A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease

Evaluating the distinct effects of body mass index at childhood and adulthood on adult major psychiatric disorders

Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Lysosomal TMEM106B interacts with galactosylceramidase to regulate myelin lipid metabolism

TMEM106B is an endolysosomal transmembrane protein not only associated with multiple neurological disorders including frontotemporal dementia, Alzheimer's disease, and hypomyelinating leukodystrophy but also potentially involved in COVID-19. Additionally, recent studies have identified amyloid fibrils of C-terminal TMEM106B in both aged healthy and neurodegenerative brains. However, so far little is known about physiological functions of TMEM106B in the endolysosome and how TMEM106B is involved in a wide range of human conditions at molecular levels. Here, we performed lipidomic analysis of the brain of TMEM106B-deficient mice. We found that TMEM106B deficiency significantly decreases levels of two major classes of myelin lipids, galactosylceramide and its sulfated derivative sulfatide. Subsequent co-immunoprecipitation assay showed that TMEM106B physically interacts with galactosylceramidase. We also found that galactosylceramidase activity was significantly increased in TMEM106B-deficient brains. Thus, our results suggest that TMEM106B interacts with galactosylceramidase to regulate myelin lipid metabolism and have implications for TMEM106B-associated diseases.

Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia

Transcriptome-wide association study (TWAS) tools have been applied to conduct proteome-wide association studies (PWASs) by integrating proteomics data with genome-wide association study (GWAS) summary data. The genetic effects of PWAS-identified significant genes are potentially mediated through genetically regulated protein abundance, thus informing the underlying disease mechanisms better than GWAS loci. However, existing TWAS/PWAS tools are limited by considering only one statistical model. We propose an omnibus PWAS pipeline to account for multiple statistical models and demonstrate improved performance by simulation and application studies of Alzheimer disease (AD) dementia. We employ the Aggregated Cauchy Association Test to derive omnibus PWAS (PWAS-O) p values from PWAS p values obtained by three existing tools assuming complementary statistical models-TIGAR, PrediXcan, and FUSION. Our simulation studies demonstrated improved power, with well-calibrated type I error, for PWAS-O over all three individual tools. We applied PWAS-O to studying AD dementia with reference proteomic data profiled from dorsolateral prefrontal cortex of postmortem brains from individuals of European ancestry. We identified 43 risk genes, including 5 not identified by previous studies, which are interconnected through a protein-protein interaction network that includes the well-known AD risk genes TOMM40, APOC1, and APOC2. We also validated causal genetic effects mediated through the proteome for 27 (63%) PWAS-O risk genes, providing insights into the underlying biological mechanisms of AD dementia and highlighting promising targets for therapeutic development. PWAS-O can be easily applied to studying other complex diseases.

Orchestration of antiviral responses within the infected central nervous system

Many newly emerging and re-emerging viruses have neuroinvasive potential, underscoring viral encephalitis as a global research priority. Upon entry of the virus into the CNS, severe neurological life-threatening conditions may manifest that are associated with high morbidity and mortality. The currently available therapeutic arsenal against viral encephalitis is rather limited, emphasizing the need to better understand the conditions of local antiviral immunity within the infected CNS. In this review, we discuss new insights into the pathophysiology of viral encephalitis, with a focus on myeloid cells and CD8+ T cells, which critically contribute to protection against viral CNS infection. By illuminating the prerequisites of myeloid and T cell activation, discussing new discoveries regarding their transcriptional signatures, and dissecting the mechanisms of their recruitment to sites of viral replication within the CNS, we aim to further delineate the complexity of antiviral responses within the infected CNS. Moreover, we summarize the current knowledge in the field of virus infection and neurodegeneration and discuss the potential links of some neurotropic viruses with certain pathological hallmarks observed in neurodegeneration.

The genetic landscape of neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

Multimodal analysis of disease onset in Alzheimer's disease using Connectome, Molecular, and genetics data

Alzheimer's disease (AD) and its related age at onset (AAO) are highly heterogeneous, due to the inherent complexity of the disease. They are affected by multiple factors, such as neuroimaging and genetic predisposition. Multimodal integration of various data types is necessary; however, it has been nontrivial due to the high dimensionality of each modality. We aimed to identify multimodal biomarkers of AAO in AD using an extended version of sparse canonical correlation analysis, in which we integrated two imaging modalities, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), and genetic data in the form of single-nucleotide polymorphisms (SNPs) obtained from the Alzheimer's disease neuroimaging initiative database. These three modalities cover low-to-high-level complementary information and offer multiscale insights into the AAO. We identified multivariate markers of AAO in AD using fMRI, PET, and SNP. Furthermore, the markers identified were largely consistent with those reported in the existing literature. In particular, our serial mediation analysis suggests that genetic variants influence the AAO in AD by indirectly affecting brain connectivity by mediation of amyloid-beta protein accumulation, supporting a plausible path in existing research. Our approach provides comprehensive biomarkers related to AAO in AD and offers novel multimodal insights into AD.

Variant-to-function mapping of late-onset Alzheimer's disease GWAS signals in human microglial cell models implicates RTFDC1 at the CASS4 locus

Late-onset Alzheimer's disease (LOAD) research has principally focused on neurons over the years due to their known role in the production of amyloid beta plaques and neurofibrillary tangles. In contrast, recent genomic studies of LOAD have implicated microglia as culprits of the prolonged inflammation exacerbating the neurodegeneration observed in patient brains. Indeed, recent LOAD genome-wide association studies (GWAS) have reported multiple loci near genes related to microglial function, including TREM2, ABI3, and CR1. However, GWAS alone cannot pinpoint underlying causal variants or effector genes at such loci, as most signals reside in non-coding regions of the genome and could presumably confer their influence frequently via long-range regulatory interactions. We elected to carry out a combination of ATAC-seq and high-resolution promoter-focused Capture-C in two human microglial cell models (iPSC-derived microglia and HMC3) in order to physically map interactions between LOAD GWAS-implicated candidate causal variants and their corresponding putative effector genes. Notably, we observed consistent evidence that rs6024870 at the GWAS CASS4 locus contacted the promoter of nearby gene, RTFDC1. We subsequently observed a directionallly consistent decrease in RTFDC1 expression with the the protective minor A allele of rs6024870 via both luciferase assays in HMC3 cells and expression studies in primary human microglia. Through CRISPR-Cas9-mediated deletion of the putative regulatory region harboring rs6024870 in HMC3 cells, we observed increased pro-inflammatory cytokine secretion and decreased DNA double strand break repair related, at least in part, to RTFDC1 expression levels. Our variant-to-function approach therefore reveals that the rs6024870-harboring regulatory element at the LOAD 'CASS4' GWAS locus influences both microglial inflammatory capacity and DNA damage resolution, along with cumulative evidence implicating RTFDC1 as a novel candidate effector gene.

The genetic association between bipolar disorder and dementia: a qualitative review

Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy and recurrent episodes of mania/hypomania and depression. Bipolar disorder may be regarded as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and dementia development. In the current review, we employed genome-wide association studies to comprehensively investigate the genetic variants associated with bipolar disorder and dementia. Thirty-nine published manuscripts were identified: 20 on bipolar disorder and 19 on dementia. The results showed that the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A were overlapping between patients with bipolar disorder and dementia. In conclusion, the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and the development of dementia in patients with bipolar disorder.

Gene-gene functional relationships in Alzheimer's disease: CELF1 regulates KLC1 alternative splicing

The causes of Alzheimer's disease (AD) are poorly understood, although many genes are known to be involved in this pathology. To gain insights into the underlying molecular mechanisms, it is essential to identify the relationships between individual AD genes. Previous work has shown that the splice variant E of KLC1 (KLC1_vE) promotes AD, and that the CELF1 gene, which encodes an RNA-binding protein involved in splicing regulation, is at a risk locus for AD. Here, we identified a functional link between CELF1 and KLC1 in AD pathogenesis. Transcriptomic data from human samples from different ethnic groups revealed that CELF1 mRNA levels are low in AD brains, and the splicing pattern of KLC1 is strongly correlated with CELF1 expression levels. Specifically, KLC1_vE is negatively correlated with CELF1. Depletion and overexpression experiments in cultured cells demonstrated that the CELF1 protein down-regulates KLC1_vE. In a cross-linking and immunoprecipitation sequencing (CLIP-seq) database, CELF1 directly binds to KLC1 RNA, following which it likely modulates terminal exon usage, hence KLC1_vE formation. These findings reveal a new pathogenic pathway where a risk allele of CELF1 is associated with reduced CELF1 expression, which up-regulates KLC1_vE to promote AD.

Single-nucleus multiome analysis of human cerebellum in Alzheimer's disease-related dementia

Although human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from cerebellum from 9 human cases of AD/ADRD and 8 controls, and with frontal cortex of 6 AD donors for additional comparison. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we prioritized two likely causal genes, including Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and Hi-C looping data. This first cell subtype-specific regulatory landscape in the human cerebellum identified here offer novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Alzheimer's disease risk gene CD2AP is a dose-sensitive determinant of synaptic structure and plasticity

CD2-Associated protein (CD2AP) is a candidate susceptibility gene for Alzheimer's disease, but its role in the mammalian central nervous system remains largely unknown. We show that CD2AP protein is broadly expressed in the adult mouse brain, including within cortical and hippocampal neurons, where it is detected at pre-synaptic terminals. Deletion of Cd2ap altered dendritic branching and spine density, and impaired ubiquitin-proteasome system activity. Moreover, in mice harboring either one or two copies of a germline Cd2ap null allele, we noted increased paired-pulse facilitation at hippocampal Schaffer-collateral synapses, consistent with a haploinsufficient requirement for pre-synaptic release. Whereas conditional Cd2ap knockout in the brain revealed no gross behavioral deficits in either 3.5- or 12-month-old mice, Cd2ap heterozygous mice demonstrated subtle impairments in discrimination learning using a touchscreen task. Based on unbiased proteomics, partial or complete loss of Cd2ap triggered perturbation of proteins with roles in protein folding, lipid metabolism, proteostasis, and synaptic function. Overall, our results reveal conserved, dose-sensitive requirements for CD2AP in the maintenance of neuronal structure and function, including synaptic homeostasis and plasticity, and inform our understanding of possible cell-type specific mechanisms in Alzheimer's Disease.

Alzheimer's disease protective allele of Clusterin modulates neuronal excitability through lipid-droplet-mediated neuron-glia communication

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms remain largely unknown. For a strong AD-associated locus near Clusterin ( CLU ), we tied an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. We identified a putative causal SNP of CLU that impacts neuron-specific chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. Transcriptomic analysis and functional studies in induced pluripotent stem cell (iPSC)-derived neurons co-cultured with mouse astrocytes show that neuronal CLU facilitates neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes cause astrocytes to uptake less glutamate thereby altering neuron excitability. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.

Region-based analysis with functional annotation identifies genes associated with cognitive function in South Asians from India

The prevalence of dementia among South Asians across India is approximately 7.4% in those 60 years and older, yet little is known about genetic risk factors for dementia in this population. Most known risk loci for Alzheimer's disease (AD) have been identified from studies conducted in European Ancestry (EA) but are unknown in South Asians. Using whole-genome sequence data from 2680 participants from the Diagnostic Assessment of Dementia for the Longitudinal Aging Study of India (LASI-DAD), we performed a gene-based analysis of 84 genes previously associated with AD in EA. We investigated associations with the Hindi Mental State Examination (HMSE) score and factor scores for general cognitive function and five cognitive domains. For each gene, we examined missense/loss-of-function (LoF) variants and brain-specific promoter/enhancer variants, separately, both with and without incorporating additional annotation weights (e.g., deleteriousness, conservation scores) using the variant-Set Test for Association using Annotation infoRmation (STAAR). In the missense/LoF analysis without annotation weights and controlling for age, sex, state/territory, and genetic ancestry, three genes had an association with at least one measure of cognitive function (FDR q<0.1). APOE was associated with four measures of cognitive function, PICALM was associated with HMSE score, and TSPOAP1 was associated with executive function. The most strongly associated variants in each gene were rs429358 (APOE ε4), rs779406084 (PICALM), and rs9913145 (TSPOAP1). rs779406084 is a rare missense mutation that is more prevalent in LASI-DAD than in EA (minor allele frequency=0.075% vs. 0.0015%); the other two are common variants. No genes in the brain-specific promoter/enhancer analysis met criteria for significance. Results with and without annotation weights were similar. Missense/LoF variants in some genes previously associated with AD in EA are associated with measures of cognitive function in South Asians from India. Analyzing genome sequence data allows identification of potential novel causal variants enriched in South Asians.

Human apolipoprotein E glycosylation and sialylation: from structure to function

Human apolipoprotein E (ApoE) was first identified as a polymorphic gene in the 1970s; however, the genetic association of ApoE genotypes with late-onset sporadic Alzheimer's disease (sAD) was only discovered 20 years later. Since then, intensive research has been undertaken to understand the molecular effects of ApoE in the development of sAD. Despite three decades' worth of effort and over 10,000 papers published, the greatest mystery in the ApoE field remains: human ApoE isoforms differ by only one or two amino acid residues; what is responsible for their significantly distinct roles in the etiology of sAD, with ApoE4 conferring the greatest genetic risk for sAD whereas ApoE2 providing exceptional neuroprotection against sAD. Emerging research starts to point to a novel and compelling hypothesis that the sialoglycans posttranslationally appended to human ApoE may serve as a critical structural modifier that alters the biology of ApoE, leading to the opposing impacts of ApoE isoforms on sAD and likely in the peripheral systems as well. ApoE has been shown to be posttranslationally glycosylated in a species-, tissue-, and cell-specific manner. Human ApoE, particularly in brain tissue and cerebrospinal fluid (CSF), is highly glycosylated, and the glycan chains are exclusively attached via an O-linkage to serine or threonine residues. Moreover, studies have indicated that human ApoE glycans undergo sialic acid modification or sialylation, a structural alteration found to be more prominent in ApoE derived from the brain and CSF than plasma. However, whether the sialylation modification of human ApoE has a biological role is largely unexplored. Our group recently first reported that the three major isoforms of human ApoE in the brain undergo varying degrees of sialylation, with ApoE2 exhibiting the most abundant sialic acid modification, whereas ApoE4 is the least sialylated. Our findings further indicate that the sialic acid moiety on human ApoE glycans may serve as a critical modulator of the interaction of ApoE with amyloid β (Aβ) and downstream Aβ pathogenesis, a prominent pathologic feature in AD. In this review, we seek to provide a comprehensive summary of this exciting and rapidly evolving area of ApoE research, including the current state of knowledge and opportunities for future exploration.

Latent profiles of modifiable dementia risk factors in later midlife: relationships with incident dementia, cognition, and neuroimaging outcomes

In 2020, the Lancet Commission identified 12 modifiable factors that increase population-level dementia risk. It is unclear if these risk factors co-occur among individuals in a clinically meaningful way. Using latent class analysis, we identified profiles of modifiable dementia risk factors in dementia-free adults aged 60-64 years from the UK Biobank. We then estimated associations between these profiles with incident dementia, cognition, and neuroimaging outcomes, and explored the differences across profiles in the effects of a polygenic risk score for Alzheimer's disease on outcomes. In 55,333 males and 63,063 females, three sex-specific latent profiles were identified: cardiometabolic risk, substance use-related risk, and low risk. The cardiometabolic risk profile in both males and females was associated with greater incidence of all-cause dementia (male: OR [95% CI] = 2.33 [2.03, 2.66]; female: OR [95% CI] = 1.44 [1.24, 1.68]), poorer cognitive performance, greater brain atrophy, and greater white matter hyperintensity volume compared to the low risk profile. The substance use-related risk profile in males was associated with poorer cognitive performance and greater white matter hyperintensities compared to the low risk profile, but no difference in all-cause dementia incidence was observed (OR [95% CI] = 1.00 [0.95, 1.06]). In females, the substance use-related risk profile demonstrated increased dementia incidence (OR [95% CI] = 1.58 [1.57, 1.58]) and greater brain atrophy but smaller white matter hyperintensity volume compared to the low risk profile. The polygenic risk score had larger effects among females, and differentially influenced outcomes across profiles; for instance, there were larger effects of the polygenic risk score on atrophy in the cardiometabolic profile vs. the low risk profile among males, and larger effects of the polygenic risk score on loss of white matter integrity in the cardiometabolic profile vs. the low risk profile among females. These results reveal three modifiable dementia risk profiles, their unique cognitive/neuroimaging outcomes, and their interactions with genetic risk for Alzheimer's disease. These differences highlight the need to consider population heterogeneity in risk prediction tools and in planning personalized prevention strategies.

Eicosanoid signaling in neuroinflammation associated with Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative condition affecting a substantial portion of the global population. It is marked by a complex interplay of factors, including the accumulation of amyloid plaques and tau tangles within the brain, leading to neuroinflammation and neuronal damage. Recent studies have underscored the role of free lipids and their derivatives in the initiation and progression of AD. Eicosanoids, metabolites of polyunsaturated fatty acids like arachidonic acid (AA), emerge as key players in this scenario. Remarkably, eicosanoids can either promote or inhibit the development of AD, and this multifaceted role is determined by how eicosanoid signaling influences the immune responses within the brain. However, the precise molecular mechanisms dictating the dual role of eicosanoids in AD remain elusive. In this comprehensive review, we explore the intricate involvement of eicosanoids in neuronal function and dysfunction. Furthermore, we assess the therapeutic potential of targeting eicosanoid signaling pathways as a viable strategy for mitigating or halting the progression of AD.

Single-cell spatial transcriptomics reveals distinct patterns of dysregulation in non-neuronal and neuronal cells induced by the Trem2R47H Alzheimer's risk gene mutation

The R47H missense mutation of the TREM2 gene is a known risk factor for development of Alzheimer's Disease. In this study, we analyze the impact of the Trem2R47H mutation on specific cell types in multiple cortical and subcortical brain regions in the context of wild-type and 5xFAD mouse background. We profile 19 mouse brain sections consisting of wild-type, Trem2R47H, 5xFAD and Trem2R47H; 5xFAD genotypes using MERFISH spatial transcriptomics, a technique that enables subcellular profiling of spatial gene expression. Spatial transcriptomics and neuropathology data are analyzed using our custom pipeline to identify plaque and Trem2R47H-induced transcriptomic dysregulation. We initially analyze cell type-specific transcriptomic alterations induced by plaque proximity. Next, we analyze spatial distributions of disease associated microglia and astrocytes, and how they vary between 5xFAD and Trem2R47H; 5xFAD mouse models. Finally, we analyze the impact of the Trem2R47H mutation on neuronal transcriptomes. The Trem2R47H mutation induces consistent upregulation of Bdnf and Ntrk2 across many cortical excitatory neuron types, independent of amyloid pathology. Spatial investigation of genotype enriched subclusters identified spatially localized neuronal subpopulations reduced in 5xFAD and Trem2R47H; 5xFAD mice. Overall, our MERFISH spatial transcriptomics analysis identifies glial and neuronal transcriptomic alterations induced independently by 5xFAD and Trem2R47H mutations, impacting inflammatory responses in microglia and astrocytes, and activity and BDNF signaling in neurons.

SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies show that SR-TWAS improves power, due to increased training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real studies identify 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations are found for these significant risk genes.

A general principle governing neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans

The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.

Multifaceted roles of APOE in Alzheimer disease

For the past three decades, apolipoprotein E (APOE) has been known as the single greatest genetic modulator of sporadic Alzheimer disease (AD) risk, influencing both the average age of onset and the lifetime risk of developing AD. The APOEε4 allele significantly increases AD risk, whereas the ε2 allele is protective relative to the most common ε3 allele. However, large differences in effect size exist across ethnoracial groups that are likely to depend on both global genetic ancestry and local genetic ancestry, as well as gene-environment interactions. Although early studies linked APOE to amyloid-β - one of the two culprit aggregation-prone proteins that define AD - in the past decade, mounting work has associated APOE with other neurodegenerative proteinopathies and broader ageing-related brain changes, such as neuroinflammation, energy metabolism failure, loss of myelin integrity and increased blood-brain barrier permeability, with potential implications for longevity and resilience to pathological protein aggregates. Novel mouse models and other technological advances have also enabled a number of therapeutic approaches aimed at either attenuating the APOEε4-linked increased AD risk or enhancing the APOEε2-linked AD protection. This Review summarizes this progress and highlights areas for future research towards the development of APOE-directed therapeutics.

Towards cascading genetic risk in Alzheimer's disease

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.

Microglia in Health and Diseases: Integrative Hubs of the Central Nervous System (CNS)

Microglia are usually referred to as "the innate immune cells of the brain," "the resident macrophages of the central nervous system" (CNS), or "CNS parenchymal macrophages." These labels allude to their inherent immune function, related to their macrophage lineage. However, beyond their classic innate immune responses, microglia also play physiological roles crucial for proper brain development and maintenance of adult brain homeostasis. Microglia sense both external and local stimuli through a variety of surface receptors. Thus, they might serve as integrative hubs at the interface between the external environment and the CNS, able to decode, filter, and buffer cues from outside, with the aim of preserving and maintaining brain homeostasis. In this perspective, we will cast a critical look at how these multiple microglial functions are acquired and coordinated, and we will speculate on their impact on human brain physiology and pathology.

Clinical application of whole genome sequencing in young onset dementia: challenges and opportunities

INTRODUCTION

Young onset dementia (YOD) by its nature is difficult to diagnose. Despite involvement of multidisciplinary neurogenetics services, patients with YOD and their families face significant diagnostic delays. Genetic testing for people with YOD currently involves a staggered, iterative approach. There is currently no optimal single genetic investigation that simultaneously identifies the different genetic variants resulting in YOD.

AREAS COVERED

This review discusses the advances in clinical genomic testing for people with YOD. Whole genome sequencing (WGS) can be employed as a 'one stop shop' genomic test for YOD. In addition to single nucleotide variants, WGS can reliably detect structural variants, short tandem repeat expansions, mitochondrial genetic variants as well as capture single nucleotide polymorphisms for the calculation of polygenic risk scores.

EXPERT OPINION

WGS, when used as the initial genetic test, can enhance the likelihood of a precision diagnosis and curtail the time taken to reach this. Finding a clinical diagnosis using WGS can reduce invasive and expensive investigations and could be cost effective. These advances need to be balanced against the limitations of the technology and the genetic counseling needs for these vulnerable patients and their families.

Single-cell multiregion dissection of Alzheimer's disease

Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.

Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry

INTRODUCTION

Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts.

METHODS

Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses.

RESULTS

A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, p = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry.

DISCUSSION

These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects.

HIGHLIGHTS

Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.

Prevalence and clinicopathological features of primary age-related tauopathy (PART): A large forensic autopsy study

INTRODUCTION

Primary age-related tauopathy (PART), often regarded as a minimally symptomatic pathology of old age, lacks comprehensive cohorts across various age groups.

METHODS

We examined PART prevalence and clinicopathologic features in 1589 forensic autopsy cases (≥40 years old, mean age ± SD 70.2 ± 14.2 years).

RESULTS

PART cases meeting criteria for argyrophilic grain diseases (AGD) were AGD+PART (n = 181). The remaining PART cases (n = 719, 45.2%) were classified as comorbid conditions (PART-C, n = 90) or no comorbid conditions (pure PART, n = 629). Compared to controls (n = 208), Alzheimer's disease (n = 133), and AGD+PART, PART prevalence peaked in the individuals in their 60s (65.5%) and declined in the 80s (21.5%). No significant clinical background differences were found (excluding controls). However, PART-C in patients inclusive of age 80 had a higher suicide rate than pure PART (p < 0.05), and AGD+PART showed more dementia (p < 0.01) and suicide (p < 0.05) than pure PART.

DISCUSSION

Our results advocate a reevaluation of the PART concept and its diagnostic criteria.

HIGHLIGHTS

We investigated 1589 forensic autopsy cases to investigate the features of primary age-related tauopathy (PART). PART peaked in people in their 60s in our study. Many PART cases over 80s had comorbid pathologies in addition to neurofibrillary tangles pathology. Argyrophilic grain disease and Lewy pathology significantly affected dementia and suicide rates in PART. Our results suggest that the diagnostic criteria of PART need to be reconsidered.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature

The under-representation of non-European cohorts in neurodegenerative disease genome-wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non-European or multi-ancestry studies. Notably, only six of the loci have been replicated. The significant under-representation of non-European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. HIGHLIGHTS: Eighty-two percent of neurodegenerative genome-wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.

Finemap-MiXeR: A variational Bayesian approach for genetic finemapping

Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBO's gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Employing Informatics Strategies in Alzheimer's Disease Research: A Review from Genetics, Multiomics, and Biomarkers to Clinical Outcomes

Alzheimer's disease (AD) is a critical national concern, affecting 5.8 million people and costing more than $250 billion annually. However, there is no available cure. Thus, effective strategies are in urgent need to discover AD biomarkers for disease early detection and drug development. In this review, we study AD from a biomedical data scientist perspective to discuss the four fundamental components in AD research: genetics (G), molecular multiomics (M), multimodal imaging biomarkers (B), and clinical outcomes (O) (collectively referred to as the GMBO framework). We provide a comprehensive review of common statistical and informatics methodologies for each component within the GMBO framework, accompanied by the major findings from landmark AD studies. Our review highlights the potential of multimodal biobank data in addressing key challenges in AD, such as early diagnosis, disease heterogeneity, and therapeutic development. We identify major hurdles in AD research, including data scarcity and complexity, and advocate for enhanced collaboration, data harmonization, and advanced modeling techniques. This review aims to be an essential guide for understanding current biomedical data science strategies in AD research, emphasizing the need for integrated, multidisciplinary approaches to advance our understanding and management of AD.

Tracking neuroinflammatory biomarkers in Alzheimer's disease: a strategy for individualized therapeutic approaches?

BACKGROUND

Recent trials of anti-amyloid-β (Aβ) monoclonal antibodies, including lecanemab and donanemab, in early Alzheimer disease (AD) showed that these drugs have limited clinical benefits and their use comes with a significant risk of serious adverse events. Thus, it seems crucial to explore complementary therapeutic approaches. Genome-wide association studies identified robust associations between AD and several AD risk genes related to immune response, including but not restricted to CD33 and TREM2. Here, we critically reviewed the current knowledge on candidate neuroinflammatory biomarkers and their role in characterizing the pathophysiology of AD.

MAIN BODY

Neuroinflammation is recognized to be a crucial and contributing component of AD pathogenesis. The fact that neuroinflammation is most likely present from earliest pre-stages of AD and co-occurs with the deposition of Aβ reinforces the need to precisely define the sequence and nature of neuroinflammatory events. Numerous clinical trials involving anti-inflammatory drugs previously yielded unfavorable outcomes in early and mild-to-moderate AD. Although the reasons behind these failures remain unclear, these may include the time and the target selected for intervention. Indeed, in our review, we observed a stage-dependent neuroinflammatory process in the AD brain. While the initial activation of glial cells counteracts early brain Aβ deposition, the downregulation in the functional state of microglia occurs at more advanced disease stages. To address this issue, personalized neuroinflammatory modulation therapy is required. The emergence of reliable blood-based neuroinflammatory biomarkers, particularly glial fibrillary acidic protein, a marker of reactive astrocytes, may facilitate the classification of AD patients based on the ATI(N) biomarker framework. This expands upon the traditional classification of Aβ ("A"), tau ("T"), and neurodegeneration ("N"), by incorporating a novel inflammatory component ("I").

CONCLUSIONS

The present review outlines the current knowledge on potential neuroinflammatory biomarkers and, importantly, emphasizes the role of longitudinal analyses, which are needed to accurately monitor the dynamics of cerebral inflammation. Such a precise information on time and place will be required before anti-inflammatory therapeutic interventions can be considered for clinical evaluation. We propose that an effective anti-neuroinflammatory therapy should specifically target microglia and astrocytes, while considering the individual ATI(N) status of patients.

Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex

Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants. Here we broadly define a "module-QTL" as the association of a genetic variant with a summary measure of gene co-expression. This approach aims to reduce the multiple testing burden of a trans-eQTL search through the consolidation of gene-based testing and provide biological context to eQTLs shared between genes. In this article we provide an in-depth examination of the co-expression module eQTL (module-QTL) through literature review, theoretical investigation, and real-data application of the module-QTL to three large prefrontal cortex genotype-RNA sequencing datasets. We find module-QTLs in our study that are disease associated and reproducible are not additionally informative beyond cis- or trans-eQTLs for module genes. Through comparison to prior studies, we highlight promises and limitations of the module-QTL across study designs and provide recommendations for further investigation of the module-QTL framework.

Human brain proteome-wide association study provides insights into the genetic components of protein abundance in obesity

BACKGROUNDS

Genome-wide association studies have identified multiple genetic variants associated with obesity. However, most obesity-associated loci were waiting to be translated into new biological insights. Given the critical role of brain in obesity development, we sought to explore whether obesity-associated genetic variants could be mapped to brain protein abundances.

METHODS

We performed proteome-wide association studies (PWAS) and colocalization analyses to identify genes whose cis-regulated brain protein abundances were associated with obesity-related traits, including body fat percentage, trunk fat percentage, body mass index, visceral adipose tissue, waist circumference, and waist-to-hip ratio. We then assessed the druggability of the identified genes and conducted pathway enrichment analysis to explore their functional relevance. Finally, we evaluated the effects of the significant PWAS genes at the brain transcriptional level.

RESULTS

By integrating human brain proteomes from discovery (ROSMAP, N = 376) and validation datasets (BANNER, N = 198) with genome-wide summary statistics of obesity-related phenotypes (N ranged from 325,153 to 806,834), we identified 51 genes whose cis-regulated brain protein abundance was associated with obesity. These 51 genes were enriched in 11 metabolic processes, e.g., small molecule metabolic process and metabolic pathways. Fourteen of the 51 genes had high drug repurposing value. Ten of the 51 genes were also associated with obesity at the transcriptome level, suggesting that genetic variants likely confer risk of obesity by regulating mRNA expression and protein abundance of these genes.

CONCLUSIONS

Our study provides new insights into the genetic component of human brain protein abundance in obesity. The identified proteins represent promising therapeutic targets for future drug development.

Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry.

METHODS

We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals.

RESULTS

In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD.

DISCUSSION

The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology.

HIGHLIGHTS

Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.

Cellular and pathological functions of tau

Tau protein is involved in various cellular processes, including having a canonical role in binding and stabilization of microtubules in neurons. Tauopathies are neurodegenerative diseases marked by the abnormal accumulation of tau protein aggregates in neurons, as seen, for example, in conditions such as frontotemporal dementia and Alzheimer disease. Mutations in tau coding regions or that disrupt tau mRNA splicing, tau post-translational modifications and cellular stress factors (such as oxidative stress and inflammation) increase the tendency of tau to aggregate and interfere with its clearance. Pathological tau is strongly implicated in the progression of neurodegenerative diseases, and the propagation of tau aggregates is associated with disease severity. Recent technological advancements, including cryo-electron microscopy and disease models derived from human induced pluripotent stem cells, have increased our understanding of tau-related pathology in neurodegenerative conditions. Substantial progress has been made in deciphering tau aggregate structures and the molecular mechanisms that underlie protein aggregation and toxicity. In this Review, we discuss recent insights into the diverse cellular functions of tau and the pathology of tau inclusions and explore the potential for therapeutic interventions.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Toward the development of a sporadic model of Alzheimer's disease: comparing pathologies between humanized APP and the familial J20 mouse models

Background

Finding successful therapies for individuals with Alzheimer's disease (AD) remains an ongoing challenge. One contributing factor is that the mouse models commonly used in preclinical research primarily mimic the familial form of AD, whereas the vast majority of human cases are sporadic. Accordingly, for a sporadic mouse model of AD, incorporating the multifactorial aspects of the disease is of utmost importance.

Methods

In the current study, we exposed humanized Aβ knock-in mice (hAβ-KI) to weekly low-dose lipopolysaccharide (LPS) injections until 24 weeks of age and compared the development of AD pathologies to the familial AD mouse model known as the J20 mice.

Results

At the early time point of 24 weeks, hAβ-KI mice and J20 mice exhibited spatial memory impairments in the Barnes maze. Strikingly, both hAβ-KI mice and J20 mice showed significant loss of dendritic spines when compared to WT controls, despite the absence of Aβ plaques in hAβ-KI mice at 24 weeks of age. Glial cell numbers remained unchanged in hAβ-KI mice compared to WT, and LPS exposure in hAβ-KI mice did not result in memory deficits and failed to exacerbate any other examined AD pathology.

Conclusion

The study highlights the potential of hAβ-KI mice as a model for sporadic AD, demonstrating early cognitive deficits and synaptic alterations despite no evidence of Aβ plaque formation. These findings underscore the importance of considering multifactorial influences in sporadic AD pathogenesis and the need for innovative models to advance our understanding and treatment strategies for this complex disease.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

A systems biology-based identification and in vivo functional screening of Alzheimer's disease risk genes reveal modulators of memory function

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C. elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Genomic stress and impaired DNA repair in Alzheimer disease

Alzheimer disease (AD) is the most prominent form of dementia and has received considerable attention due to its growing burden on economic, healthcare and basic societal infrastructures. The two major neuropathological hallmarks of AD, i.e., extracellular amyloid beta (Aβ) peptide plaques and intracellular hyperphosphorylated Tau neurofibrillary tangles, have been the focus of much research, with an eye on understanding underlying disease mechanisms and identifying novel therapeutic avenues. One often overlooked aspect of AD is how Aβ and Tau may, through indirect and direct mechanisms, affect genome integrity. Herein, we review evidence that Aβ and Tau abnormalities induce excessive genomic stress and impair genome maintenance mechanisms, events that can promote DNA damage-induced neuronal cell loss and associated brain atrophy.

Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank

Background

During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging.

Methods

We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer's disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data.

Results

Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages.

Conclusions

We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Single-cell atlas of ABCA7 loss-of-function reveals impaired neuronal respiration via choline-dependent lipid imbalances

Loss-of-function (LoF) variants in the lipid transporter ABCA7 significantly increase the risk of Alzheimer's disease (odds ratio ∼2), yet the pathogenic mechanisms and the neural cell types affected by these variants remain largely unknown. Here, we performed single-nuclear RNA sequencing of 36 human post-mortem samples from the prefrontal cortex of 12 ABCA7 LoF carriers and 24 matched non-carrier control individuals. ABCA7 LoF was associated with gene expression changes in all major cell types. Excitatory neurons, which expressed the highest levels of ABCA7, showed transcriptional changes related to lipid metabolism, mitochondrial function, cell cycle-related pathways, and synaptic signaling. ABCA7 LoF-associated transcriptional changes in neurons were similarly perturbed in carriers of the common AD missense variant ABCA7 p.Ala1527Gly (n = 240 controls, 135 carriers), indicating that findings from our study may extend to large portions of the at-risk population. Consistent with ABCA7's function as a lipid exporter, lipidomic analysis of isogenic iPSC-derived neurons (iNs) revealed profound intracellular triglyceride accumulation in ABCA7 LoF, which was accompanied by a relative decrease in phosphatidylcholine abundance. Metabolomic and biochemical analyses of iNs further indicated that ABCA7 LoF was associated with disrupted mitochondrial bioenergetics that suggested impaired lipid breakdown by uncoupled respiration. Treatment of ABCA7 LoF iNs with CDP-choline (a rate-limiting precursor of phosphatidylcholine synthesis) reduced triglyceride accumulation and restored mitochondrial function, indicating that ABCA7 LoF-induced phosphatidylcholine dyshomeostasis may directly disrupt mitochondrial metabolism of lipids. Treatment with CDP-choline also rescued intracellular amyloid β -42 levels in ABCA7 LoF iNs, further suggesting a link between ABCA7 LoF metabolic disruptions in neurons and AD pathology. This study provides a detailed transcriptomic atlas of ABCA7 LoF in the human brain and mechanistically links ABCA7 LoF-induced lipid perturbations to neuronal energy dyshomeostasis. In line with a growing body of evidence, our study highlights the central role of lipid metabolism in the etiology of Alzheimer's disease.

Systematic Review and Phenome-Wide Scans of Genetic Associations with Vascular Cognitive Impairment

Vascular cognitive impairment (VCI) is a heterogenous form of cognitive impairment that results from cerebrovascular disease. It is a result of both genetic and non-genetic factors. Although much research has been conducted on the genetic contributors to other forms of cognitive impairment (e.g. Alzheimer's disease), knowledge is lacking on the genetic factors associated with VCI. A better understanding of the genetics of VCI will be critical for prevention and treatment. To begin to fill this gap, the genetic contributors are reviewed with VCI from the literature. Phenome-wide scans of the identified genes are conducted and genetic variants identified in the review in large-scale resources displaying genetic variant-trait association information. Gene set are also carried out enrichment analysis using the genes identified from the review. Thirty one articles are identified meeting the search criteria and filters, from which 107 unique protein-coding genes are noted related to VCI. The phenome-wide scans and gene set enrichment analysis identify pathways associated with a diverse set of biological systems. This results indicate that genes with evidence of involvement in VCI are involved in a diverse set of biological functions. This information can facilitate downstream research to better dissect possible shared biological mechanisms for future therapies.

Comprehensive Overview of Alzheimer's Disease: Etiological Insights and Degradation Strategies

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects millions of individuals globally. AD is associated with cognitive decline and memory loss that worsens with aging. A statistical report using U.S. data on AD estimates that approximately 6.9 million individuals suffer from AD, a number projected to surge to 13.8 million by 2060. Thus, there is a critical imperative to pinpoint and address AD and its hallmark tau protein aggregation early to prevent and manage its debilitating effects. Amyloid-β and tau proteins are primarily associated with the formation of plaques and neurofibril tangles in the brain. Current research efforts focus on degrading amyloid-β and tau or inhibiting their synthesis, particularly targeting APP processing and tau hyperphosphorylation, aiming to develop effective clinical interventions. However, navigating this intricate landscape requires ongoing studies and clinical trials to develop treatments that truly make a difference. Genome-wide association studies (GWASs) across various cohorts identified 40 loci and over 300 genes associated with AD. Despite this wealth of genetic data, much remains to be understood about the functions of these genes and their role in the disease process, prompting continued investigation. By delving deeper into these genetic associations, novel targets such as kinases, proteases, cytokines, and degradation pathways, offer new directions for drug discovery and therapeutic intervention in AD. This review delves into the intricate biological pathways disrupted in AD and identifies how genetic variations within these pathways could serve as potential targets for drug discovery and treatment strategies. Through a comprehensive understanding of the molecular underpinnings of AD, researchers aim to pave the way for more effective therapies that can alleviate the burden of this devastating disease.

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent form of dementia, affecting millions worldwide with a progressive decline in cognitive abilities. The AD continuum encompasses a prodormal stage known as Mild Cognitive Impairment (MCI), where patients may either progress to AD (MCIc) or remain stable (MCInc). Understanding the underlying mechanisms of AD requires complementary analysis derived from different data sources, leading to the development of multimodal deep learning models. In this study, we leveraged structural and functional Magnetic Resonance Imaging (sMRI/fMRI) to investigate the disease-induced grey matter and functional network connectivity changes. Moreover, considering AD's strong genetic component, we introduce Single Nucleotide Polymorphisms (SNPs) as a third channel. Given such diverse inputs, missing one or more modalities is a typical concern of multimodal methods. We hence propose a novel deep learning based classification framework where generative module employing Cycle Generative Adversarial Networks (cGAN) was adopted to impute missing data within the latent space. Additionally, we adopted an Explainable Artificial Intelligence (XAI) method, Integrated Gradients (IG), to extract input features relevance, enhancing our understanding of the learned representations. Two critical tasks were addressed: AD detection and MCI conversion prediction. Experimental results showed that our framework was able to reach the state-of-the-art in the classification of CN vs AD reaching an average test accuracy of 0.926 ± 0.02. For the MCInc vs MCIc task, we achieved an average prediction accuracy of 0.711 ± 0.01 using the pre-trained model for CN and AD. The interpretability analysis revealed that the classification performance was led by significant grey matter modulations in cortical and subcortical brain areas well known for their association with AD. Moreover, impairments in sensory-motor and visual resting state network connectivity along the disease continuum, as well as mutations in SNPs defining biological processes linked to amyloid-beta and cholesterol formation clearance and regulation, were identified as contributors to the achieved performance. Overall, our integrative deep learning approach shows promise for AD detection and MCI prediction, while shading light on important biological insights.