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SummaryAging is a major risk factor for Alzheimer’s disease (AD), and cell-type vulnerability underlies its characteristic clinical manifestations. We have performed longitudinal, single-cell RNA-sequencing inDrosophilawith pan-neuronal expression of human tau, which forms AD neurofibrillary tangle pathology. Whereas tau- and aging-induced gene expression strongly overlap (93%), they differ in the affected cell types. In contrast to the broad impact of aging, tau-triggered changes are strongly polarized to excitatory neurons and glia. Further, tau can either activate or suppress innate immune gene expression signatures in a cell type-specific manner. Integration of cellular abundance and gene expression pinpoints Nuclear Factor Kappa B signaling as a potential marker for neuronal vulnerability. We also highlight the conservation of cell type-specific transcriptional patterns betweenDrosophilaand human postmortem brain tissue. Overall, our results create a resource for dissection of dynamic, age-dependent gene expression changes at cellular resolution in a genetically tractable model of tauopathy.

With the growing availability of Alzheimer’s disease (AD) transcriptomic data, several studies have nominated new therapeutic targets. However, a major challenge is accounting for latent (hidden) factors which affect the discovery of therapeutic targets. Using unsupervised machine learning, we identified a latent factor in brain tissue, and we validated the factor in AD and normal samples, across multiple studies, and different brain tissues. Moreover, significant metabolic differences were observed due to the latent factor. The latent factor was found to reflect cell-type heterogeneity in the brain and after adjusting for it, we were able to identify new biological pathways. The changes observed at both transcriptomic and metabolomic levels support the importance of identifying any latent factors before pursuing downstream analysis to accurately identify biomarkers.

Heterozygous variants in the glucocerebrosidase (GBA) gene are common and potent risk factors for Parkinson’s disease (PD). GBA also causes the autosomal recessive lysosomal storage disorder (LSD), Gaucher disease, and emerging evidence from human genetics implicates many other LSD genes in PD susceptibility. We have systemically tested 88 conserved fly homologs of 38 human LSD genes for requirements in the aging adult Drosophila brain and for potential genetic interactions with neurodegeneration caused by α-synuclein (αSyn), which forms Lewy body pathology in PD. Our screen identifies 15 genetic enhancers of αSyn-induced progressive locomotor dysfunction, following knockdown of fly homologs of GBA and other LSD genes with independent support as PD susceptibility factors from human genetics (SCARB2, SMPD1, CTSD, GNPTAB, SLC17A5). For several genes, results from multiple alleles support dose-sensitivity and context-dependent pleiotropy in the presence or absence of αSyn. Homologs of 2 genes causing cholesterol storage disorders, Npc1a / NPC1 and Lip4 / LIPA, were independently confirmed as loss-of-function enhancers of αSyn-induced brain structural degeneration. The enzymes encoded by several modifier genes are upregulated in αSyn transgenic flies, based on unbiased proteomics, revealing a possible compensatory response. Overall, our results reinforce the important role of lysosomal genes in brain health and PD pathogenesis, and implicate several metabolic pathways, including cholesterol homeostasis, in αSyn-mediated neurodegeneration.

Background and ObjectivesGenetic variants impact both Parkinson’s disease (PD) risk and manifestations. While genetic information is of potential interest to patients and clinicians, genetic testing is rarely performed during routine PD clinical care. The goal of this study was to perform genome sequencing and examine patient interest in comprehensive genetic testing for PD in 2 academic movement disorder clinics.MethodsIn 208 subjects with PD (age=63 years, 67% male), genome sequencing was performed and filtered using a custom panel, including 49 genes associated with PD, parkinsonism, or related disorders, as well as a 90-variant PD genetic risk score. Separately, 231 patients (age=67 years, 63% male) were surveyed on interest in genetic testing at baseline and in response to vignettes covering (i) familial risk of PD (LRRK2); (ii) risk of PD dementia (GBA); (iii) PD genetic risk score; and (iv) secondary, medically-actionable variants (BRCA1).ResultsGenome sequencing revealed a LRRK2 variant in 3.4% and a GBA risk variant in 10.1% of our clinical sample. The genetic risk score was normally distributed, identifying 42 subjects with high risk of PD. Medically-actionable findings were discovered in 2 subjects (1%). In our survey, the majority (82%) responded they would share a LRRK2 variant with relatives. Most registered unchanged or increased interest in testing when confronted with potential risk for dementia or medically- actionable findings, and most (75%) expressed interest in learning their PD genetic risk score.DiscussionOur results highlight broad interest in comprehensive genetic testing among patients with PD and may facilitate integration of genome sequencing in clinical practice.

OBJECTIVETo discover genetic determinants of Parkinson disease (PD) motor subtypes, including Tremor Dominant (TD) and Postural Instability/Gait Difficulty (PIGD) forms.METHODSIn 3,212 PD cases of European ancestry, we performed a genome-wide association study (GWAS) examining two complementary outcome traits derived from the Unified Parkinson’s Disease Rating Scale (UPDRS), including dichotomous motor subtype (TD vs. PIGD) or a continuous tremor / PIGD score ratio. Logistic or linear regression models were adjusted for sex, age of onset, disease duration, and 5 ancestry principal components, followed by meta-analysis.RESULTSAmong 71 established PD risk variants, we detected multiple suggestive associations with PD motor subtype, including GPNMB (rs199347, psubtype = 0.01, pratio = 0.03), SH3GL2 (rs10756907, psubtype = 0.02, pratio = 0.01), HIP1R (rs10847864, psubtype = 0.02), RIT2 (rs12456492, psubtype = 0.02), and FBRSL1 (rs11610045, psubtype = 0.02). A PD genetic risk score integrating all 71 PD risk variants was also associated with subtype ratio (p = 0.026, ß = −0.04, 95% CI = −0.07, 0). Based on top results of our GWAS, we identify a novel suggestive association at the STK32B locus (rs2301857, pratio = 6.6×10−7), which harbors an independent risk allele for essential tremor.CONCLUSIONSMultiple PD risk alleles may also modify clinical manifestations to influence PD motor subtype. The discovery of a novel variant at STK32B suggests a possible overlap between genetic risk for essential tremor and tremor-dominant PD.

One of the defining pathological features of Alzheimer’s Disease (AD) is the deposition of neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau in the brain. Aberrant activation of kinases in AD has been suggested to enhance phosphorylation and toxicity of tau, making the responsible tau-directed kinases attractive therapeutic targets. The full complement of tau interacting kinases in AD brain and their activity in disease remains incompletely defined. Here, immunoaffinity enrichment coupled with mass spectrometry (MS) identified TANK-binding kinase 1 (TBK1) as a tau-interacting partner in human AD cortical brain tissues. We validated this interaction in both human AD and familial frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) caused by mutations inMAPT(R406W) postmortem brain tissues as well as human cell lines. Further, we document increased TBK1 activity in both AD and FTDP-17 and map the predominant TBK1 phosphorylation sites on tau based onin vitrokinase assays coupled to MS. Lastly, in aDrosophilatauopathy model, activating expression of a conserved TBK1 ortholog triggers tau hyperphosphorylation and enhanced neurodegeneration, whereas knockdown had the reciprocal effect, suppressing tau toxicity. Collectively, our findings suggest that increased TBK1 activity may promote tau hyperphosphorylation and neuronal loss in AD and related tauopathies.

BackgroundParkinson’s disease (PD) is a genetically heterogeneous condition; both single nucleotide variants (SNVs) and copy number variants (CNVs) are important genetic risk factors. We examined the utility of combining exome sequencing and genome-wide array-based comparative genomic hybridization (aCGH) for identification of PD genetic risk factors.MethodsWe performed exome sequencing on 110 subjects with PD and a positive family history; 99 subjects were also evaluated using genome-wide aCGH. We interrogated exome sequencing and array comparative genomic hybridization data for pathogenic SNVs and CNVs at Mendelian PD gene loci. SNVs were confirmed via Sanger sequencing. CNVs were confirmed with custom-designed high-density aCGH, droplet digital PCR, and breakpoint sequencing.ResultsUsing exome sequencing, we discovered individuals with known pathogenic single nucleotide variants in GBA (p.E365K, p.T408M, p.N409S, p.L483P) and LRRK2 (p.R1441G and p.G2019S). Two subjects were each double heterozygotes for variants in GBA and LRRK2. Based on aCGH, we additionally discovered cases with an SNCA duplication and heterozygous intragenic GBA deletion. Five additional subjects harbored both SNVs (p.N52fs, p.T240M, p.P437L, p.W453*) and likely disrupting CNVs at the PARK2 locus, consistent with compound heterozygosity. In nearly all cases, breakpoint sequencing revealed microhomology, a mutational signature consistent with CNV formation due to DNA replication errors.ConclusionsIntegrated exome sequencing and aCGH yielded a genetic diagnosis in 19.3% of our familial PD cohort. Our analyses highlight potential mechanisms for SNCA and PARK2 CNV formation, uncover multilocus pathogenic variation, and identify novel SNVs and CNVs for further investigation as potential PD risk alleles.

Our understanding of the biological changes in the brain associated with Alzheimer’s disease (AD) pathology and cognitive impairment remains incomplete. To increase our understanding of these changes, we analyzed dorsolateral prefrontal cortex of control, asymptomatic AD, and AD brains from four different centers by label-free quantitative mass spectrometry and weighted protein co-expression analysis to obtain a consensus protein co-expression network of AD brain. This network consisted of 13 protein co-expression modules. Six of these modules correlated with amyloid-β plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community-based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network. In this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.

Retromer, including Vps35, Vps26, and Vps29, is a protein complex responsible for recycling proteins within the endolysosomal pathway. Although implicated in both Parkinson’s and Alzheimer’s disease, our understanding of retromer function in the adult brain remains limited, in part becauseVps35andVps26are essential for development. InDrosophila, we find thatVps29is dispensable for embryogenesis but required for retromer function in aging adults, including for synaptic transmission, survival, and locomotion. Unexpectedly, inVps29mutants, Vps35 and Vps26 proteins are normally expressed and associated, but retromer is mislocalized from neuropil to soma with the Rab7 GTPase. Further,Vps29phenotypes are suppressed by reducing Rab7 or overexpressing the GTPase activating protein, TBC1D5. With aging, retromer insufficiency triggers progressive endolysosomal dysfunction, with ultrastructural evidence of impaired substrate clearance and lysosomal stress. Our results reveal the role of Vps29 in retromer localization and function, highlighting requirements for brain homeostasis in aging.Impact StatementVps29 promotes retromer localization in the adultDrosophilabrain, engaging Rab7 and TBC1D5, and its loss triggers age-dependent neuronal impairments in endolysosomal trafficking and synaptic transmission.

SUMMARYAlzheimer’s disease (AD) is a complex and heterogenous brain disease that affects multiple inter-related biological processes. This complexity contributes, in part, to existing difficulties in the identification of successful disease-modifying therapeutic strategies. To address this, systems approaches are being used to characterize AD-related disruption in molecular state. To evaluate the consistency across these molecular models, a consensus atlas of the human brain transcriptome was developed through coexpression meta-analysis across the AMP-AD consortium. Consensus analysis was performed across five coexpression methods used to analyze RNA-seq data collected from 2114 samples across 7 brain regions and 3 research studies. From this analysis, five consensus clusters were identified that described the major sources of AD-related alterations in transcriptional state that were consistent across studies, methods, and samples. AD genetic associations, previously studied AD-related biological processes, and AD targets under active investigation were enriched in only three of these five clusters. The remaining two clusters demonstrated strong heterogeneity between males and females in AD-related expression that was consistently observed across studies. AD transcriptional modules identified by systems analysis of individual AMP-AD teams were all represented in one of these five consensus clusters except ROS/MAP-identified Module 109, which was specific for genes that showed the strongest association with changes in AD-related gene expression across consensus clusters. The other two AMP-AD transcriptional analyses reported modules that were enriched in one of the two sex-specific Consensus Clusters. The fifth cluster has not been previously identified and was enriched for genes related to proteostasis. This study provides an atlas to map across biological inquiries of AD with the goal of supporting an expansion in AD target discovery efforts.

SUMMARYHuman brain transcriptomes can highlight biological pathways associated with Alzheimer’s disease (AD); however, challenges remain to link expression changes with causal triggers. We have examined 30 AD-associated, gene coexpression modules from human brains for overlap with 251 differentially-expressed gene sets from mouse brain RNA-sequencing experiments, including from models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus neurofibrillary tangle pathology and further reveal age- and sex-dependent expression signatures for AD progression. Human coexpression modules enriched for neuronal and/or microglial genes overlap broadly with signatures from mouse models of AD, Huntington’s disease, Amyotrophic Lateral Sclerosis, and also aging. Several human AD coexpression modules, including those implicated in the unfolded protein response and oxidative phosphorylation, were not activated in AD models, but instead were detected following other, unexpected mouse genetic manipulations. Our results comprise a powerful, cross-species resource and pinpoint experimental models for diverse features of AD pathophysiology from human brain transcriptomes.

Increasing evidence supports an extensive and complex genetic contribution to Parkinson’s disease (PD). Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age of onset are largely unknown. Here we performed an age of onset GWAS based on 28,568 PD cases. We estimated that the heritability of PD age of onset due to common genetic variation was ~0.11, lower than the overall heritability of risk for PD (~0.27) likely in part because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni corrected significant effect at other known PD risk loci, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. In addition, we identified that GBA coding variant carriers had an earlier age of onset compared to non-carriers. Notably, SNCA, TMEM175, SCARB2, BAG3 and GBA have all been shown to either directly influence alpha-synuclein aggregation or are implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci such as GCH1, MAPT and RAB7L1/NUCKS1 (PARK16) did not show a significant effect on age of onset of PD. While for some loci, this may be a measure of power, this is clearly not the case for the MAPT locus; thus genetic variability at this locus influences whether but not when an individual develops disease. We believe this is an important mechanistic and therapeutic distinction. Furthermore, these data support a model in which alpha-synuclein and lysosomal mechanisms impact not only PD risk but also age of disease onset and highlights that therapies that target alpha-synuclein aggregation are more likely to be disease-modifying than therapies targeting other pathways.

We performed the largest genome-wide association study of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases, and 1.4M controls. We identified 90 independent genome-wide significant signals across 78 loci, including 38 independent risk signals in 37 novel loci. These variants explained 26-36% of the heritable risk of PD. Tests of causality within a Mendelian randomization framework identified putatively causal genes for 70 risk signals. Tissue expression enrichment analysis suggested that signatures of PD loci were heavily brain-enriched, consistent with specific neuronal cell types being implicated from single cell expression data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. In sum, these data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

Subcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.