Mapping medically relevant RNA isoform diversity in the aged human frontal cortex with deep long-read RNA-seq.

Determining whether the RNA isoforms from medically relevant genes have distinct functions could facilitate direct targeting of RNA isoforms for disease treatment. Here, as a step toward this goal for neurological diseases, we sequenced 12 postmortem, aged human frontal cortices (6 Alzheimer disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. We identified 1,917 medically relevant genes expressing multiple isoforms in the frontal cortex where 1,018 had multiple isoforms with different protein-coding sequences. Of these 1,018 genes, 57 are implicated in brain-related diseases including major depression, schizophrenia, Parkinson's disease and Alzheimer disease. Our study also uncovered 53 new RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. We also reported on five mitochondrially encoded, spliced RNA isoforms. We found 99 differentially expressed RNA isoforms between cases with Alzheimer disease and controls.

Test-retest reliability and reliable change index of the Philips IntelliSpace Cognition digital test battery.

OBJECTIVE: This article provides the test-retest reliability and Reliable Change Indices (RCIs) of the Philips IntelliSpace Cognition (ISC) platform, which contains digitized versions of well-established neuropsychological tests. METHOD: 147 participants (ages 19 to 88) completed a digital cognitive test battery on the ISC platform or paper-pencil versions of the same test battery during two separate visits. Intraclass correlation coefficients (ICC) were calculated separately for the ISC and analog test versions to compare reliabilities between administration modalities. RCIs were calculated for the digital tests using the practice-adjusted RCI and standardized regression-based (SRB) method. RESULTS: Test-retest reliabilities for the ISC tests ranged from moderate to excellent and were comparable to the test-retest reliabilities for the paper-pencil tests. Baseline test performance, retest interval, age, and education predicted test performance at visit 2 with baseline test performance being the strongest predictor for all outcome measures. For most outcome measures, both methods for the calculation of RCIs show agreement on whether or not a reliable change was observed. CONCLUSIONS: RCIs for the digital tests enable clinicians to determine whether a measured change between assessments is due to real improvement or decline. Together, this contributes to the growing evidence for the clinical utility of the ISC platform.

Microglial Imaging in Alzheimer's Disease and Its Relationship to Brain Amyloid: A Human 18F-GE180 PET Study.

BACKGROUND: Emerging evidence suggests a potential causal role of neuroinflammation in Alzheimer's disease (AD). Using positron emission tomography (PET) to image overexpressed 18 kDA translocator protein (TSPO) by activated microglia has gained increasing interest. The uptake of 18F-GE180 TSPO PET was observed to co-localize with inflammatory markers and have a two-stage association with amyloid PET in mice. Very few studies evaluated the diagnostic power of 18F-GE180 PET in AD population and its interpretation in human remains controversial about whether it is a marker of microglial activation or merely reflects disrupted blood-brain barrier integrity in humans. OBJECTIVE: The goal of this study was to study human GE180 from the perspective of the previous animal observations. METHODS: With data from twenty-four participants having 18F-GE180 and 18F-AV45 PET scans, we evaluated the group differences of 18F-GE180 uptake between participants with and without cognitive impairment. An association analysis of 18F-GE180 and 18F-AV45 was then conducted to test if the relationship in humans is consistent with the two-stage association in AD mouse model. RESULTS: Elevated 18F-GE180 was observed in participants with cognitive impairment compared to those with normal cognition. No regions showed reduced 18F-GE180 uptake. Consistent with mouse model, a two-stage association between 18F-GE180 and 18F-AV45 was observed. CONCLUSIONS: 18F-GE180 PET imaging showed promising utility in detecting pathological alterations in a symptomatic AD population. Consistent two-stage association between 18F-GE180 and amyloid PET in human and mouse suggested that 18F-GE180 uptake in human might be considerably influenced by microglial activation.

Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer's disease.

INTRODUCTION: There is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer's disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression. METHODS: One hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants. RESULTS: Among the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement. CONCLUSION: Our findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants.

Using deep long-read RNAseq in Alzheimer's disease brain to assess medical relevance of RNA isoform diversity.

Due to alternative splicing, human protein-coding genes average over eight RNA isoforms, resulting in nearly four distinct protein coding sequences per gene. Long-read RNAseq (IsoSeq) enables more accurate quantification of isoforms, shedding light on their specific roles. To assess the medical relevance of measuring RNA isoform expression, we sequenced 12 aged human frontal cortices (6 Alzheimer's disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. Our study uncovered 53 new high-confidence RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. Specific examples include WDR4 (61%; microcephaly), MYL3 (44%; hypertrophic cardiomyopathy), and MTHFS (25%; major depression, schizophrenia, bipolar disorder). Other notable genes with new high-confidence isoforms include CPLX2 (10%; schizophrenia, epilepsy) and MAOB (9%; targeted for Parkinson's disease treatment). We identified 1,917 medically relevant genes expressing multiple isoforms in human frontal cortex, where 1,018 had multiple isoforms with different protein coding sequences, demonstrating the need to better understand how individual isoforms from a single gene body are involved in human health and disease, if at all. Exactly 98 of the 1,917 genes are implicated in brain-related diseases, including Alzheimer's disease genes such as APP (Aß precursor protein; five), MAPT (tau protein; four), and BIN1 (eight). As proof of concept, we also found 99 differentially expressed RNA isoforms between Alzheimer's cases and controls, despite the genes themselves not exhibiting differential expression. Our findings highlight the significant knowledge gaps in RNA isoform diversity and their medical relevance. Deep long-read RNA sequencing will be necessary going forward to fully comprehend the medical relevance of individual isoforms for a "single" gene.

Evaluation of Neighborhood-Level Disadvantage and Cognition in Mexican American and Non-Hispanic White Adults 50 Years and Older in the US.

Importance: Understanding how socioeconomic factors are associated with cognitive aging is important for addressing health disparities in Alzheimer disease. Objective: To examine the association of neighborhood disadvantage with cognition among a multiethnic cohort of older adults. Design, Setting, and Participants: In this cross-sectional study, data were collected between September 1, 2017, and May 31, 2022. Participants were from the Health and Aging Brain Study-Health Disparities, which is a community-based single-center study in the Dallas/Fort Worth area of Texas. A total of 1614 Mexican American and non-Hispanic White adults 50 years and older were included. Exposure: Neighborhood disadvantage for participants' current residence was measured by the validated Area Deprivation Index (ADI); ADI Texas state deciles were converted to quintiles, with quintile 1 representing the least disadvantaged area and quintile 5 the most disadvantaged area. Covariates included age, sex, and educational level. Main Outcomes and Measures: Performance on cognitive tests assessing memory, language, attention, processing speed, and executive functioning; measures included the Spanish-English Verbal Learning Test (SEVLT) Learning and Delayed Recall subscales; Wechsler Memory Scale, third edition (WMS-III) Digit Span Forward, Digit Span Backward, and Logical Memory 1 and 2 subscales; Trail Making Test (TMT) parts A and B; Digit Symbol Substitution Test (DSST); Letter Fluency; and Animal Naming. Raw scores were used for analyses. Associations between neighborhood disadvantage and neuropsychological performance were examined via demographically adjusted linear regression models stratified by ethnic group. Results: Among 1614 older adults (mean [SD] age, 66.3 [8.7] years; 980 women [60.7%]), 853 were Mexican American (mean [SD] age, 63.9 [7.9] years; 566 women [66.4%]), and 761 were non-Hispanic White (mean [SD] age, 69.1 [8.7] years; 414 women [54.4%]). Older Mexican American adults were more likely to reside in the most disadvantaged areas (ADI quintiles 3-5), with 280 individuals (32.8%) living in ADI quintile 5, whereas a large proportion of older non-Hispanic White adults resided in ADI quintile 1 (296 individuals [38.9%]). Mexican American individuals living in more disadvantaged areas had worse performance than those living in ADI quintile 1 on 7 of 11 cognitive tests, including SEVLT Learning (ADI quintile 5: ß = -2.50; 95% CI, -4.46 to -0.54), SEVLT Delayed Recall (eg, ADI quintile 3: ß = -1.11; 95% CI, -1.97 to -0.24), WMS-III Digit Span Forward (eg, ADI quintile 4: ß = -1.14; 95% CI, -1.60 to -0.67), TMT part A (ADI quintile 5: ß = 7.85; 95% CI, 1.28-14.42), TMT part B (eg, ADI quintile 5: ß = 31.5; 95% CI, 12.16-51.35), Letter Fluency (ADI quintile 4: ß = -2.91; 95% CI, -5.39 to -0.43), and DSST (eg, ADI quintile 5: ß = -4.45; 95% CI, -6.77 to -2.14). In contrast, only non-Hispanic White individuals living in ADI quintile 4 had worse performance than those living in ADI quintile 1 on 4 of 11 cognitive tests, including SEVLT Learning (ß = -2.35; 95% CI, -4.40 to -0.30), SEVLT Delayed Recall (ß = -0.95; 95% CI, -1.73 to -0.17), TMT part B (ß = 15.95; 95% CI, 2.47-29.44), and DSST (ß = -3.96; 95% CI, -6.49 to -1.43). Conclusions and Relevance: In this cross-sectional study, aging in a disadvantaged area was associated with worse cognitive functioning, particularly for older Mexican American adults. Future studies examining the implications of exposure to neighborhood disadvantage across the life span will be important for improving cognitive outcomes in diverse populations.

Cognitive and Clinical Characteristics of Patients With Limbic-Predominant Age-Related TDP-43 Encephalopathy.

BACKGROUND AND OBJECTIVES: Limbic-predominant age-related TDP-43 encephalopathy (LATE) affects similar neuroanatomical networks as Alzheimer disease (AD) and is often comorbid with AD, though frequently missed in clinical diagnosis. The primary aim of this study was to elucidate the clinical and cognitive differences at baseline between patients with autopsy-confirmed LATE and patients with AD and comorbid LATE + AD. METHODS: Clinical and neuropathologic datasets were requested from the National Alzheimer Coordination Center. Baseline data from individuals older than 75 years during death without neuropathologic indication of frontotemporal lobar degeneration were included in analyses. Pathologically defined groups reflecting LATE, AD, and comorbid LATE + AD were identified. Group differences in clinical characteristics and cognition were explored through analysis of variance and the χ2 using measures from the Uniform Data Set measures. RESULTS: Pathology groups included 31 individuals with LATE (mean age: 80.6 ± 5.4 years), 393 with AD (mean age: 77.8 ± 6.4 years), and 262 with LATE + AD (mean age: 77.8 ± 6.6 years) without significant differences in sex, education, or race. Compared with participants with AD and LATE + AD pathology, participants with LATE pathology lived significantly longer (mean visits: LATE = 7.3 ± 3.7; AD = 5.8 ± 3.0; and LATE + AD = 5.8 ± 3.0; F(2,683) = 3.7, p < 0.05), reported later onset of cognitive decline (mean onset: LATE = 78.8 ± 5.7; AD = 72.5 ± 7.0; and LATE + AD = 72.9 ± 7.0; F(2,516) = 6.2, p < 0.01), and were more likely to be diagnosed as cognitively normal at baseline (LATE = 41.9%; AD = 25.4%; and LATE + AD = 12%; χ2 = 38.7, p < 0.001). Individuals with LATE (45.2%) also reported fewer memory complaints than those with AD (74.4%) or LATE + AD (66.4%; χ2 = 13.3, p = 0.001) and were less likely to be classified as impaired on the Mini-Mental State Examination (LATE = 6.5%; AD = 24.2%; and LATE + AD = 40.1%; χ2 = 29.20, p < 0.001). Across all neuropsychological measures, participants with LATE + AD pathology performed significantly worse than the AD and LATE groups. DISCUSSION: Those with LATE pathology were older when cognitive symptoms began and lived longer than participants with AD or LATE + AD pathology. Participants with LATE pathology were also more likely to be classified as "cognitively normal" based on objective screening and self-report measures, and they had higher scores on neuropsychological testing. Consistent with prior literature, comorbid pathologies led to more significant cognitive and functional impairment. Early disease characteristics based on clinical presentation alone were insufficient for differentiating LATE from AD, reiterating the need for a validated biomarker.

Neuropsychological test performance of former American football players.

BACKGROUND: Patterns of cognitive impairment in former American football players are uncertain because objective neuropsychological data are lacking. This study characterized the neuropsychological test performance of former college and professional football players. METHODS: One hundred seventy male former football players (n=111 professional, n=59 college; 45-74 years) completed a neuropsychological test battery. Raw scores were converted to T-scores using age, sex, and education-adjusted normative data. A T-score ≤ 35 defined impairment. A domain was impaired if 2+ scores fell in the impaired range except for the language and visuospatial domains due to the limited number of tests. RESULTS: Most football players had subjective cognitive concerns. On testing, rates of impairments were greatest for memory (21.2% two tests impaired), especially for recall of unstructured (44.7%) versus structured verbal stimuli (18.8%); 51.8% had one test impaired. 7.1% evidenced impaired executive functions; however, 20.6% had impaired Trail Making Test B. 12.1% evidenced impairments in the attention, visual scanning, and psychomotor speed domain with frequent impairments on Trail Making Test A (18.8%). Other common impairments were on measures of language (i.e., Multilingual Naming Test [21.2%], Animal Fluency [17.1%]) and working memory (Number Span Backward [14.7%]). Impairments on our tasks of visuospatial functions were infrequent. CONCLUSIONS: In this sample of former football players (most of whom had subjective cognitive concerns), there were diffuse impairments on neuropsychological testing with verbal memory being the most frequently impaired domain.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores.

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Web-Based Protein Interactions Calculator Identifies Likely Proteome Coevolution with Alzheimer's Disease-Associated Proteins.

Protein-protein functional interactions arise from either transitory or permanent biomolecular associations and often lead to the coevolution of the interacting residues. Although mutual information has traditionally been used to identify coevolving residues within the same protein, its application between coevolving proteins remains largely uncharacterized. Therefore, we developed the Protein Interactions Calculator (PIC) to efficiently identify coevolving residues between two protein sequences using mutual information. We verified the algorithm using 2102 known human protein interactions and 233 known bacterial protein interactions, with a respective 1975 and 252 non-interacting protein controls. The average PIC score for known human protein interactions was 4.5 times higher than non-interacting proteins (p = 1.03 × 10-108) and 1.94 times higher in bacteria (p = 1.22 × 10-35). We then used the PIC scores to determine the probability that two proteins interact. Using those probabilities, we paired 37 Alzheimer's disease-associated proteins with 8608 other proteins and determined the likelihood that each pair interacts, which we report through a web interface. The PIC had significantly higher sensitivity and residue-specific resolution not available in other algorithms. Therefore, we propose that the PIC can be used to prioritize potential protein interactions, which can lead to a better understanding of biological processes and additional therapeutic targets belonging to protein interaction groups.

The Ramp Atlas: facilitating tissue and cell-specific ramp sequence analyses through an intuitive web interface.

Ramp sequences occur when the average translational efficiency of codons near the 5' end of highly expressed genes is significantly lower than the rest of the gene sequence, which counterintuitively increases translational efficiency by decreasing downstream ribosomal collisions. Here, we show that the relative codon adaptiveness within different tissues changes the existence of a ramp sequence without altering the underlying genetic code. We present the first comprehensive analysis of tissue and cell type-specific ramp sequences and report 3108 genes with ramp sequences that change between tissues and cell types, which corresponds with increased gene expression within those tissues and cells. The Ramp Atlas (https://ramps.byu.edu/) allows researchers to query precomputed ramp sequences in 18 388 genes across 62 tissues and 66 cell types and calculate tissue-specific ramp sequences from user-uploaded FASTA files through an intuitive web interface. We used The Ramp Atlas to identify seven SARS-CoV-2 genes and seven human SARS-CoV-2 entry factor genes with tissue-specific ramp sequences that may help explain viral proliferation within those tissues. We anticipate that The Ramp Atlas will facilitate personalized and creative tissue-specific ramp sequence analyses for both human and viral genes that will increase our ability to utilize this often-overlooked regulatory region.

Multiple Sclerosis Performance Test (MSPT): Normative study of 428 healthy participants ages 18 to 89.

BACKGROUND: The Multiple Sclerosis Performance Test (MSPT) is a self-administered, iPad®-based, computerized system for quantifying neuroperformance (cognition, upper and lower extremity motor function, and vision) in patients with multiple sclerosis (MS). OBJECTIVE: The goal of the study is to provide regression-based norms for the four MSPT test modules to adjust for the influence of demographic variables (age, education, and sex). METHODS: The MSPT was administered to 428 cognitively intact, healthy adults (ages 18 to 89 years). Participants were recruited to achieve a demographically stratified sample from four geographically diverse United States testing sites. RESULTS: The amount of shared variance in test performance accounted for by demographic variables was 18-23% for an upper extremity motor test, 31% for a walking speed test, 32% for a low contrast visual acuity test, and 48% for a cognitive test. All four test modules were significantly influenced by age (linear and non-linear effects) and education. Additionally, sex influenced performance on the cognitive and walking speed tests. CONCLUSION: This study provides regression-based equations that can enhance the clinical interpretation of MSPT scores by adjusting for the potential influences of age, education, and sex.

Philips IntelliSpace Cognition digital test battery: Equivalence and measurement invariance compared to traditional analog test versions.

Objective: To collect evidence of validity for a selection of digital tests on the Philips IntelliSpace Cognition (ISC) platform.Method: A total of 200 healthy participants (age 50-80) completed both the ISC battery and an analog version of the battery during separate visits. The battery included the following screeners and cognitive tests: Mini-Mental State Examination (2nd edition), Clock Drawing Test, Trail-Making Test (TMT), Rey Auditory Verbal Learning Test (RAVLT), Rey-Osterrieth Complex Figure Test (ROCFT), Letter Fluency, Star Cancellation Test, and Digit Span Test. The ISC tests were administered on an iPad Pro and were automatically scored using designated algorithms. The analog tests were administered in line with existing guidelines and scored by trained neuropsychologists. Criterion validity was established through relative agreement coefficients and raw score equivalence tests. In addition,measurement invariance analysis was used to compare the factor structures of both versions. Finally, we explored effects of demographics and experience with digital devices on performance.Results: We found fair to excellent relative agreement between test versions. Absolute equivalence was found for RAVLT, Letter Fluency, Star Cancellation Test, and Digit Span Test. Importantly, we demonstrated equal loadings of the digital and analog test versions on the same set of underlying cognitive domains. Demographic effects were mostly comparable between modalities, and people's experience with digital devices was found to only influence performance on TMT B.Conclusions: This study provides several sources of evidence for the validity of the ISC test battery, offering an important step in validating ISC for clinical use.Supplemental data for this article is available online at https://doi.org/10.1080/13854046.2021.1974565.

Cognition and disease characteristics in adult onset versus late onset multiple sclerosis.

BACKGROUND: Cognitive impairment is common sequelae of multiple sclerosis (MS); however, relatively little is known about cognitive impairment in late-onset multiple sclerosis (LOMS). OBJECTIVE: To investigate differences in disease characteristics and cognition in LOMS and adult-onset multiple sclerosis (AOMS) patients. METHODS: Archival medical records and neuropsychological evaluations from an MS specialty center were reviewed. Differences in disease characteristics between 53 LOMS and 124 AOMS were compared using chi-square or analysis of variance (ANOVA). To investigate differences in cognitive functioning, age-adjusted standardized scores were compared via analysis of covariance (ANCOVA), using cardiac risk factors and disease duration as covariates. RESULTS: Compared to AOMS, LOMS patients had significantly more cardiac risk factors, shorter disease duration, and shorter time to diagnosis. LOMS patients had similar Expanded Disability Status Scale scores as AOMS patients. LOMS patients demonstrated significantly more impairment on tasks of visual learning and memory, and working memory than AOMS patients. CONCLUSION: Despite a shorter disease duration, LOMS and AOMS patients had similar levels of physical impairment. However, even after accounting for differences in disease duration and cardiac risk, LOMS patients showed a greater burden of cognitive impairment than AOMS patients, suggesting MS diagnosed later in life may progress faster due to the interaction between MS neuropathology and aging.

Story Memory Impairment Rates and Association with Hippocampal Volumes in a Memory Clinic Population.

OBJECTIVE: Story memory tasks are among the most commonly used memory tests; however, research suggests they may be less sensitive to memory decline and have a weaker association with hippocampal volumes than list learning tasks. To examine its utility, we compared story memory to other memory tests on impairment rates and association with hippocampal volumes. METHOD: Archival records from 1617 older adults (Mage = 74.41, range = 65-93) who completed the Wechsler Memory Scale - 4th edition (WMS-IV) Logical Memory (LM), Hopkins Verbal Learning Test - Revised (HVLT-R), and Brief Visuospatial Memory Test - Revised (BVMT-R) as part of a clinical neuropsychological evaluation were reviewed. Scores >1.5 SD below age-adjusted means were considered impaired, and frequency distributions were used to examine impairment rates. A subset of participants (n = 179) had magnetic resonance imaging (MRI) data that underwent image quality assessment. Partial correlations and linear regression analyses, accounting for age, education, and total intracranial volume (TIV), examined associations between memory raw scores and hippocampal volumes. RESULTS: For delayed recall, nearly half of the sample was impaired on HVLT-R (48.8%) and BVMT-R (46.1%), whereas a little more than a third was impaired on LM (35.7%). Better performance on all three measures was related to larger hippocampal volumes (r's =. 26-.43, p's < .001). Individually adding memory scores to regression models predicting hippocampal volumes improved the model fit for all measures. CONCLUSIONS: Despite findings suggesting that story memory is less sensitive to memory dysfunction, it was not differentially associated with hippocampal volumes compared to other memory measures. Results support assessing memory using different formats and modalities in older adults.

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants. METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members. RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD-related phenotypes. Three variants were validated via evidence of co-segregation to additional relatives (PELI3, ABCA7, and SNAP91). DISCUSSION: These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants.

Pairwise Correlation Analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset Reveals Significant Feature Correlation.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer's disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the extent to which this issue might impact large scale analyses using these data. We found that 93.457% of biomarkers, 92.549% of the gene expression values, and 100% of MRI features were strongly correlated with at least one other feature in ADNI based on our Bonferroni corrected α (p-value ≤ 1.40754 × 10-13). We provide a comprehensive mapping of all ADNI biomarkers to highly correlated features within the dataset. Additionally, we show that significant correlation within the ADNI dataset should be resolved before performing bulk data analyses, and we provide recommendations to address these issues. We anticipate that these recommendations and resources will help guide researchers utilizing the ADNI dataset to increase model performance and reduce the cost and complexity of their analyses.

Editorial for the Genetics of Alzheimer's Disease Special Issue: October 2021.

Alzheimer's disease is a complex and multifactorial condition regulated by both genetics and lifestyle, which ultimately results in the accumulation of ß-amyloid (Aß) and tau proteins in the brain, loss of gray matter, and neuronal death [...].

Alzheimer's disease alters oligodendrocytic glycolytic and ketolytic gene expression.

INTRODUCTION: Sporadic Alzheimer's disease (AD) is strongly correlated with impaired brain glucose metabolism, which may affect AD onset and progression. Ketolysis has been suggested as an alternative pathway to fuel the brain. METHODS: RNA-seq profiles of post mortem AD brains were used to determine whether dysfunctional AD brain metabolism can be determined by impairments in glycolytic and ketolytic gene expression. Data were obtained from the Knight Alzheimer's Disease Research Center (62 cases; 13 controls), Mount Sinai Brain Bank (110 cases; 44 controls), and the Mayo Clinic Brain Bank (80 cases; 76 controls), and were normalized to cell type: astrocytes, microglia, neurons, oligodendrocytes. RESULTS: In oligodendrocytes, both glycolytic and ketolytic pathways were significantly impaired in AD brains. Ketolytic gene expression was not significantly altered in neurons, astrocytes, and microglia. DISCUSSION: Oligodendrocytes may contribute to brain hypometabolism observed in AD. These results are suggestive of a potential link between hypometabolism and dysmyelination in disease physiology. Additionally, ketones may be therapeutic in AD due to their ability to fuel neurons despite impaired glycolytic metabolism.