Pleiotropic Effects of Variants in Dementia Genes in Parkinson Disease

Brain metabolic signatures in patients with genetic and nongenetic amyotrophic lateral sclerosis

AIMS

To study the brain metabolic signature in Chinese amyotrophic lateral sclerosis (ALS) patients and compare the difference in brain metabolic patterns between ALS with and without genetic variants.

METHODS

We included 146 patients with ALS and 128 healthy controls (HCs). All patients with ALS underwent genetic testing to screen for ALS related genetic variants and were then divided into genetic (n = 22) and nongenetic ALS (n = 93) subgroups. All participants underwent brain 18 F-FDG-PET scans. Group comparisons were performed using the two-sample t-test model of SPM12.

RESULTS

We identified a large of hypometabolic clusters in ALS patients as compared with HCs, especially in the bilateral basal ganglia, midbrain, and cerebellum. Moreover, hypometabolism in the bilateral temporal lobe, precentral gyrus and hypermetabolism in the left anterior cingulate, occipital lobe, and bilateral frontal lobe were also found in ALS patients as compared with HCs. Compared with nongenetic ALS patients, genetic ALS patients showed hypometabolism in the right postcentral gyrus, precuneus, and middle occipital gyrus. The incidence of sensory disturbance in patients with genetic ALS was higher than that in patients with nongenetic ALS (5 of 22 [22.72%] vs. 7 of 93 [7.52%], p = 0.036).

CONCLUSIONS

Our investigation provided unprecedented evidence of relative hypometabolism in the midbrain and cerebellum in ALS patients. Genetic ALS patients showed a specific signature of brain metabolism and a higher incidence of sensory disturbance, indicating that genetic factors may be an underlying cause affecting the brain metabolism and increasing the risk of sensory disturbance in ALS.

TREX1 p.A129fs and p.Y305C variants in a large multi-ethnic cohort of CADASIL-like unrelated patients

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and retinal vasculopathy with cerebral leukodystrophy and systemic manifestations (RVCL-S) are the most common forms of rare monogenic early-onset cerebral small vessel disease and share clinical, and, to different extents, neuroradiological and neuropathological features. However, whether CADASIL and RVCL-S overlapping phenotype may be explained by shared genetic risk or causative factors such as TREX1 coding variants remains poorly understood. To investigate this intriguing hypothesis, we used exome sequencing to screen TREX1 protein-coding variability in a large multi-ethnic cohort of 180 early-onset independent familial and apparently sporadic CADASIL-like Caucasian patients from the USA, Portugal, Finland, Serbia and Turkey. We report 2 very rare and likely pathogenic TREX1 mutations: a loss of function mutation (p.Ala129fs) clustering in the catalytic domain, in an apparently sporadic 46-year-old patient from the USA and a missense mutation (p.Tyr305Cys) in the well conserved C-terminal region, in a 57-year-old patient with positive family history from Serbia. In concert with recent findings, our study expands the clinical spectrum of diseases associated with TREX1 mutations.

DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN-/SOX10- (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in 'bulk' cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.

Genetics, Functions, and Clinical Impact of Presenilin-1 (PSEN1) Gene

Presenilin-1 (PSEN1) has been verified as an important causative factor for early onset Alzheimer's disease (EOAD). PSEN1 is a part of γ-secretase, and in addition to amyloid precursor protein (APP) cleavage, it can also affect other processes, such as Notch signaling, β-cadherin processing, and calcium metabolism. Several motifs and residues have been identified in PSEN1, which may play a significant role in γ-secretase mechanisms, such as the WNF, GxGD, and PALP motifs. More than 300 mutations have been described in PSEN1; however, the clinical phenotypes related to these mutations may be diverse. In addition to classical EOAD, patients with PSEN1 mutations regularly present with atypical phenotypic symptoms, such as spasticity, seizures, and visual impairment. In vivo and in vitro studies were performed to verify the effect of PSEN1 mutations on EOAD. The pathogenic nature of PSEN1 mutations can be categorized according to the ACMG-AMP guidelines; however, some mutations could not be categorized because they were detected only in a single case, and their presence could not be confirmed in family members. Genetic modifiers, therefore, may play a critical role in the age of disease onset and clinical phenotypes of PSEN1 mutations. This review introduces the role of PSEN1 in γ-secretase, the clinical phenotypes related to its mutations, and possible significant residues of the protein.

Amyotrophic lateral sclerosis with SOD1 mutations shows distinct brain metabolic changes

Purpose

Neuropathological data suggest that ALS with SOD1 mutations (SOD1-ALS) is a distinct form of ALS. We evaluated brain metabolic changes characterizing SOD1-ALS as compared to sporadic ALS (sALS), employing ¹⁸fluorodeoxyglucose-positron-emission tomography (¹⁸F-FDG-PET).

Methods

We included 18 SOD1-ALS patients, 40 healthy controls (HC), and 46 sALS patients without mutations in SOD1, TARDBP, FUS, and C9ORF72, randomly selected from 665 subjects who underwent brain ¹⁸F-FDG-PET at diagnosis between 2008 and 2019 at the ALS Centre of Turin. We excluded patients with frontotemporal dementia. We used the full factorial design in SPM12 to evaluate whether differences among groups exist overall. In case the hypothesis was confirmed, group comparisons were performed through the two-sample t-test model of SPM12. In all the analyses, the height threshold was P < 0.001 (P < 0.05 FWE-corrected at cluster level).

Results

The full factorial design resulted in a significant main effect of groups. We identified a relative hypometabolism in sALS patients compared to SOD1-ALS cases in the right precentral and medial frontal gyrus, right paracentral lobule, and bilateral postcentral gyrus. SOD1 patients showed a relative hypermetabolism as compared to HC in the right precentral gyrus and paracentral lobule. As compared to HC, sALS patients showed relative hypometabolism in frontal, temporal, and occipital cortices.

Conclusion

SOD1-ALS was characterized by a relative hypermetabolism in the motor cortex as compared to sALS and HC. Since promising, targeted, therapeutic strategies are upcoming for SOD1-ALS, our data support the use of PET to study disease pathogenesis and to track its course in clinical trials, in both asymptomatic and symptomatic mutation carriers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05668-7.

APOE genotype regulates pathology and disease progression in synucleinopathy

Apolipoprotein E (APOE) ε4 genotype is associated with increased risk of dementia in Parkinson's disease (PD), but the mechanism is not clear, because patients often have a mixture of α-synuclein (αSyn), amyloid-β (Aβ), and tau pathologies. APOE ε4 exacerbates brain Aβ pathology, as well as tau pathology, but it is not clear whether APOE genotype independently regulates αSyn pathology. In this study, we generated A53T αSyn transgenic mice (A53T) on Apoe knockout (A53T/EKO) or human APOE knockin backgrounds (A53T/E2, E3, and E4). At 12 months of age, A53T/E4 mice accumulated higher amounts of brainstem detergent-insoluble phosphorylated αSyn compared to A53T/EKO and A53T/E3; detergent-insoluble αSyn in A53T/E2 mice was undetectable. By immunohistochemistry, A53T/E4 mice displayed a higher burden of phosphorylated αSyn and reactive gliosis compared to A53T/E2 mice. A53T/E2 mice exhibited increased survival and improved motor performance compared to other APOE genotypes. In a complementary model of αSyn spreading, striatal injection of αSyn preformed fibrils induced greater accumulation of αSyn pathology in the substantia nigra of A53T/E4 mice compared to A53T/E2 and A53T/EKO mice. In two separate cohorts of human patients with PD, APOE ε4/ε4 individuals showed the fastest rate of cognitive decline over time. Our results demonstrate that APOE genotype directly regulates αSyn pathology independent of its established effects on Aβ and tau, corroborate the finding that APOE ε4 exacerbates pathology, and suggest that APOE ε2 may protect against αSyn aggregation and neurodegeneration in synucleinopathies.

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer’s Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10^-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.

Genetic association studies have been successful in identifying many genetic variants associated with disease risk, but it has been far more challenging to determine the genes through which these act. This is important, because such genes may encode effective drug targets for these diseases. We used Mendelian randomization (MR) and colocalization, two methods which in combination exploit these genetic variants to estimate the causal effects of individual genes. We applied this approach to 12 neurological and psychiatric diseases using data from the AMP-AD and CMC brain expression quantitative locus dataset, which is large enough to provide robust evidence for the relationship between genetic variants and gene expression. We found a causal relationship between the change in expression of 47 genes and increased disease risk across the 12 diseases we tested. As drug targets with human genetic evidence are far more likely to be approved in clinical trials, these findings provide a valuable list of potential therapeutic targets, including the ACE, GPNMB, KCNQ5, RERE and SUOX genes.

PharmKG: a dedicated knowledge graph benchmark for bomedical data mining

Biomedical knowledge graphs (KGs), which can help with the understanding of complex biological systems and pathologies, have begun to play a critical role in medical practice and research. However, challenges remain in their embedding and use due to their complex nature and the specific demands of their construction. Existing studies often suffer from problems such as sparse and noisy datasets, insufficient modeling methods and non-uniform evaluation metrics. In this work, we established a comprehensive KG system for the biomedical field in an attempt to bridge the gap. Here, we introduced PharmKG, a multi-relational, attributed biomedical KG, composed of more than 500 000 individual interconnections between genes, drugs and diseases, with 29 relation types over a vocabulary of ~8000 disambiguated entities. Each entity in PharmKG is attached with heterogeneous, domain-specific information obtained from multi-omics data, i.e. gene expression, chemical structure and disease word embedding, while preserving the semantic and biomedical features. For baselines, we offered nine state-of-the-art KG embedding (KGE) approaches and a new biological, intuitive, graph neural network-based KGE method that uses a combination of both global network structure and heterogeneous domain features. Based on the proposed benchmark, we conducted extensive experiments to assess these KGE models using multiple evaluation metrics. Finally, we discussed our observations across various downstream biological tasks and provide insights and guidelines for how to use a KG in biomedicine. We hope that the unprecedented quality and diversity of PharmKG will lead to advances in biomedical KG construction, embedding and application.

Functional genomic analyses uncover APOE-mediated regulation of brain and cerebrospinal fluid beta-amyloid levels in Parkinson disease

Alpha-synuclein is the main protein component of Lewy bodies, the pathological hallmark of Parkinson's disease. However, genetic modifiers of cerebrospinal fluid (CSF) alpha-synuclein levels remain unknown. The use of CSF levels of amyloid beta1-42, total tau, and phosphorylated tau181 as quantitative traits in genetic studies have provided novel insights into Alzheimer's disease pathophysiology. A systematic study of the genomic architecture of CSF biomarkers in Parkinson's disease has not yet been conducted. Here, genome-wide association studies of CSF biomarker levels in a cohort of individuals with Parkinson's disease and controls (N = 1960) were performed. PD cases exhibited significantly lower CSF biomarker levels compared to controls. A SNP, proxy for APOE ε4, was associated with CSF amyloid beta1-42 levels (effect = - 0.5, p = 9.2 × 10-19). No genome-wide loci associated with CSF alpha-synuclein, total tau, or phosphorylated tau181 levels were identified in PD cohorts. Polygenic risk score constructed using the latest Parkinson's disease risk meta-analysis were associated with Parkinson's disease status (p = 0.035) and the genomic architecture of CSF amyloid beta1-42 (R2 = 2.29%; p = 2.5 × 10-11). Individuals with higher polygenic risk scores for PD risk presented with lower CSF amyloid beta1-42 levels (p = 7.3 × 10-04). Two-sample Mendelian Randomization revealed that CSF amyloid beta1-42 plays a role in Parkinson's disease (p = 1.4 × 10-05) and age at onset (p = 7.6 × 10-06), an effect mainly mediated by variants in the APOE locus. In a subset of PD samples, the APOE ε4 allele was associated with significantly lower levels of CSF amyloid beta1-42 (p = 3.8 × 10-06), higher mean cortical binding potentials (p = 5.8 × 10-08), and higher Braak amyloid beta score (p = 4.4 × 10-04). Together these results from high-throughput and hypothesis-free approaches converge on a genetic link between Parkinson's disease, CSF amyloid beta1-42, and APOE.

Pro-cathepsin D, Prosaposin, and Progranulin: Lysosomal Networks in Parkinsonism

Mutations in GBA1, the gene encoding the lysosomal hydrolase glucocerebrosidase (GCase), are a risk factor for parkinsonism. Pursuing the potential mechanisms underlying this risk in aging neurons, we propose a new network uniting three major lysosomal proteins: (i) cathepsin D (CTSD), which plays a major role in α-synuclein (SNCA) degradation and prosaposin (PSAP) cleavage; (ii) PSAP, essential for GCase activation and progranulin (PGRN) transport; and (iii) PGRN, impacting lysosomal biogenesis, PSAP trafficking, and CTSD maturation. We hypothesize that alterations to this network and associated receptors modify lysosomal function and subsequently impact both SNCA degradation and GCase activity. By exploring the interactions between this protein trio and each of their respective transporters and receptors, we may identify secondary risk factors that provide insight into the relationship between these lysosomal proteins, GCase, and SNCA, and reveal novel therapeutic targets.

Characterization of novel progranulin gene variants in Italian patients with neurodegenerative diseases

Loss-of-function mutations in the gene encoding for the protein progranulin (PGRN), GRN, are one of the major genetic abnormalities involved in frontotemporal lobar degeneration. However, genetic variations, mainly missense, in GRN have also been linked to other neurodegenerative diseases. We found 12 different pathogenic/likely pathogenic variants in 21 patients identified in a cohort of Italian patients affected by various neurodegenerative disorders. We detected the p.Thr272SerfsTer10 as the most frequent, followed by the c.1179+3A>G variant. We characterized the clinical phenotype of 12 patients from 3 pedigrees carrying the c.1179+3A>G variant, demonstrated the pathogenicity of this mutation, and detected other rarer variants causing haploinsufficiency (p.Met1?, c.709-2A>T, p.Gly79AspfsTer39). Finally, by applying bioinformatics, neuropathological, and biochemical studies, we characterized 6 missense/synonymous variants (p.Asp94His, p.Gly117Asp, p.Ala266Pro, p.Val279Val, p.Arg298His, p.Ala505Gly), including 4 previously unreported. The designation of variants is crucial for genetic counseling and the enrollment of patients in clinical studies.

Aβ, Tau, and α-Synuclein aggregation and integrated role of PARK2 in the regulation and clearance of toxic peptides

Alzheimer's and Parkinson's diseases are one of the world's leading causes of death. >50 million people throughout the world are suffering with these diseases. They are two distinct progressive neurodegenerative disorders affecting different regions of the brain with diverse symptoms, including memory and motor loss respectively, but with the advancement of diseases, both affect the whole brain and exhibit some common biological symptoms. For instance, >50% PD patients develop dementia in their later stages, though it is a hallmark of Alzheimer's disease. In fact, latest research has suggested the involvement of some common pathophysiological and genetic links between these diseases, including the deposition of pathological Aβ, Tau, and α-synuclein in both the cases. Therefore, it is pertinent to diagnose the shared biomarkers, their aggregation mechanism, their intricate relationships in the pathophysiology of disease and therapeutic markers to target them. This would enable us to identify novel markers for the early detection of disease and targets for the future therapies. Herein, we investigated molecular aspects of Aβ, Tau, and α-Synuclein aggregation, and characterized their functional partners involved in the pathology of AD and PD. Moreover, we identified the molecular-crosstalk between AD and PD associated with their pathogenic proteins- Aβ, Tau, and α-Synuclein. Furthermore, we characterized their ubiquitinational enzymes and associated interaction network regulating the proteasomal clearance of these pathological proteins.

The Missing Heritability of Sporadic Frontotemporal Dementia: New Insights from Rare Variants in Neurodegenerative Candidate Genes

Frontotemporal dementia (FTD) is a common form of dementia among early-onset cases. Several genetic factors for FTD have been revealed, but a large proportion of FTD cases still have an unidentified genetic origin. Recent studies highlighted common pathobiological mechanisms among neurodegenerative diseases. In the present study, we investigated a panel of candidate genes, previously described to be associated with FTD and/or other neurodegenerative diseases by targeted next generation sequencing (NGS). We focused our study on sporadic FTD (sFTD), devoid of disease-causing mutations in GRN, MAPT and C9orf72. Since genetic factors have a substantially higher pathogenetic contribution in early onset patients than in late onset dementia, we selected patients with early onset (<65 years). Our study revealed that, in 50% of patients, rare missense potentially pathogenetic variants in genes previously associated with Alzheimer's disease, Parkinson disease, amyotrophic lateral sclerosis and Lewy body dementia (GBA, ABCA7, PARK7, FUS, SORL1, LRRK2, ALS2), confirming genetic pleiotropy in neurodegeneration. In parallel, a synergic genetic effect on FTD is suggested by the presence of variants in five different genes in one single patient. Further studies employing genome-wide approaches might highlight pathogenic variants in novel genes that explain the still missing heritability of FTD.

Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43,870 individuals from the eMERGE network

The link between cardiovascular diseases and neurological disorders has been widely observed in the aging population. Disease prevention and treatment rely on understanding the potential genetic nexus of multiple diseases in these categories. In this study, we were interested in detecting pleiotropy, or the phenomenon in which a genetic variant influences more than one phenotype. Marker-phenotype association approaches can be grouped into univariate, bivariate, and multivariate categories based on the number of phenotypes considered at one time. Here we applied one statistical method per category followed by an eQTL colocalization analysis to identify potential pleiotropic variants that contribute to the link between cardiovascular and neurological diseases. We performed our analyses on ~530,000 common SNPs coupled with 65 electronic health record (EHR)-based phenotypes in 43,870 unrelated European adults from the Electronic Medical Records and Genomics (eMERGE) network. There were 31 variants identified by all three methods that showed significant associations across late onset cardiac- and neurologic- diseases. We further investigated functional implications of gene expression on the detected "lead SNPs" via colocalization analysis, providing a deeper understanding of the discovered associations. In summary, we present the framework and landscape for detecting potential pleiotropy using univariate, bivariate, multivariate, and colocalization methods. Further exploration of these potentially pleiotropic genetic variants will work toward understanding disease causing mechanisms across cardiovascular and neurological diseases and may assist in considering disease prevention as well as drug repositioning in future research.