ40 ratio (HR = 0.83, p = 0.02) were associated with a higher risk of progression to DAT. In addition, higher plasma levels of P‐tau181 (p = 3.05×10−4), NfL (p = 0.04), and GFAP (p = 2.78×10−7) were associated with faster cognitive decline, but no association was found with plasma Aβ42/Aβ40 ratio (p = 0.24). When evaluated separately, plasma biomarkers displayed a rather low AUC at different time points (2, 4, 6, 8 years from baseline; AUC < 0.7) to discriminate between non‐converters and DAT‐converters. However, when combined into a single prediction model, plasma biomarkers substantially improved the discrimination capacity beyond demographics and APOE genotype within a 6‐year period (AUC base model = 0.66, AUC biomarkers model = 0.72, DeLong’s test: p = 0.01).ConclusionPlasma biomarkers are associated with progression to DAT in non‐demented participants. Assessing multiple plasma biomarkers will considerably improve risk assessment for progressing to DAT in primary care.

Re‐calibration and performance of a proteomic prognostic test for 5‐year dementia risk

AbstractBackgroundProteomics‐driven health and wellness tests can provide personalized insight into individual risk for disease that is sensitive to change across time. The SomaSignalTM Mid‐Life Dementia Risk Test is a blood‐based, protein‐only prognostic model developed using SomaScan® Assay v4.0 (measuring ∼5,000 proteins) combined with machine learning methods to predict 20‐year risk for dementia in individuals aged 49 years and older. However, shorter term risk stratification for dementia may better enable early detection of emerging changes in cognition, enrich clinical trial enrollment for novel interventions, and eventually improve precision medicine prescribing of therapeutics. Thus, the 20‐year dementia risk test was re‐calibrated to maximize performance of 5‐year prediction in an older population.MethodThe 25‐protein Mid‐Life Dementia Risk model was re‐calibrated to predict 5‐year risk for a dementia diagnosis in adults aged 65 and older. We utilized plasma samples from ARIC visit 5 (n = 4985; median age 75 years) for the re‐calibration, which included a total of 391 total incident dementia diagnoses occurring within 5 years of blood draw. Re‐calibrated models were assessed in a training dataset consisting of 70% of the ARIC visit 5 data to identify the optimal 5‐year risk model. The final model was tested for robustness in a 15% holdout sample and validated independently in the remaining 15% samples.ResultThe AUC of the re‐calibrated 5‐Year Dementia Risk model was equal to 0.778, 0.735, and 0.776, in training, verification, and validation datasets, respectively. Individuals were stratified by relative risk into Low‐, Medium‐Low‐, Medium‐High‐, and High‐risk bins, with a 5‐year dementia diagnosis rate of 1.510% in the Low‐risk bin vs 20.337% in the High‐risk bin. The performance of the proteomic model was superior to that of APOE genotype or age in predicting 5‐year dementia risk as evaluated by AUC and dynamic range.ConclusionThe 20‐Year Dementia Risk Test was successfully re‐calibrated to predict 5‐year dementia risk in individuals aged 65 years and older with more than a 13‐fold dynamic range for risk stratification. The proteomics‐based 5‐Year Dementia Risk Test outperforms leading risk factors for dementia, including APOE genotype and age.

The role of biofluid markers in predicting near‐term cognitive impairment

AbstractBackgroundAlzheimer’s disease (AD) has been defined as a biological construct that can be determined using in vivo biomarkers. Recent studies confirmed the clinical value of the AT(N) framework when using Aβ and tau positron emission tomography (PET) scans in predicting progression from cognitively unimpaired to MCI. Our study aims to investigate if plasma biomarkers can yield similar predictive performance to PET biomarkers, and to also compare against cerebrospinal fluid (CSF) biomarkersMethodIndividuals from the PREVENT‐AD cohort were included in the study. Participants had Aβ and tau plasma measurements and at least one year of clinical follow‐up thereafter (n = 278). A subset of participants had CSF measurements (n = 102) and/or PET scans (n = 133) also with 1‐year clinical follow‐up. Participants were cognitively unimpaired at the time of all biomarker measurements. MCI diagnoses were made by clinical consensus among expert clinical and research staff blind to plasma, CSF, PET, MRI and APOE genotype. We established thresholds of plasma and CSF Aβ and tau positivity based on >80% specificity in identifying individuals with significant levels of Aβ‐PET (plasma Aβ42/40 = 0.057; plasma pTau181 = 7.53 pg/mL; CSF Aβ42 = 961.37; CSF pTau181 = 66.59 pg/mL). Aβ ([18F]NAV4694) and tau ([18F]AV1451)PET thresholds were defined by the mean plus 2 standard deviations from young participants (Aβ SUVR cut‐off = 1.17; tau SUVR cut‐off = 1.24).Result36.8% (7/19) of the A+T+ plasma group progressed to MCI, 50% (4/8) of the A+T+ CSF group progressed to MCI, and 46.6% (7/15) A+T+ PET group progressed to MCI (Fig. 1).We found differences in MCI progression status between the A+T+ group compared to the A‐T‐ and A+T‐ groups across all biomarkers’ measurements, with the A+T+ group always showing a higher rate of progression than the other two groups (post‐hoc chi‐square analyses; p<0.05).ConclusionAbnormal levels of Aβ and tau plasma biomarkers can help predict near‐ term progression to MCI. When plasma thresholds are derived based on PET data, however, plasma biomarkers have a slightly lower specificity than PET and CSF biomarkers, and both plasma and CSF biomarkers are less sensitive than PET biomarkers.

Longitudinal trajectories of myelin loss in the context of Alzhiemer’s disease biomarkers, glial activation, and APOE4

AbstractBackgroundLower measures of myelin have been associated with abnormal levels of AD biomarkers and APOE4 carriage. However, most human studies have been cross‐sectional, leaving the relationship between AD and myelin changes unclear. The purpose of this study was to determine the association between AD pathology, APOE4, glial activation, and longitudinal changes in quantitative R1 (qR1), a marker sensitive to myelination obtained via MPnRAGE MRI.MethodParticipants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) and Wisconsin Alzheimer’s Disease Research Center (ADRC) were selected based on available longitudinal MPnRAGE, clinical diagnosis, and APOE genotyping (N = 446). A subset (N = 141) included those with available baseline CSF (AB42/40, pTau181), and gliosis markers (sTREM2, GFAP, YKL40) measured using a robust prototype assay as part of the Roche NeuroToolKit research platform (Roche International). Longitudinal mean qR1 was estimated from white matter regions from the ICBM‐DTI‐81 atlas. In the overall sample, linear mixed effects models predicting regional qR1 (FDR‐corrected) with random intercepts and slopes were estimated controlling for sex, age centered within‐subjects (agec), age averaged within‐subjects (agegm), cognitive impairment, and APOE4 carriage as covariates. Two‐way interactions between impairment and APOE4 with agec were tested in the overall sample as were moderating effects of CSF amyloid‐positivity, pTau181, and gliosis markers on agec in the CSF sample.ResultIn the overall sample, older agec, agegm, and female sex were associated with lower qR1 in a majority of tracts indicating substantial longitudinal declines in qR1 over time and lower qR1 with advanced age and female sex. Sex, impairment, and APOE4 did not show significant agec interactions. Likewise, none of the CSF biomarkers moderated the effect of agec in the CSF subsample.ConclusionWhile aging is robustly associated with longitudinal demyelination as potentially indexed by qR1, these rates do not appear to be moderated by AD pathology, cognitive impairment, APOE4, or glial activation in early disease. Given the capacity for re‐myelination in the context of injury, longitudinal studies are critical for parsing myelin and AD relationships. Established associations between myelin and AD risk may reflect later disease processes, particularly in samples more enriched for tau pathology.

Ethnoracial differences in the prevalence of amyloid abnormality

AbstractBackgroundPrevalence estimates of amyloid positivity in persons across the AD clinical spectrum are important to reduce screen failure rates and improve recruitment efficiency in anti‐amyloid trials. We have previously estimated the prevalence according to age, sex, education and APOE genotype. It is however unknown whether these prevalence estimates generalize to diverse ethnoracial groups. We here aim to estimate the prevalence of amyloid abnormality in Black, White and Asian persons without dementia and examine associations with age, sex, educational level and APOE‐e4 carrier status.MethodWe selected 7,419 participants (6,083 with normal cognition; 1,336 with MCI) from 9 Amyloid Biomarker Study cohorts, including 291 Black, 6,310 White and 818 Asian participants. Amyloid positivity was determined with a PET (n = 5,714) or CSF (n = 1,705) biomarker, using data‐driven or study‐specific cutoffs. Generalized estimating equations were used to estimate the age‐related prevalence by ethnoracial group and to evaluate moderation by APOE‐e4 carrier status while adjusting for sex and education.ResultThe mean age was 70.9+‐7.4 years, 3,848 (57%) were women, and 20% were APOE‐e4 carriers. In persons with normal cognition, the age‐related prevalence of amyloid positivity was higher for White (25%) than for Black (17%) and Asian (16%) participants (p = 0.016). Among APOE‐e4 carriers with normal cognition, the prevalence of amyloid abnormality was again higher for White (46%) than for Black (29%) and Asian (30%) participants (Asian vs Black p‐value = 0.046, Asian vs White p‐value<0.001, Black vs White p‐value<0.001). Among APOE‐e4 noncarriers, no differences among the ethnoracial groups were identified (p = 0.56). In persons with MCI, White (59%) and Asian (60%) participants had abnormal amyloid more often than Black participants (43%; p<0.001). Ethnoracial differences were similar for APOE‐e4 carriers and noncarriers with MCI.ConclusionIn persons with normal cognition, the prevalence of amyloid abnormality among APOE‐e4 carriers was ∼15% higher for White than for Black and Asian participants, while among APOE‐e4 noncarriers no ethnoracial differences were found. In persons with MCI, both White and Asian participants ∼15% more often had abnormal amyloid than Black participants, irrespective of APOE‐e4 carrier status. Ethnoracial status may be an important factor to consider in the design of AD clinical trials.

In‐depth evaluation of protein domains improves classification of SORL1 variant pathogenicity in Alzheimer’s Disease patients

AbstractBackgroundRare pathogenic SORL1 gene variants have been identified as strong risk‐increasing factors in Alzheimer’s disease (AD). Recent analysis indicated that SORL1 loss‐of‐function (LoF) variants associated with a ∼40‐fold increased risk for early‐onset AD, while missense variants that were prioritized using in silico variant pathogenicity‐prediction algorithms associated only with a 2‐fold risk increase. However, current risk‐prediction strategies do not take SORL1‐specific features into account. We aimed to design a variant classification strategy that adds in‐depth knowledge of SORLA structural folding and function to the variant risk prediction.MethodWe identified coding SORL1 variants in a discovery/replication sample of whole exome sequencing data from the ADES/ADSP studies comprising 18,959 cases and 21,893 controls after quality control. We selected only the extremely rare variants (MAF<0.05%) and further divided these into LoF(n = 77) and missense variants(n = 539). With an in‐depth evaluation of protein functional domains (informed by pathogenic variants in homologous genes) combined with their predicted pathogenicity (REVEL algorithm) we prioritized missense variants into ‘high priority’, ‘moderate priority’ and ‘low priority’. We compared the age‐dependent penetrance of missense variants for each priority‐category and LoF variants, in context of APOE genotype.ResultCarriers of prioritized missense variants had a similar age‐dependent penetrance as LoF variants, with median age at AD‐onset of ∼65 years which is significantly lower compared to non‐carriers (∼72 years). In addition, carriers of prioritized SORL1 missense variants have an expedited age at onset by ∼7 years independent of their APOE genotype. If we look at a 80% penetrance level, SORL1 carriers with homozygous ε4 background had AD by age 61 (95%CI 60‐NA, n = 6) compared to age 73 (95%CI 72‐73, n = 1091) for SORL1 WT carriers. Carriers with a heterozygous background had AD by age 71 (95%CI 68‐76, n = 62) compared to 78 (95%CI 78‐78, n = 4816) for WT. For a non‐ε4 background the age at onset for carriers was 83 years (95%CI 78‐90, n = 54) compared to 85 years (95%CI 85‐85, n = 5773) for WT. The moderate and low priority group showed no significant difference compared to WT.ConclusionOur prioritization model can successfully identify likely pathogenic missense SORL1 variants, allowing for better identification of patients with possible SORL1‐associated‐AD.

Potential utility of using both APOEε4 and Aβ positivity to enrich clinical trials of tau‐targeting therapies

AbstractBackgroundThe use of enrichment strategies is crucial for selecting individuals with the highest probability of Alzheimer’s disease (AD)‐related progression in typical clinical trial time frames. Although both amyloid‐ß (Aß) pathology and the apolipoprotein E e4 (APOEe4) genotype have been shown to accelerate tau accumulation, it is still not clear whether assessing both APOEe4 genotype and Aß positivity is useful to enrich tau‐targeting trials using tau positron emission tomography (PET) as outcome. Here, we investigated the implications of considering APOEe4 carriership for population enrichment in trials testing drug effects on tau tangle deposition in cognitively impaired (CI) individuals across the AD continuum.MethodWe studied 29 Aß positive CI individuals (16 with mild cognitive impairment [MCI] and 13 with AD dementia) from the McGill Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Study participants underwent clinical assessments, APOE genotyping, magnetic resonance imaging, PET for Aß ([18F]AZD4694) and tau ([18F]MK6240) at baseline, as well as a follow‐up tau‐PET scan (mean follow‐up, 2.2 years). Aß positivity was determined as global [18F]AZD4694 SUVR = 1.55.ResultNo demographic differences were observed between APOEe4 carriers and noncarriers (Table 1). Regression analysis revealed that APOEe4 carriers had higher tau‐PET SUVR increase in temporal regions compared to APOEe4 noncarriers (Figure 1). The use of Aß positivity alone for population enrichment of a clinical trial focusing on CI individuals would require a sample size of 436 individuals per study arm to test a 25% drug effect on tau‐PET accumulation (Figure 2). A similar clinical trial with a population enrichment strategy using Aß positivity plus APOEe4 carriership would require a sample size of as few as 158 individuals per study arm (reduction of 64% in relation to using only Aß positivity) to test the same drug effect (Figure 2).ConclusionOur results reveal that APOEe4 carriership is associated with increased tau tangle accumulation in CI individuals who are Aß positive. Clinical trials testing drug effects on tangle deposition may benefit from assessing both APOEe4 carriership and Aß positivity statuses as enrollment criteria to select individuals at higher risk of fast tau accumulation, resulting in a more cost‐effective trial.

Statin therapy reduces the risk of AD: Clinic to bench translation for protective mechanism

AbstractBackgroundCholesterol dysregulation is a well‐documented factor involved in the pathophysiology of Alzheimer’s Disease (AD). APOE4, which is involved in cholesterol transport, is recognized as the strongest genetic risk factor for late‐onset AD. In a previous study using clinical data, we showed that exposure to statins, a first‐line cholesterol lowering therapeutic, was associated with a reduced risk of developing AD. Another study showed the risk reduction associated with statins was greater in APOE4 carriers. Although the effects of statins in the periphery are well documented, the mechanisms by which statins act in the brain remain poorly understood.MethodThis study aimed to identify potential mechanisms by which statins impact AD pathology at a cellular level and the different response by APOE genotype. Humanized APP/APOE3 and APOE4 mouse neurons and astrocytes were co‐cultured and treated with vehicle or atorvastatin at clinically relevant concentrations. Metabolic flux analysis was used to determine the impact of statins on mitochondrial bioenergetics and dynamics. Multi‐electrode array (MEA) was used to conduct electrophysiological recordings on hippocampal neurons. Lipid droplet burden in astrocytic cells was determined using LipidTOX staining and confocal microscopy. qPCR and Western Blot were used to determine the expression of key proteins involved in cholesterol transport.ResultIn this study, hippocampal neurons treated with atorvastatin in the presence of astrocytic cells induced a significant increase in the number of spikes and spike frequency, as well as the number of bursts and number of spikes within a burst. In contrast, in the absence of astrocytes atorvastatin exposure in neurons did not exhibit a significant difference compared to vehicle. Electrophysiological properties were increased in a dose‐dependent manner and the effect was greater 24‐hours following treatment. Atorvastatin also increased astrocyte mitochondrial respiration whereas it did not in neurons or in neurons co‐cultured with astrocytes.ConclusionOutcomes of these analyses indicated that atorvastatin acts primarily on astrocytes. Specifically, atorvastatin increased mitochondrial respiration in astrocytes and increased synaptic activity on neurons which was astrocyte dependent. These results provide evidence of a neuroprotective role of atorvastatin by regulating lipid metabolism deficits in a cell‐specific manner.Acknowledgments: NIA P01AG026572 and R01AG057931 to RDB.

The role of biofluid markers in predicting near‐term cognitive impairment

AbstractBackgroundAlzheimer’s disease (AD) has been defined as a biological construct that can be determined using in vivo biomarkers. Recent studies confirmed the clinical value of the AT(N) framework when using Aß and tau positron emission tomography (PET) scans in predicting progression from cognitively unimpaired to MCI. Our study aims to investigate if plasma biomarkers can yield similar predictive performance to PET biomarkers, and to also compare against cerebrospinal fluid (CSF) biomarkersMethodIndividuals from the PREVENT‐AD cohort were included in the study. Participants had Aß and tau plasma measurements and at least one year of clinical follow‐up thereafter (n = 278). A subset of participants had CSF measurements (n = 102) and/or PET scans (n = 133) also with 1‐year clinical follow‐up. Participants were cognitively unimpaired at the time of all biomarker measurements. MCI diagnoses were made by clinical consensus among expert clinical and research staff blind to plasma, CSF, PET, MRI and APOE genotype. We established thresholds of plasma and CSF Aß and tau positivity based on >80% specificity in identifying individuals with significant levels of Aß‐PET (plasma Aß42/40 = 0.057; plasma pTau181 = 7.53 pg/mL; CSF Aß42 = 961.37; CSF pTau181 = 66.59 pg/mL). Aß ([18F]NAV4694) and tau ([18F]AV1451)PET thresholds were defined by the mean plus 2 standard deviations from young participants (Aß SUVR cut‐off = 1.17; tau SUVR cut‐off = 1.24).Result36.8% (7/19) of the A+T+ plasma group progressed to MCI, 50% (4/8) of the A+T+ CSF group progressed to MCI, and 46.6% (7/15) A+T+ PET group progressed to MCI (Fig. 1).We found differences in MCI progression status between the A+T+ group compared to the A‐T‐ and A+T‐ groups across all biomarkers’ measurements, with the A+T+ group always showing a higher rate of progression than the other two groups (post‐hoc chi‐square analyses; p<0.05).ConclusionAbnormal levels of Aß and tau plasma biomarkers can help predict near‐ term progression to MCI. When plasma thresholds are derived based on PET data, however, plasma biomarkers have a slightly lower specificity than PET and CSF biomarkers, and both plasma and CSF biomarkers are less sensitive than PET biomarkers.