Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

African ancestry neurodegeneration risk variant disrupts an intronic branchpoint in GBA1

Recently, a novel African ancestry specific Parkinson's disease (PD) risk signal was identified at the gene encoding glucocerebrosidase (GBA1). This variant (rs3115534-G) is carried by ~50% of West African PD cases and imparts a dose-dependent increase in risk for disease. The risk variant has varied frequencies across African ancestry groups, but is almost absent in European and Asian ancestry populations. GBA1 is a gene of high clinical and therapeutic interest. Damaging bi-allelic protein-coding variants cause Gaucher disease and mono-allelic variants confer risk for PD and Dementia with Lewy Bodies, likely by reducing the function of glucocerebrosidase. Interestingly, the novel African ancestry specific GBA1 risk variant is a non-coding variant, suggesting a different mechanism of action. Using full length RNA transcript sequencing, we identified intron 8 expression in risk variant carriers (G) but not in non-variant carriers (T). Antibodies targeting the N-terminus of glucocerebrosidase showed that this intron-retained isoform is likely not protein coding and subsequent proteomics did not identify a shorter protein isoform, suggesting the disease mechanism is RNA-based. CRISPR editing of the reported index variant (rs3115534) revealed that this is the responsible sequence alteration driving production of these intron 8 containing transcripts. Follow-up analysis of this variant showed that it is in a key intronic branchpoint sequence and therefore has important implications in splicing and disease. In addition, when measuring glucocerebrosidase activity we identified a dose-dependent reduction in risk variant carriers (G). Overall, we report the functional effect of a GBA1 non-coding risk variant, which acts by interfering with the splicing of functional GBA1 transcripts, resulting in reduced protein levels and reduced glucocerebrosidase activity. This understanding reveals a novel therapeutic target in an underserved and underrepresented population.

Genetic analysis of the X chromosome in people with Lewy body dementia nominates new risk loci

Sex influences the prevalence and symptoms of Lewy body dementia (LBD). However, genome-wide association studies typically focus on autosomal variants and exclude sex-specific risk factors. We addressed this gap by performing an X chromosome-wide association study using whole-genome sequence data from 2591 LBD cases and 4391 controls. We identified a significant risk locus within intron 1 of MAP3K15 (rs141773145, odds ratio = 2.42, 95% confidence interval = 1.65-3.56, p-value = 7.0 × 10-6) in female LBD cases conditioned for APOE ε4 dosage. The locus includes an enhancer region that regulates MAP3K15 expression in ganglionic eminence cells derived from primary cultured neurospheres. Rare variant burden testing showed differential enrichment of missense mutations in TEX13A in female LBD cases, that did not reach significance (p-value = 1.34 × 10-4). These findings support the sex-specific effects of genetic factors and a potential role of Alzheimer's-related risk for females with LBD.

Identification of Potentially Repurposable Drugs for Lewy Body Dementia Using a Network-Based Approach

The conventional method of one drug being used for one target has not yielded therapeutic solutions for Lewy body dementia (LBD), which is a leading progressive neurological disorder characterized by significant loss of neurons. The age-related disease is marked by memory loss, hallucinations, sleep disorder, mental health deterioration, palsy, and cognitive impairment, all of which have no known effective cure. The present study deploys a network medicine pipeline to repurpose drugs having considerable effect on the genes and proteins related to the diseases of interest. We utilized the novel SAveRUNNER algorithm to quantify the proximity of all drugs obtained from DrugBank with the disease associated gene dataset obtained from Phenopedia and targets in the human interactome. We found that most of the 154 FDA-approved drugs predicted by SAveRUNNER were used to treat nervous system disorders, but some off-label drugs like quinapril and selegiline were interestingly used to treat hypertension and Parkinson's disease (PD), respectively. Additionally, we performed gene set enrichment analysis using Connectivity Map (CMap) and pathway enrichment analysis using EnrichR to validate the efficacy of the drug candidates obtained from the pipeline approach. The investigation enabled us to identify the significant role of the synaptic vesicle pathway in our disease and accordingly finalize 8 suitable antidepressant drugs from the 154 drugs initially predicted by SAveRUNNER. These potential anti-LBD drugs are either selective or non-selective inhibitors of serotonin, dopamine, and norepinephrine transporters. The validated selective serotonin and norepinephrine inhibitors like milnacipran, protriptyline, and venlafaxine are predicted to manage LBD along with the affecting symptomatic issues.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

BACKGROUND

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited.

METHODS

We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation.

RESULTS

Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOEand the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge.

CONCLUSIONS

Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Elevated serum LDL-C increases the risk of Lewy body dementia: a two-sample mendelian randomization study

BACKGROUND

Lewy body dementia (LBD) ranks second among prevalent neurodegenerative dementias. Previous studies have revealed associations of serum lipid measures with several neurodegenerative diseases. Nevertheless, the potential connection between serum lipids and LBD remains undetermined. In this study, Mendelian randomization (MR) analyses were carried out to assess the causal relationships of several serum lipid measures with the risk of developing LBD.

METHODS

Genome-wide association study (GWAS) data for serum lipids and LBD in European descent individuals were acquired from publicly available genetic summary data. A series of filtering procedures were conducted to identify the genetic variant candidates that are related to serum lipids, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). The causal effects were primarily determined through inverse-variance weighting (IVW)-based analyses.

RESULTS

Neither TG (odds ratio [OR] = 1.149; 95% confidence interval [CI], 0.887-1.489; P = 0.293) nor HDL-C (OR = 0.864; 95% CI, 0.718-1.041; P = 0.124) had causal effects on LBD. However, a causal relationship was identified between LDL-C and LBD (OR = 1.343; 95% CI, 1.094-1.649; P = 0.005), which remained significant (OR = 1.237; 95% CI, 1.015-1.508; P = 0.035) following adjustment for HDL-C and TG in multivariable MR.

CONCLUSIONS

Elevated serum LDL-C increases the risk of LBD, while HDL-C and TG have no significant causal effects on LBD.

Inhibition of cysteine protease cathepsin L increases the level and activity of lysosomal glucocerebrosidase

The glucocerebrosidase (GCase) encoded by the GBA1 gene hydrolyzes glucosylceramide (GluCer) to ceramide and glucose in lysosomes. Homozygous or compound heterozygous GBA1 mutations cause the lysosomal storage disease Gaucher disease (GD) due to severe loss of GCase activity. Loss-of-function variants in the GBA1 gene are also the most common genetic risk factor for Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Restoring lysosomal GCase activity represents an important therapeutic approach for GBA1-associated diseases. We hypothesized that increasing the stability of lysosomal GCase protein could correct deficient GCase activity in these conditions. However, it remains unknown how GCase stability is regulated in the lysosome. We found that cathepsin L, a lysosomal cysteine protease, cleaves GCase and regulates its stability. In support of these data, GCase protein was elevated in the brain of cathepsin L-KO mice. Chemical inhibition of cathepsin L increased both GCase levels and activity in fibroblasts from patients with GD. Importantly, inhibition of cathepsin L in dopaminergic neurons from a patient GBA1-PD led to increased GCase levels and activity as well as reduced phosphorylated α-synuclein. These results suggest that targeting cathepsin L-mediated GCase degradation represents a potential therapeutic strategy for GCase deficiency in PD and related disorders that exhibit decreased GCase activity.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

BACKGROUND

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited.

METHODS

We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation.

RESULTS

Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOE and the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge.

CONCLUSIONS

Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Dementia with Lewy Bodies: Genomics, Transcriptomics, and Its Future with Data Science

Dementia with Lewy bodies (DLB) is a significant public health issue. It is the second most common neurodegenerative dementia and presents with severe neuropsychiatric symptoms. Genomic and transcriptomic analyses have provided some insight into disease pathology. Variants within SNCA, GBA, APOE, SNCB, and MAPT have been shown to be associated with DLB in repeated genomic studies. Transcriptomic analysis, conducted predominantly on candidate genes, has identified signatures of synuclein aggregation, protein degradation, amyloid deposition, neuroinflammation, mitochondrial dysfunction, and the upregulation of heat-shock proteins in DLB. Yet, the understanding of DLB molecular pathology is incomplete. This precipitates the current clinical position whereby there are no available disease-modifying treatments or blood-based diagnostic biomarkers. Data science methods have the potential to improve disease understanding, optimising therapeutic intervention and drug development, to reduce disease burden. Genomic prediction will facilitate the early identification of cases and the timely application of future disease-modifying treatments. Transcript-level analyses across the entire transcriptome and machine learning analysis of multi-omic data will uncover novel signatures that may provide clues to DLB pathology and improve drug development. This review will discuss the current genomic and transcriptomic understanding of DLB, highlight gaps in the literature, and describe data science methods that may advance the field.

Network Proteomics of the Lewy Body Dementia Brain Reveals Presynaptic Signatures Distinct from Alzheimer's Disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

Gut microbiota in combination with blood metabolites reveals characteristics of the disease cluster of coronary artery disease and cognitive impairment: a Mendelian randomization study

Background

The coexistence of coronary artery disease (CAD) and cognitive impairment has become a common clinical phenomenon. However, there is currently limited research on the etiology of this disease cluster, discovery of biomarkers, and identification of precise intervention targets.

Methods

We explored the causal connections between gut microbiota, blood metabolites, and the disease cluster of CAD combined with cognitive impairment through two-sample Mendelian randomization (TSMR). Additionally, we determine the gut microbiota and blood metabolites with the strongest causal associations using Bayesian model averaging multivariate Mendelian randomization (MR-BMA) analysis. Furthermore, we will investigate the mediating role of blood metabolites through a two-step Mendelian randomization design.

Results

We identified gut microbiota that had significant causal associations with cognitive impairment. Additionally, we also discovered blood metabolites that exhibited significant causal associations with both CAD and cognitive impairment. According to the MR-BMA results, the free cholesterol to total lipids ratio in large very low density lipoprotein (VLDL) was identified as the key blood metabolite significantly associated with CAD. Similarly, the cholesteryl esters to total lipids ratio in small VLDL emerged as the primary blood metabolite with a significant causal association with dementia with lewy bodies (DLB). For the two-step Mendelian randomization analysis, we identified blood metabolites that could potentially mediate the association between genus Butyricicoccus and CAD in the potential causal links.

Conclusion

Our study utilized Mendelian randomization (MR) to identify the gut microbiota features and blood metabolites characteristics associated with the disease cluster of CAD combined with cognitive impairment. These findings will provide a meaningful reference for the identification of biomarkers for the disease cluster of CAD combined with cognitive impairment as well as the discovery of targets for intervention to address the problems in the clinic.

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

Importance

The under-representation of participants with non-European ancestry in genome-wide association studies (GWAS) is a critical issue that has significant implications, including hindering the progress of precision medicine initiatives. This issue is particularly significant in the context of neurodegenerative diseases (NDDs), where current therapeutic approaches have shown limited success. Addressing this under-representation is crucial to harnessing the full potential of genomic medicine in underserved communities and improving outcomes for NDD patients.

Objective

Our primary objective was to assess the representation of non-European ancestry participants in genetic discovery efforts related to NDDs. We aimed to quantify the extent of inclusion of diverse ancestry groups in NDD studies and determine the number of associated loci identified in more inclusive studies. Specifically, we sought to highlight the disparities in research efforts and outcomes between studies predominantly involving European ancestry participants and those deliberately targeting non-European or multi-ancestry populations across NDDs.

Evidence Review

We conducted a systematic review utilizing existing GWAS results and publications to assess the inclusion of diverse ancestry groups in neurodegeneration and neurogenetics studies. Our search encompassed studies published up to the end of 2022, with a focus on identifying research that deliberately included non-European or multi-ancestry cohorts. We employed rigorous methods for the inclusion of identified articles and quality assessment.

Findings

Our review identified a total of 123 NDD GWAS. Strikingly, 82% of these studies predominantly featured participants of European ancestry. Endeavors specifically targeting non-European or multi-ancestry populations across NDDs identified only 52 risk loci. This contrasts with predominantly European studies, which reported over 90 risk loci for a single disease. Encouragingly, over 65% of these discoveries occurred in 2020 or later, indicating a recent increase in studies deliberately including non-European cohorts.

Conclusions and relevance

Our findings underscore the pressing need for increased diversity in neurodegenerative research. The significant under-representation of non-European ancestry participants in NDD GWAS limits our understanding of the genetic underpinnings of these diseases. To advance the field of neurodegenerative research and develop more effective therapies, it is imperative that future investigations prioritize and harness the genomic diversity present within and across global populations.

Neuronal dysfunction and gene modulation by non-coding RNA in Parkinson's disease and synucleinopathies

Over the last few decades, emerging evidence suggests that non-coding RNAs (ncRNAs) including long-non-coding RNA (lncRNA), microRNA (miRNA) and circular-RNA (circRNA) contribute to the molecular events underlying progressive neuronal degeneration, and a plethora of ncRNAs have been identified significantly misregulated in many neurodegenerative diseases, including Parkinson's disease and synucleinopathy. Although a direct link between neuropathology and causative candidates has not been clearly established in many cases, the contribution of ncRNAs to the molecular processes leading to cellular dysfunction observed in neurodegenerative diseases has been addressed, suggesting that they may play a role in the pathophysiology of these diseases. Aim of the present Review is to overview and discuss recent literature focused on the role of RNA-based mechanisms involved in different aspects of neuronal pathology in Parkinson's disease and synucleinopathy models.

Differential methylation analysis in neuropathologically confirmed dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a common form of dementia in the elderly population. We performed genome-wide DNA methylation mapping of cerebellar tissue from pathologically confirmed DLB cases and controls to study the epigenetic profile of this understudied disease. After quality control filtering, 728,197 CpG-sites in 278 cases and 172 controls were available for the analysis. We undertook an epigenome-wide association study, which found a differential methylation signature in DLB cases. Our analysis identified seven differentially methylated probes and three regions associated with DLB. The most significant CpGs were located in ARSB (cg16086807), LINC00173 (cg18800161), and MGRN1 (cg16250093). Functional enrichment evaluations found widespread epigenetic dysregulation in genes associated with neuron-to-neuron synapse, postsynaptic specialization, postsynaptic density, and CTCF-mediated synaptic plasticity. In conclusion, our study highlights the potential importance of epigenetic alterations in the pathogenesis of DLB and provides insights into the modified genes, regions and pathways that may guide therapeutic developments.

Gut microbiota, circulating cytokines and dementia: a Mendelian randomization study

BACKGROUND

Some studies have shown that gut microbiota may be associated with dementia. However, the causal effects between gut microbiota and different types of dementia and whether cytokines act as a mediator remain unclear.

METHODS

Gut microbiota, cytokines, and five dementia types, including Alzheimer's disease (AD), frontotemporal dementia (FTD), dementia with Lewy body (DLB), vascular dementia (VD), and Parkinson's disease dementia (PDD) were identified from large-scale genome-wide association studies (GWAS) summary data. We used Mendelian randomization (MR) to investigate the causal relationships between gut microbiota, cytokines, and five types of dementia. Inverse variance weighting (IVW) was used as the main statistical method. In addition, we explored whether cytokines act as a mediating factor in the pathway from gut microbiota to dementia.

RESULTS

There were 20 positive and 16 negative causal effects between genetic liability in the gut microbiota and dementia. Also, there were five positive and four negative causal effects between cytokines and dementias. Cytokines did not act as mediating factors.

CONCLUSIONS

Gut microbiota and cytokines were causally associated with five types of dementia, and cytokines seemed not to be the mediating factors in the pathway from gut microbiota to dementia.

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer's disease: a cross-sectional metabolomic analysis

Background

In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis.

Methods

A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data.

Results

The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809-0.996; sensitivity = 0.90; specificity = 0.90).

Discussion

Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases

Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Cardiac noradrenergic deficiency revealed by 18F-dopamine positron emission tomography identifies preclinical central Lewy body diseases

BACKGROUND

In Lewy body diseases (LBDs) Parkinson disease (PD), and dementia with Lewy bodies (DLB), by the time parkinsonism or cognitive dysfunction manifests clinically, substantial neurodegeneration has already occurred. Biomarkers are needed to identify central LBDs in a preclinical phase, when neurorescue strategies might forestall symptomatic disease. This phase may involve catecholamine deficiency in the autonomic nervous system. We analyzed data from the prospective, observational, long-term PDRisk study to assess the predictive value of low versus normal cardiac 18F-dopamine positron emission tomography (PET), an index of myocardial content of the sympathetic neurotransmitter norepinephrine, in at-risk individuals.

METHODS

Participants self-reported risk factor information (genetics, olfactory dysfunction, dream enactment behavior, and orthostatic intolerance or hypotension) at a protocol-specific website. Thirty-four with 3 or more confirmed risk factors underwent serial cardiac 18F-dopamine PET at 1.5-year intervals for up to 7.5 years or until PD was diagnosed.

RESULTS

Nine participants had low initial myocardial 18F-dopamine-derived radioactivity (<6,000 nCi-kg/cc-mCi) and 25 had normal radioactivity. At 7 years of follow-up, 8 of 9 with low initial radioactivity and 1 of 11 with normal radioactivity were diagnosed with a central LBD (LBD+) (P = 0.0009 by Fisher's exact test). Conversely, all 9 LBD+ participants had low 18F-dopamine-derived radioactivity before or at the time of diagnosis of a central LBD, whereas among 25 participants without a central LBD only 1 (4%) had persistently low radioactivity (P < 0.0001 by Fisher's exact test).

CONCLUSION

Cardiac 18F-dopamine PET highly efficiently distinguishes at-risk individuals who are diagnosed subsequently with a central LBD from those who are not.

TRIAL REGISTRATION

CLINICALTRIALS

gov NCT00775853.

FUNDING

Division of Intramural Research, NIH, NINDS.

Interpretation of Neurodegenerative GWAS Risk Alleles in Microglia and their Interplay with Other Cell Types

Microglia have been implicated in numerous neurodegenerative and neuroinflammatory disorders; however, the causal contribution of this immune cell type is frequently debated. Genetic studies offer a unique vantage point in that they infer causality over a secondary consequence. Genome-wide association studies (GWASs) have identified hundreds of loci in the genome that are associated with susceptibility to neurodegenerative disorders. GWAS studies implicate microglia in the pathogenesis of Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and to a lesser degree suggest a role for microglia in vascular dementia (VaD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS), and other neurodegenerative and neuropsychiatric disorders. The contribution and function of GWAS risk loci on disease progression is an ongoing field of study, in which large genomic datasets, and an extensive framework of computational tools, have proven to be crucial. Several GWAS risk loci are shared between disorders, pointing towards common pleiotropic mechanisms. In this chapter, we introduce key concepts in GWAS and post-GWAS interpretation of neurodegenerative disorders, with a focus on GWAS risk genes implicated in microglia, their interplay with other cell types and shared convergence of GWAS risk loci on microglia.

Potential Biomarkers in Cerebrospinal Fluid and Plasma for Dementia

Background

The identification of biomarkers for different dementias in plasma and cerebrospinal fluid (CSF) has made substantial progress. However, they are observational studies, and there remains a lack of research on dementias with low incidence rates.

Objective

We performed a comprehensive Mendelian randomization to identify potential biomarkers for different dementia type.

Methods

The summary-level datasets encompassed 734 plasma and 154 cerebrospinal fluid proteins sourced from recently published genome-wide association studies (GWAS). Summary statistics for different dementias, including any dementia (refering to any type of dementia symptoms, 218,792 samples), Alzheimer's disease (AD, 63,926 samples), vascular dementia (212,389 samples), frontotemporal dementia (3,024 samples), dementia with Lewy bodies (DLB, 6,618 samples), and dementia in Parkinson's disease (216,895 samples), were collected from large GWAS. The primary method is inverse variance weighting, with additional sensitivity analyses conducted to ensure the robustness of the findings.

Results

The molecules released into CSF, namely APOE2 for any dementia, APOE2 and Siglec-3 for AD, APOE2 for vascular dementia, and APOE2 for DLB, might be potential biomarkers. CD33 for AD and SNCA for DLB in plasma could be promising biomarkers.

Conclusions

This is the first study to integrate plasma and CSF proteins to identify potential biomarkers for different dementias.

Undetected Association Between Fatty Acids and Dementia with Lewy Bodies: A Bidirectional Two-Sample Mendelian Randomization Study

Background

Although observational studies indicated connections between fatty acids (FAs) and Alzheimer's disease and dementia, uncertainty persists regarding how these relationships extend to dementia with Lewy bodies (DLB).

Objective

To explore the potential causal relationships between FAs and the development of DLB, thus clarifying these associations using genetic instruments to infer causality.

Methods

We applied a two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) approach. Genetic data were obtained from a DLB cohort, comprising 2,591 cases and 4,027 controls of European descent. Eight FAs, including linoleic acid, docosahexaenoic acid, monounsaturated fatty acid, omega-3 fatty acid, omega-6 fatty acid, polyunsaturated fatty acid, saturated fatty acid, and total fatty acid, were procured from a comprehensive GWAS of metabolic biomarkers of UK Biobank, conducted by Nightingale Health in 2020 (met-d), involving 114,999 individuals. Our analysis included inverse-variance weighted, MR-Egger, weighted-median, simple mode, and weighted-mode MR estimates. Cochran's Q-statistics, MR-PRESSO, and MR-Egger intercept test were used to quantify the heterogeneity and horizontal pleiotropy of instrumental variables.

Results

Only linoleic acid showed a significant genetic association with the risk of developing DLB in the univariate MR. The odds ratio for linoleic acid was 1.337 with a 95% confidence interval of 1.019-1.756 (pIVW = 0.036). Results from the MVMR showed that no FAs were associated with the incidence of DLB.

Conclusions

The results did not support the hypothesis that FAs could reduce the risk of developing DLB. However, elucidating the relationship between FAs and DLB risk holds potential implications for informing dietary recommendations and therapeutic approaches in DLB.

Mendelian Randomization Analysis to Assess Whether Magnetic Resonance Imaging Signs of Cerebral Small Vessel Disease Can Cause Cognitive Decline and Dementia

OBJECTIVE

Cognitive decline and dementia have been linked to cerebral small vessel disease, so we explored using Mendelian randomization whether cerebral small vessel disease visible as 10 neuroimaging signs may cause cognitive decline and dementia.

METHODS

We analyzed publicly available data from genome-wide association studies using two-sample Mendelian randomization involving inverse variance weighting, weighted median, MR-Egger, and MR-PRESSO approaches.

RESULTS

Mendelian randomization suggested that cognitive decline can be caused by lacunar stroke (inverse variance weighting, β = -0.012, 95% CI -0.024 to -0.001, P = 0.033). Furthermore, an elevated burden of white matter hyperintensities was associated with an increased risk of Dementia due to Parkinson's disease (inverse variance weighting, OR 2.035, 95% CI 1.105 to 3.745, P = 0.023). Notably, no significant associations were observed between neuroimaging markers of Cerebral Small Vessel Disease and other types of dementia.

CONCLUSION

This Mendelian randomization study provides evidence that lacunar stroke and white matter lesions can cause cognitive decline, and that white matter hyperintensity may increase risk of dementia due to Parkinson's disease. These results underscore the need for further investigations into the neurocognitive effects of cerebral small vessel disease.

Causal Association Between Sepsis and Neurodegenerative Diseases: A Bidirectional Two-Sample Mendelian Randomization Study

BACKGROUND

Previous observational studies suggested an association between sepsis and neurodegenerative diseases, but causality remains unclear.

OBJECTIVE

Determining the causal association between sepsis and four neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Lewy body dementia) through bidirectional two-sample Mendelian randomization (MR) analysis.

METHODS

Genome-wide association study summary statistics for all traits were obtained from publicly available databases. Inverse variance weighted (IVW) was the primary method for evaluating causal associations. In addition, three additional MR methods (MR-Egger, weighted median, and maximum likelihood method) were employed to supplement IVW. Furthermore, various sensitivity tests were conducted to assess the reliability: 1) Cochrane's Q test for assessing heterogeneity; 2) MR-Egger intercept test and MR-PRESSO global test for evaluating horizontal pleiotropy; 3) leave-one-out sensitivity test for determining the stability.

RESULTS

The results of IVW indicated that sepsis significantly increased the risk of Alzheimer's disease (OR = 1.11, 95% CI: 1.01-1.21, p = 0.025). In addition, three additional MR methods suggested parallel results. However, no causal effect of sepsis on the three other neurodegenerative diseases was identified. Subsequently, reverse MR analysis indicated that the four neurodegenerative diseases do not causally affect sepsis. Furthermore, sensitivity tests demonstrated the reliability of the MR analyses, suggesting no heterogeneity or horizontal pleiotropy.

CONCLUSIONS

The present study contributes to a deeper comprehension of the intricate interplay between sepsis and neurodegenerative disorders, thereby offering potential avenues for the development of therapeutic agents that can effectively mitigate the multifarious complications associated with sepsis.

Under-Diagnosis of Dementia with Lewy Bodies in Individuals Racialized as Black: Hypotheses Regarding Potential Contributors

Dementia with Lewy bodies (DLB) is one of the most common degenerative dementias after Alzheimer's disease (AD) dementia. DLB is under-diagnosed across populations but may be particularly missed in older Black adults. The object of this review was to examine key features of DLB and potential associations with race in order to hypothesize why DLB may be under-diagnosed in Black adults in the U.S. In terms of dementia, symptoms associated with high rates of co-pathology (e.g., AD, vascular disease) in older Black adults may obscure the clinical picture that might suggest Lewy body pathology. Research also suggests that clinicians may be predisposed to give AD dementia diagnoses to Black adults, potentially missing contributions of Lewy body pathology. Hallucinations in Black adults may be misattributed to AD or primary psychiatric disease rather than Lewy body pathology. Research on the prevalence of REM sleep behavior in diverse populations is lacking, but REM sleep behavior disorder could be under-diagnosed in Black adults due to sleep patterns or reporting by caregivers who are not bed partners. Recognition of parkinsonism could be reduced in Black adults due to clinician biases, cultural effects on self-report, and potentially underlying differences in the frequency of parkinsonism. These considerations are superimposed on structural and systemic contributions to health (e.g., socioeconomic status, education, structural racism) and individual-level social exposures (e.g., social interactions, discrimination). Improving DLB recognition in Black adults will require research to investigate reasons for diagnostic disparities and education to increase identification of core symptoms in this population.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

Association of cardiovascular disease management drugs with Lewy body dementia: a case-control study

Lewy body dementia is the second most common neurodegenerative dementia after Alzheimer's disease. Disease-modifying therapies for this disabling neuropsychiatric condition are critically needed. To identify drugs associated with the risk of developing Lewy body dementia, we performed a population-based case-control study of 148 170 US Medicare participants diagnosed with Lewy body dementia between 1 January 2008 and 31 December 2014 and of 1 253 043 frequency-matched controls. We estimated odds ratios and 95% confidence intervals for the association of Lewy body dementia risk with 1017 prescription drugs overall and separately for the three major racial groups (Black, Hispanic and White Americans). We identified significantly reduced Lewy body dementia risk associated with drugs used to treat cardiovascular diseases (anti-hypertensives: odds ratio = 0.72, 95% confidence interval = 0.70-0.74, P-value = 0; cholesterol-lowering agents: odds ratio = 0.85, 95% confidence interval = 0.83-0.87, P-value = 0; anti-diabetics: odds ratio = 0.83, 95% confidence interval = 0.62-0.72, P-value = 0). Notably, anti-diabetic medications were associated with a larger risk reduction among Black Lewy body dementia patients compared with other racial groups (Black: odds ratio = 0.67, 95% confidence interval = 0.62-0.72, P-value = 0; Hispanic: odds ratio = 0.86, 95% = 0.80-0.92, P-value = 5.16 × 10-5; White: odds ratio = 0.85, 95% confidence interval = 0.82-0.88, P-value = 0). To independently confirm the epidemiological findings, we looked for evidence of genetic overlap between Lewy body dementia and cardiovascular traits using whole-genome sequence data generated for 2591 Lewy body dementia patients and 4027 controls. Bivariate mixed modelling identified shared genetic risk between Lewy body dementia and low-density lipoprotein cholesterol levels, Type 2 diabetes and hypertension. By combining epidemiological and genomic data, we demonstrated that drugs treating cardiovascular diseases are associated with reduced Lewy body dementia risk, and these associations varied across racial groups. Future randomized clinical trials need to confirm our findings, but our data suggest that assiduous management of cardiovascular diseases may be beneficial in this understudied form of dementia.

Causal associations between common musculoskeletal disorders and dementia: a Mendelian randomization study

Introduction

Dementia and musculoskeletal disorders (MSDs) are major public health problems. We aimed to investigate the genetic causality of common MSDs and dementia.

Methods

Two-sample Mendelian randomization (MR) was used in this study. MR analysis based on gene-wide association study (GWAS) data on osteoarthritis (OA), dementia with Lewy bodies, and other MSDs and dementia types were obtained from the Genetics of Osteoarthritis consortium, IEU-open GWAS project, GWAS catalog, and FinnGen consortium. Rigorously selected single-nucleotide polymorphisms were regarded as instrumental variables for further MR analysis. Inverse-variance weighted, MR-Egger regression, weight median, simple mode, and weight mode methods were used to obtain the MR estimates. Cochran's Q test, MR-Egger and MR-Pleiotropy Residual Sum and Outlier analysis, and the leave-one-out test were applied for sensitivity testing.

Results

The inverse-variance weighted method showed that hip OA was genetically associated with a lower risk of dementia, unspecified dementia, dementia in Alzheimer's disease, and vascular dementia. Kneehip OA was inversely associated with unspecified dementia and vascular dementia. Rheumatoid arthritis, juvenile idiopathic arthritis and seronegative rheumatoid arthritis were inversely associated with frontotemporal dementia, and rheumatoid arthritis was inversely associated with unspecified dementia. Simultaneously, ankylosing spondylitis was an independent risk factor for dementia, dementia with Lewy bodies, and dementia in Alzheimer's disease. Sensitivity tests showed that heterogeneity and horizontal pleiotropy did not exist in these associations. The leave-one-out test showed that these associations were stable.

Conclusion

We found that some MSDs were associated with the risk of dementia and provide evidence for the early detection of dementia in patients with MSDs and for the impact of inflammation on the central nervous system.

The non-specific lethal complex regulates genes and pathways genetically linked to Parkinson's disease

Genetic variants conferring risks for Parkinson's disease have been highlighted through genome-wide association studies, yet exploration of their specific disease mechanisms is lacking. Two Parkinson's disease candidate genes, KAT8 and KANSL1, identified through genome-wide studies and a PINK1-mitophagy screen, encode part of the histone acetylating non-specific lethal complex. This complex localizes to the nucleus, where it plays a role in transcriptional activation, and to mitochondria, where it has been suggested to have a role in mitochondrial transcription. In this study, we sought to identify whether the non-specific lethal complex has potential regulatory relationships with other genes associated with Parkinson's disease in human brain. Correlation in the expression of non-specific lethal genes and Parkinson's disease-associated genes was investigated in primary gene co-expression networks using publicly-available transcriptomic data from multiple brain regions (provided by the Genotype-Tissue Expression Consortium and UK Brain Expression Consortium), whilst secondary networks were used to examine cell type specificity. Reverse engineering of gene regulatory networks generated regulons of the complex, which were tested for heritability using stratified linkage disequilibrium score regression. Prioritized gene targets were then validated in vitro using a QuantiGene multiplex assay and publicly-available chromatin immunoprecipitation-sequencing data. Significant clustering of non-specific lethal genes was revealed alongside Parkinson's disease-associated genes in frontal cortex primary co-expression modules, amongst other brain regions. Both primary and secondary co-expression modules containing these genes were enriched for mainly neuronal cell types. Regulons of the complex contained Parkinson's disease-associated genes and were enriched for biological pathways genetically linked to disease. When examined in a neuroblastoma cell line, 41% of prioritized gene targets showed significant changes in mRNA expression following KANSL1 or KAT8 perturbation. KANSL1 and H4K8 chromatin immunoprecipitation-sequencing data demonstrated non-specific lethal complex activity at many of these genes. In conclusion, genes encoding the non-specific lethal complex are highly correlated with and regulate genes associated with Parkinson's disease. Overall, these findings reveal a potentially wider role for this protein complex in regulating genes and pathways implicated in Parkinson's disease.

Cardiac 18F-dopamine positron emission tomography predicts the type of phenoconversion of pure autonomic failure

PURPOSE

Pure autonomic failure (PAF) is a rare disease characterized by neurogenic orthostatic hypotension (nOH), no known secondary cause, and lack of a neurodegenerative movement or cognitive disorder. Clinically diagnosed PAF can evolve ("phenoconvert") to a central Lewy body disease [LBD, e.g., Parkinson's disease (PD) or dementia with Lewy bodies (DLB)] or to the non-LBD synucleinopathy multiple system atrophy (MSA). Since cardiac 18F-dopamine-derived radioactivity usually is low in LBDs and usually is normal in MSA, we hypothesized that patients with PAF with low cardiac 18F-dopamine-derived radioactivity would be more likely to phenoconvert to a central LBD than to MSA.

METHODS

We reviewed data from all the patients seen at the National Institutes of Health Clinical Center from 1994 to 2023 with a clinical diagnosis of PAF and data about 18F-dopamine positron emission tomography (PET).

RESULTS

Nineteen patients (15 with low 18F-dopamine-derived radioactivity, 4 with normal radioactivity) met the above criteria and had follow-up data. Nine (47%) phenoconverted to a central synucleinopathy over a mean of 6.6 years (range 1.5-18.8 years). All 6 patients with low cardiac 18F-dopamine-derived radioactivity who phenoconverted during follow-up developed a central LBD, whereas none of 4 patients with consistently normal 18F-dopamine PET phenoconverted to a central LBD (p = 0.0048), 3 evolving to probable MSA and 1 upon autopsy having neither a LBD nor MSA.

CONCLUSION

Cardiac 18F-dopamine PET can predict the type of phenoconversion of PAF. This capability could refine eligibility criteria for entry into disease-modification trials aimed at preventing evolution of PAF to symptomatic central LBDs.

Artificial intelligence for dementia genetics and omics

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.

Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis

BACKGROUND

Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis.

METHODS

The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined.

RESULTS

A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts.

CONCLUSION

The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.

A two-sample Mendelian randomization study of atherosclerosis and dementia

The causality between atherosclerosis and dementia remains unclear. This study aimed to explore the causal effect of atherosclerosis related indicators on dementia risk based on two-sample Mendelian randomization (MR) using summary statistics of genome-wide association studies (GWASs). The inverse variance weighted (IVW) method was performed as the main analysis, supplemented by different sensitivity analyses. Suggestive evidence indicated that peripheral arterial disease (PAD) (odds ratio (OR): 0.864, 95% confidence interval (CI): 0.797-0.937), coronary atherosclerosis (CoAS) (OR: 0.927, 95% CI: 0.860-0.998) and atherosclerosis, excluding cerebral, coronary, and PAD (ATHSCLE) (OR: 0.812, 95% CI: 0.725-0.909) were inversely associated with the risk of AD. The sensitivity analysis confirmed a suggestive reverse effect of ATHSCLE on the risk of frontotemporal dementia (FTD) (OR, 0.812, 95% CI, 0.725-0.909). Findings provide suggestive evidence that PAD, CoAS, and ATHSCLE might be associated with the risk of AD or FTD, which requires further exploration in larger samples.

Human brain single nucleus cell type enrichments in neurodegenerative diseases

Background

Single-cell RNA sequencing has opened a window into clarifying the complex underpinnings of disease, particularly in quantifying the relevance of tissue- and cell-type-specific gene expression.

Methods

To identify the cell types and genes important to therapeutic target development across the neurodegenerative disease spectrum, we leveraged genome-wide association studies, recent single-cell sequencing data, and bulk expression studies in a diverse series of brain region tissues.

Results

We were able to identify significant immune-related cell types in the brain across three major neurodegenerative diseases: Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. Subsequently, putative roles of 30 fine-mapped loci implicating seven genes in multiple neurodegenerative diseases and their pathogenesis were identified.

Conclusions

We have helped refine the genetic regions and cell types effected across multiple neurodegenerative diseases, helping focus future translational research efforts.

Clinical biomarkers for Lewy body diseases

Synucleinopathies are a group of neurodegenerative disorders characterized by pathologic aggregates of neural and glial α-synuclein (α-syn) in the form of Lewy bodies (LBs), Lewy neurites, and cytoplasmic inclusions in both neurons and glia. Two major classes of synucleinopathies are LB disease and multiple system atrophy. LB diseases include Parkinson's disease (PD), PD with dementia, and dementia with LBs. All are increasing in prevalence. Effective diagnostics, disease-modifying therapies, and therapeutic monitoring are urgently needed. Diagnostics capable of differentiating LB diseases are based on signs and symptoms which might overlap. To date, no specific diagnostic test exists despite disease-specific pathologies. Diagnostics are aided by brain imaging and cerebrospinal fluid evaluations, but more accessible biomarkers remain in need. Mechanisms of α-syn evolution to pathologic oligomers and insoluble fibrils can provide one of a spectrum of biomarkers to link complex neural pathways to effective therapies. With these in mind, we review promising biomarkers linked to effective disease-modifying interventions.

Exploring shared features in neurodegenerative diseases

This scientific commentary refers to ‘Genetic risk factor clustering within and across neurodegenerative diseases’ by Koretsky et al. (https://doi.org/10.1093/brain/awad161).

Genetic risk factor clustering within and across neurodegenerative diseases

Overlapping symptoms and co-pathologies are common in closely related neurodegenerative diseases (NDDs). Investigating genetic risk variants across these NDDs can give further insight into disease manifestations. In this study we have leveraged genome-wide single nucleotide polymorphisms and genome-wide association study summary statistics to cluster patients based on their genetic status across identified risk variants for five NDDs (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Lewy body dementia and frontotemporal dementia). The multi-disease and disease-specific clustering results presented here provide evidence that NDDs have more overlapping genetic aetiology than previously expected and how neurodegeneration should be viewed as a spectrum of symptomology. These clustering analyses also show potential subsets of patients with these diseases that are significantly depleted for any known common genetic risk factors suggesting environmental or other factors at work. Establishing that NDDs with overlapping pathologies share genetic risk loci, future research into how these variants might have different effects on downstream protein expression, pathology and NDD manifestation in general is important for refining and treating NDDs.

Relationship of Klotho with cognition and dementia: Results from the NHANES 2011-2014 and Mendelian randomization study

The relationships of Klotho levels with cognition and dementia are poorly understood. This study aimed to investigate the association between Klotho levels and cognitive function and to determine causality between Klotho and dementia using Mendelian randomization (MR). Based on data from the National Health and Nutrition Survey (NHANES) 2011-2014, this study consisted of 1875 older adults aged 60-79 years. Cognitive function was assessed by the digit symbol substitution test (DSST). We performed weighted multivariable-adjusted linear regression to assess the association between Klotho concentrations and cognitive function. Then, 2-sample MR was conducted to assess the causal relationship between Klotho and dementia. The inverse variance weighted (IVW) method was used as the primary analysis. We observed a positive association between serum Klotho concentrations and the results of the Digit Symbol Substitution test (DSST) (T2: β 2.16, 95% CI: 0.30-4.01, P = 0.03, T3: β 2.48, 95% CI: 0.38-4.57, P = 0.02) after adjusting for the covariates. Moreover, there was also a potential nonlinear relationship between Klotho and DSST. The IVW method showed that genetically predicted high Klotho levels were not significantly associate with any type of dementia, including Alzheimer's disease (OR = 1.03, 95% CI: 0.96-1.10, P = 0.46), vascular dementia (OR = 1.04, 95% CI: 0.87-1.25, P = 0.66), frontotemporal dementia (OR = 0.73, 95% CI: 0.47-1.14, P = 0.16), or dementia with Lewy bodies (OR = 1.03, 95% CI: 0.87-1.23, P = 0.73). In the cross-sectional observational study, Klotho and cognitive function were significantly correlated; however, findings from MR studies did not indicate a causal relationship between Klotho and dementia.

Elucidating distinct molecular signatures of Lewy body dementias

Dementia with Lewy bodies and Parkinson's disease dementia are common neurodegenerative diseases that share similar neuropathological profiles and spectra of clinical symptoms but are primarily differentiated by the order in which symptoms manifest. The question of whether a distinct molecular pathological profile could distinguish these disorders is yet to be answered. However, in recent years, studies have begun to investigate genomic, epigenomic, transcriptomic and proteomic differences that may differentiate these disorders, providing novel insights in to disease etiology. In this review, we present an overview of the clinical and pathological hallmarks of Lewy body dementias before summarizing relevant research into genetic, epigenetic, transcriptional and protein signatures in these diseases, with a particular interest in those resolving "omic" level changes. We conclude by suggesting future research directions to address current gaps and questions present within the field.

Investigation of the genetic aetiology of Lewy body diseases with and without dementia

Up to 80% of Parkinson's disease patients develop dementia, but time to dementia varies widely from motor symptom onset. Dementia with Lewy bodies presents with clinical features similar to Parkinson's disease dementia, but cognitive impairment precedes or coincides with motor onset. It remains controversial whether dementia with Lewy bodies and Parkinson's disease dementia are distinct conditions or represent part of a disease spectrum. The biological mechanisms underlying disease heterogeneity, in particular the development of dementia, remain poorly understood, but will likely be key to understanding disease pathways and ultimately therapy development. Previous genome-wide association studies in Parkinson's disease and dementia with Lewy bodies/Parkinson's disease dementia have identified risk loci differentiating patients from controls. We collated data for 7,804 patients of European ancestry from Tracking Parkinson's (PRoBaND), The Oxford Discovery Cohort, and AMP-PD. We conducted a discrete phenotype genome-wide association studies comparing Lewy body diseases with and without dementia to decode disease heterogeneity by investigating the genetic drivers of dementia in Lewy body diseases. We found that risk alleles rs429358 tagging APOEe4 and rs7668531 near the MMRN1 and SNCA-AS1 genes, increase the odds of developing dementia and that an intronic variant rs17442721 tagging LRRK2 G2019S, on chromosome 12 is protective against dementia. These results should be validated in autopsy confirmed cases in future studies.

Pervasive biases in proxy GWAS based on parental history of Alzheimer's disease

Almost every recent Alzheimer's disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and non-random participation of parental illness survey, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that current AD GWAX provide highly misleading genetic correlations between AD risk and higher education which subsequently affects a variety of genetic epidemiologic applications involving AD and cognition. Our study sheds important light on the design and analysis of mid-aged biobank cohorts and underscores the need for caution when interpreting genetic association results based on proxy-reported parental disease history.

Genome-wide association study identifies APOE and ZMIZ1 variants as mitophagy modifiers in Lewy body disease

The PINK1-PRKN pathway mediates a critical quality control to maintain mitochondrial health and function. Together the kinase-ligase pair identifies and decorate damaged mitochondria with phosphorylated ubiquitin (p-S65-Ub). This selective label serves as the mitophagy tag and facilitates their degradation via autophagy-lysosome system. While complete loss of PINK1 or PRKN function causes early-onset Parkinson disease, much broader mitophagy impairments are emerging across neurodegenerative disorders. We previously found age- and disease-dependent accumulation of p-S65-Ub signal in the hippocampus of autopsy brains with Lewy body disease (LBD). However, the contribution of genetic variation to mitochondrial damage and p-S65-Ub levels remains unknown in LBD cases. To identify novel regulators of PINK1-PRKN mitophagy in LBD, we performed an unbiased genome-wide association study of hippocampal p-S65-Ub level with 1,012 autopsy confirmed LBD samples. Using an established, mostly automated workflow, hippocampal sections were immunostained for p-S65-Ub, scanned, and quantified with unbiased algorithms. Functional validation of the significant hit was performed in animal model and human induced pluripotent stem cells (hiPSCs). We identified a strong association with p-S65-Ub for APOE4 (rs429358; β : 0.50, 95% CI: 0.41 to 0.69; p =8.67x10 -25 ) and a genome-wide significant association for ZMIZ1 (rs6480922; β : -0.33, 95% CI: -0.45 to -0.22; p =1.42x10 -8 ). The increased p-S65-Ub levels in APOE4 -carrier may be mediated by both co-pathology-dependent and -independent mechanisms, which was confirmed in Apoe-targeted replacement mice and hiPSC-derived astrocytes. Intriguingly, ZMIZ1 rs6480922 also significantly associated with increased brain weight and reduced neuropathological burden indicating a potential role as a resilience factor. Our findings nominate novel mitophagy regulators in LBD brain ( ZMIZ1 locus) and highlight a strong association of APOE4 with mitophagy alteration. With APOE4 being the strongest known risk factor for clinical Alzheimer's disease and dementia with Lewy bodies, our findings suggest a common mechanistic link underscoring the importance of mitochondrial quality control.

Overlapping Neuroimmune Mechanisms and Therapeutic Targets in Neurodegenerative Disorders

Many potential immune therapeutic targets are similarly affected in adult-onset neurodegenerative diseases, such as Alzheimer's (AD) disease, Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD), as well as in a seemingly distinct Niemann-Pick type C disease with primarily juvenile onset. This strongly argues for an overlap in pathogenic mechanisms. The commonly researched immune targets include various immune cell subsets, such as microglia, peripheral macrophages, and regulatory T cells (Tregs); the complement system; and other soluble factors. In this review, we compare these neurodegenerative diseases from a clinical point of view and highlight common pathways and mechanisms of protein aggregation, neurodegeneration, and/or neuroinflammation that could potentially lead to shared treatment strategies for overlapping immune dysfunctions in these diseases. These approaches include but are not limited to immunisation, complement cascade blockade, microbiome regulation, inhibition of signal transduction, Treg boosting, and stem cell transplantation.

Lysosomal polygenic risk is associated with the severity of neuropathology in Lewy body disease

Intraneuronal accumulation of misfolded α-synuclein is the pathological hallmark of Parkinson's disease and dementia with Lewy bodies, often co-occurring with variable degrees of Alzheimer's disease related neuropathology. Genetic association studies have successfully identified common variants associated with disease risk and phenotypic traits in Lewy body disease, yet little is known about the genetic contribution to neuropathological heterogeneity. Using summary statistics from Parkinson's disease and Alzheimer's disease genome-wide association studies, we calculated polygenic risk scores and investigated the relationship with Lewy, amyloid-β and tau pathology. Associations were nominated in neuropathologically defined samples with Lewy body disease from the Netherlands Brain Bank (n = 217) and followed up in an independent sample series from the Mayo Clinic Brain Bank (n = 394). We also generated stratified polygenic risk scores based on single-nucleotide polymorphisms annotated to eight functional pathways or cell types previously implicated in Parkinson's disease and assessed for association with Lewy pathology in subgroups with and without significant Alzheimer's disease co-pathology. In an ordinal logistic regression model, the Alzheimer's disease polygenic risk score was associated with concomitant amyloid-β and tau pathology in both cohorts. Moreover, both cohorts showed a significant association between lysosomal pathway polygenic risk and Lewy pathology, which was more consistent than the association with a general Parkinson's disease risk score and specific to the subset of samples without significant concomitant Alzheimer's disease related neuropathology. Our findings provide proof of principle that the specific risk alleles a patient carries for Parkinson's and Alzheimer's disease also influence key aspects of the underlying neuropathology in Lewy body disease. The interrelations between genetic architecture and neuropathology are complex, as our results implicate lysosomal risk loci specifically in the subset of samples without Alzheimer's disease co-pathology. Our findings hold promise that genetic profiling may help predict the vulnerability to specific neuropathologies in Lewy body disease, with potential relevance for the further development of precision medicine in these disorders.

Chronic Pain, Analgesics, and Cognitive Status: A Comprehensive Mendelian Randomization Study

BACKGROUND

Observational studies have suggested an intricate relationship among chronic pain (CP), use of analgesics, and cognitive status, but it remains unclear whether these associations are of a causal nature.

METHODS

To investigate the causal relationship among them, summary statistics of 9 types of CP (headache, hip, neck/shoulder, stomach/abdominal, back, knee, facial, general, and multisite CP), analgesics (nonsteroidal anti-inflammatory drugs [NSAIDs], opioids, salicylic acid and derivatives, and anilides), and cognitive status (cognitive function, Alzheimer's disease [AD], vascular dementia, Lewy body dementia [LBD], and dementia) were included in this Mendelian randomization (MR) study. As both CP and analgesic use were associated with cognitive status and vice versa, we performed a bidirectional MR analysis between CP or analgesics and dementia using strong genetic instruments ( P < .001) identified from genome-wide association studies (GWAS). The inverse-variance weighted method was applied to calculate estimates. The MR estimated odds ratio (OR) was interpreted as odds of outcome per unit increase in the exposure. The Benjamini-Hochberg method was applied to adjust the P value for multiple testing, and P < .05 means statistically significant.

RESULTS

Multisite CP (MCP) was associated with worse cognitive function (OR [95% confidence interval], 0.69 [0.53-0.89], P = .043), but no significant reverse effect of cognitive status on CP was found. There were no significant associations observed between analgesics and cognitive status. Unexpectedly, patients with AD and LBD had significantly lower exposure to anilides (AD: OR = 0.97 [0.94-0.99], P = .034; LBD: OR = 0.97 [0.96-0.99], P = .012) and NSAIDs (AD: OR = 0.96 [0.93-0.98], P = .012; LBD: OR = 0.98 [0.96-0.99], P = .034).

CONCLUSIONS

Our findings indicate that an elevated number of CP sites predict future cognitive decline. Patients with dementia had lower exposure to anilides and NSAIDs, suggesting that they might not be adequately medicated for pain.

Investigation of the causal relationship between osteocalcin and dementia: A Mendelian randomization study

Objective

Basic medical studies have reported an improved effect of osteocalcin on cognition. We explored the causal link between osteocalcin and dementia via the implementation of Mendelian randomization methodology.

Methods

Genome-wide association studies were employed to identify single nucleotide polymorphisms (SNPs) showing significant correlations with osteocalcin. Subsequently, A two-sample Mendelian randomization analysis was conducted utilizing the inverse-variance-weighted (IVW) technique to assess the causal relationship between osteocalcin and various types of dementia, including Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD), and vascular dementia (VD). This approach aimed to minimize potential sources of confounding bias and provide more robust results. Multivariable MR (MVMR) analysis was conducted to adjust for potential genetic pleiotropy.

Results

The study employed three SNPs, namely rs71631868, rs9271374, and rs116843408, as genetic tools to evaluate the causal association of osteocalcin with dementia. The IVW analysis indicated that osteocalcin may have a potential protective effect against AD with an odds ratio (OR) of 0.790 (95 % CI: 0.688-0.906; P < 0.001). However, no significant relationship was observed between osteocalcin and other types of dementia. Furthermore, the MVMR analysis indicated that the impact of osteocalcin on AD remained consistent even after adjusting for age-related macular degeneration and Type 2 diabetes with an OR of 0.856 (95 % CI: 0.744-0.985; P = 0.030).

Conclusions

Our findings provide important insights into the role of osteocalcin in the pathogenesis of AD. Future research is required to clarify the underlying mechanisms and their clinical applications.

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms in vivo , measuring 5,543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n=490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n=487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders, we performed a metabolome-wide association study (MWAS), identifying 40 associations between CSF metabolites and brain traits. Similarly, over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.

The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis

While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.

APOE-ε4 and BIN1 increase risk of Alzheimer's disease pathology but not specifically of Lewy body pathology

Lewy body (LB) pathology commonly occurs in individuals with Alzheimer's disease (AD) pathology. However, it remains unclear which genetic risk factors underlie AD pathology, LB pathology, or AD-LB co-pathology. Notably, whether APOE-ε4 affects risk of LB pathology independently from AD pathology is controversial. We adapted criteria from the literature to classify 4,985 subjects from the National Alzheimer's Coordinating Center (NACC) and the Rush University Medical Center as AD-LB co-pathology (AD+LB+), sole AD pathology (AD+LB-), sole LB pathology (AD-LB+), or no pathology (AD-LB-). We performed a meta-analysis of a genome-wide association study (GWAS) per subpopulation (NACC/Rush) for each disease phenotype compared to the control group (AD-LB-), and compared the AD+LB+ to AD+LB- groups. APOE-ε4 was significantly associated with risk of AD+LB- and AD+LB+ compared to AD-LB-. However, APOE-ε4 was not associated with risk of AD-LB+ compared to AD-LB- or risk of AD+LB+ compared to AD+LB-. Associations at the BIN1 locus exhibited qualitatively similar results. These results suggest that APOE-ε4 is a risk factor for AD pathology, but not for LB pathology when decoupled from AD pathology. The same holds for BIN1 risk variants. These findings, in the largest AD-LB neuropathology GWAS to date, distinguish the genetic risk factors for sole and dual AD-LB pathology phenotypes. Our GWAS meta-analysis summary statistics, derived from phenotypes based on postmortem pathologic evaluation, may provide more accurate disease-specific polygenic risk scores compared to GWAS based on clinical diagnoses, which are likely confounded by undetected dual pathology and clinical misdiagnoses of dementia type.

Multiancestry analysis of the HLA locus in Alzheimer's and Parkinson's diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.