Shared genetic etiology between Parkinson's disease and blood levels of specific lipids

Identification of metabolites reproducibly associated with Parkinson's Disease via meta-analysis and computational modelling

Many studies have reported metabolomic analysis of different bio-specimens from Parkinson's disease (PD) patients. However, inconsistencies in reported metabolite concentration changes make it difficult to draw conclusions as to the role of metabolism in the occurrence or development of Parkinson's disease. We reviewed the literature on metabolomic analysis of PD patients. From 74 studies that passed quality control metrics, 928 metabolites were identified with significant changes in PD patients, but only 190 were replicated with the same changes in more than one study. Of these metabolites, 60 exclusively increased, such as 3-methoxytyrosine and glycine, 54 exclusively decreased, such as pantothenic acid and caffeine, and 76 inconsistently changed in concentration in PD versus control subjects, such as ornithine and tyrosine. A genome-scale metabolic model of PD and corresponding metabolic map linking most of the replicated metabolites enabled a better understanding of the dysfunctional pathways of PD and the prediction of additional potential metabolic markers from pathways with consistent metabolite changes to target in future studies.

The potential role of glucose metabolism, lipid metabolism, and amino acid metabolism in the treatment of Parkinson's disease

PURPOSE OF REVIEW

Parkinson's disease (PD) is a common neurodegenerative disease, which can cause progressive deterioration of motor function causing muscle stiffness, tremor, and bradykinesia. In this review, we hope to describe approaches that can improve the life of PD patients through modifications of energy metabolism.

RECENT FINDINGS

The main pathological features of PD are the progressive loss of nigrostriatal dopaminergic neurons and the production of Lewy bodies. Abnormal aggregation of α-synuclein (α-Syn) leading to the formation of Lewy bodies is closely associated with neuronal dysfunction and degeneration. The main causes of PD are said to be mitochondrial damage, oxidative stress, inflammation, and abnormal protein aggregation. Presence of abnormal energy metabolism is another cause of PD. Many studies have found significant differences between neurodegenerative diseases and metabolic decompensation, which has become a biological hallmark of neurodegenerative diseases.

SUMMARY

In this review, we highlight the relationship between abnormal energy metabolism (Glucose metabolism, lipid metabolism, and amino acid metabolism) and PD. Improvement of key molecules in glucose metabolism, fat metabolism, and amino acid metabolism (e.g., glucose-6-phosphate dehydrogenase, triglycerides, and levodopa) might be potentially beneficial in PD. Some of these metabolic indicators may serve well during the diagnosis of PD. In addition, modulation of these metabolic pathways may be a potential target for the treatment and prevention of PD.

Rubusoside mitigates neuroinflammation and cellular apoptosis in Parkinson's disease, and alters gut microbiota and metabolite composition

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative condition characterized by the progressive loss of dopaminergic neurons within the substantia nigra. Neuroinflammation plays a pivotal role in the pathogenesis of PD, involving the activation of microglia cells, heightened production of proinflammatory cytokines, and perturbations in the composition of the gut microbiota. Rubusoside (Ru), the principal steviol bisglucoside present in Rubus chingii var. suavissimus (S.K.Lee) L.T.Lu (Rosaceae), has been documented for its anti-inflammatory properties in diverse disease models. Nonetheless, there is an imperative need to comprehensively assess and elucidate the protective and anti-inflammatory attributes of Ru concerning PD, as well as to uncover the underlying mechanism involved.

OBJECTIVE

The aim of this study is to evaluate the neuroprotective and anti-inflammatory effects of Ru on PD and investigate its potential mechanisms associated with microbes.

RESEARCH DESIGN AND METHODS

We pre-treated mice and cell lines with Ru in order to simulate the progression of PD and the neuroinflammatory state. The mouse model was induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), SN4741 cells were induced by 1-methyl-4-phenylpyridine (mpp+), and BV-2 cells were induced by lipopolysaccharide (LPS). We assessed the impact of Ru on motor function, neuroinflammation, neuron apoptosis, the composition of gut microbes, and their metabolites.

RESULTS

Ru treatment reduces the release of pro-inflammatory mediators by inhibiting microglia activation. It also prevents neuronal apoptosis, thereby safeguarding dopaminergic neurons and ameliorating motor dysfunction. Furthermore, it induces alterations in the fecal microbiota composition and metabolites profile in PD mice. In vitro experiments have demonstrated that Ru inhibits neuronal apoptosis in SN4741 cells induced by mpp+, suppresses the production of pro-inflammatory mediators, and activates the c-Jun N-terminal kinase (JNK), mitogen-activated protein kinase (p38 MAPK), and nuclear factor kappa-B (NF-κB) signaling pathways.

CONCLUSION

Ru exhibits inhibitory effects on the MPTP-induced PD model by mitigating neuroinflammation and neuronal apoptosis while also inducing changes in the gut microbiota and metabolite composition.

Serum lipid levels are associated with orthostatic hypotension in multiple system atrophy patients

OBJECTIVES

Orthostatic hypotension (OH) is one of the most important autonomic features of multiple system atrophy (MSA). This study was established to confirm the correlation between lipid levels and OH in MSA.

METHODS

A total of 580 patients with probable or possible MSA from neurological wards in six hospitals in Tianjin, Beijing, Hebei Province, and Henan Province, China, were included in this study. The tilt test or stand test was used to assess the severity of OH. Lipid contents, including total cholesterol, low-density-lipoprotein cholesterol (LDL-C), high-density-lipoprotein cholesterol (HDL-C), and triglyceride were evaluated.

RESULTS

Serum levels of total cholesterol, LDL-C, and triglyceride in MSA-OH patients were significantly lower than those in MSA without OH. The risks of OH were significantly higher in the lowest quartiles of triglyceride and LDL-C than in the highest quartiles, after adjusting for confounders (OR = 2.17, 95% CI: 1.23-3.82, P = 0.008 and OR = 2.02, 95% CI: 1.16-3.47, P = 0.012). The risk of severe OH was significantly higher in the lowest quartile and the second quartile of triglyceride than in the highest quartile after adjusting for confounders (OR = 2.16, 95% CI: 1.20-3.87, P = 0.010 and OR = 2.25, 95% CI: 1.24-4.07, P = 0.007). Moreover, the risk of OH was significantly higher in the lowest quartile, and the third quartile of TC than in the highest quartile after adjusting for confounders (OR = 2.04, 95% CI: 1.18-3.52, P = 0.010 and OR = 2.06, 95% CI: 1.19-3.56, P = 0.010).

CONCLUSION

Low levels of TC, LDL-C, and triglyceride increased the risk of OH in MSA. A low level of triglyceride predicted severe OH in MSA.

Associations between polyunsaturated fatty acid concentrations and Parkinson's disease: A two-sample Mendelian randomization study

Introduction

Observational studies demonstrated controversial effect of polyunsaturated fatty acids (PUFAs) on Parkinson's disease (PD) with limited causality evidence. Randomized control trials showed possible improvement in PD symptoms with PUFA supplement but had small study population and limited intervention time.

Methods

A two-sample Mendelian randomization was designed to evaluate the causal relevance between PUFAs and PD, using genetic variants of PUFAs as instrumental variables and PD data from the largest genome-wide association study as outcome. Inverse variance weighted (IVW) method was applied to obtain the primary outcome. Mendelian randomization Egger regression, weighted median and weighted mode methods were exploited to assist result analyses. Strict Mendelian randomization and multivariable Mendelian randomization (MVMR) were used to estimate direct effects of PUFAs on PD, eliminating pleiotropic effect. Debiased inverse variance weighted estimator was implemented when weak instrument bias was introduced into the analysis. A variety of sensitivity analyses were utilized to assess validity of the results.

Results

Our study included 33,674 PD cases and 449,056 controls. Higher plasma level of arachidonic acid (AA) was associated with a 3% increase of PD risk per 1-standard deviation (SD) increase of AA (IVW; Odds ratio (OR)=1.03 [95% confidence interval (CI) 1.01-1.04], P = 2.24E-04). After MVMR (IVW; OR=1.03 [95% CI 1.02-1.04], P =6.15E-08) and deletion of pleiotropic single-nucleotide polymorphisms overlapping with other lipids (IVW; OR=1.03 [95% CI 1.01-1.05], P =5.88E-04), result was still significant. Increased level of eicosapentaenoic acid (EPA) showed possible relevance with increased PD risk after adjustment of pleiotropy (MVMR; OR=1.05 [95% CI 1.01-1.08], P =5.40E-03). Linoleic acid (LA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA) and alpha-linolenic acid (ALA) were found not causally relevant to PD risk. Various sensitivity analyses verified the validity of our results. In conclusion, our findings from Mendelian randomization suggested that elevated levels of AA and possibly EPA might be linked to a higher risk of PD. No association between PD risk and LA, DHA, DPA, or ALA was found.

Discussion

The odds ratio for plasma AA and PD risk was weak. It is important to approach our results with caution in clinical practice and to conduct additional studies on the relationship between PUFAs and PD risk.

Association between serum lipid levels over time and risk of Parkinson's disease

The role of serum lipids in Parkinson's disease (PD) remains controversial. We aimed to evaluate the association between time-varying serum lipid levels and the risk of PD. This study included an assessment of the complete lipid profiles of 200,454 individuals from the 2002-2019 Korean National Health Insurance Health Screening Cohort. Time-dependent Cox proportional hazard regression models were used to evaluate the association between serum lipid levels over time and the risk of PD. Individuals in the lowest tertile of total cholesterol and low-density lipoprotein cholesterol had a 1.17 times [hazard ratio (HR) 1.17; 95% confidence interval (CI) 1.04-1.31] and 1.19 times (HR 1.19; 95% CI 1.06-1.34) higher risk of PD than those in middle tertile, respectively. Individuals in the highest high-density lipoprotein cholesterol tertile had a 0.89 times (HR 0.89; 95% CI 0.79-1.00) lower risk of PD than those in middle tertile, but the association was less robust in sensitivity analyses. Serum triglyceride levels were not related to the risk of PD. Our results suggest that the serum total and low-density lipoprotein cholesterol levels over time are inversely associated with the risk of PD. Further research is warranted to confirm these findings and reveal the underlying mechanisms.

Genomic, transcriptomic, and metabolomic profiles of hiPSC-derived dopamine neurons from clinically discordant brothers with identical PRKN deletions

We previously reported on two brothers who carry identical compound heterozygous PRKN mutations yet present with significantly different Parkinson's Disease (PD) clinical phenotypes. Juvenile cases demonstrate that PD is not necessarily an aging-associated disease. Indeed, evidence for a developmental component to PD pathogenesis is accumulating. Thus, we hypothesized that the presence of additional genetic modifiers, including genetic loci relevant to mesencephalic dopamine neuron development, could potentially contribute to the different clinical manifestations of the two brothers. We differentiated human-induced pluripotent stem cells (hiPSCs) derived from the two brothers into mesencephalic neural precursor cells and early postmitotic dopaminergic neurons and performed wholeexome sequencing and transcriptomic and metabolomic analyses. No significant differences in the expression of canonical dopamine neuron differentiation markers were observed. Yet our transcriptomic analysis revealed a significant downregulation of the expression of three neurodevelopmentally relevant cell adhesion molecules, CNTN6, CNTN4 and CHL1, in the cultures of the more severely affected brother. In addition, several HLA genes, known to play a role in neurodevelopment, were differentially regulated. The expression of EN2, a transcription factor crucial for mesencephalic dopamine neuron development, was also differentially regulated. We further identified differences in cellular processes relevant to dopamine metabolism. Lastly, wholeexome sequencing, transcriptomics and metabolomics data all revealed differences in glutathione (GSH) homeostasis, the dysregulation of which has been previously associated with PD. In summary, we identified genetic differences which could potentially, at least partially, contribute to the discordant clinical PD presentation of the two brothers.

Lower Blood Lipid Level Is Associated with the Occurrence of Parkinson's Disease: A Meta-Analysis and Systematic Review

BACKGROUND

The changes of blood lipid levels in patients with Parkinson's disease (PD) and its clinical relevance remain unclear. We aimed to evaluate the potential association of blood lipid and the occurrence of PD, to provide evidence to the clinical treatment and nursing care of PD.

METHODS

We searched PubMed, Medline, Web of Science, Cochrane Library, Wanfang Database, Weipu Database, and China National Knowledge Infrastructure for studies related to the blood lipid levels and PD until November 30, 2021. Two researchers independently screened the literature and extricated the data including the levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included studies. RevMan5.3 and Stata 12.0 software were used for statistical processing and analysis.

RESULTS

A total of 15 cohort studies with 9740 participants involving 2032 PD patients and 7708 controls were included. Meta-analysis indicated that TC (SMD = -0.29, 95% CI -0.55∼-0.03, P=0.04), TG (SMD = -16.83, 95% CI -20.71∼-12.95, P < 0.001), HDL-C (SMD = -0.14, 95% CI -0.26∼-0.02, P < 0.001) and LDL-C (SMD = -0.26, 95% CI -0.50∼-0.01, P=0.04) level in the PD patients was significantly lower than that of health controls. Sensitivity analysis indicated that the results were stable. No significant publication bias was found between the synthesized outcomes.

CONCLUSIONS

Lower blood TC, TG, HDL-C, and LDL-C level are associated with the occurrence of PD. Limited by sample size and study population, further high-quality, large-sample clinical trials in different areas are needed to further determine the relationship between blood lipids and PD in the future.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Polygenic Risk Scores Contribute to Personalized Medicine of Parkinson's Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by the loss of dopaminergic neurons. The vast majority of PD patients develop the disease sporadically and it is assumed that the cause lies in polygenic and environmental components. The overall polygenic risk is the result of a large number of common low-risk variants discovered by large genome-wide association studies (GWAS). Polygenic risk scores (PRS), generated by compiling genome-wide significant variants, are a useful prognostic tool that quantifies the cumulative effect of genetic risk in a patient and in this way helps to identify high-risk patients. Although there are limitations to the construction and application of PRS, such as considerations of limited genetic underpinning of diseases explained by SNPs and generalizability of PRS to other populations, this personalized risk prediction could make a promising contribution to stratified medicine and tailored therapeutic interventions in the future.

Targeted fatty acid metabolomics to discover Parkinson's disease associated metabolic alteration

The pathogenesis of Parkinson's disease (PD) remains to be elucidated, and the metabolomics analysis has the potential to identify metabolic profiles that are involved in PD pathogenesis. Here we applied a target metabolomics approach to measure the plasma levels of 158 fatty acid metabolites in a discovery cohort including 42 PD patients and 54 health volunteers, and found two upregulated (arachidonic acid and 13-hydroxy-octadecatrienoic acid) and eleven down-regulated (docosahexaenoic acid, lyso-platelet-activating factor, 12-hydroxy-eicosatetraenoic acid, dihydroxy-eicosatrienoic acids, dihidroxy-octadecenoic acids, 17,18-dihydroxy-eicosatetraenoic acid, and hydroperoxy-octadecadienoic acids) metabolites as primary candidate marker of PD. A support vector machine algorithm with primary candidate marker was used in an independent validation cohort to identify PD. Arachidonic acid and 13-hydroxy-octadecatrienoic acid were evaluated as an effective tool in that area under the receiver operating characteristic curve reached 0.995 and 0.912 in the validation set for diagnosing PD from healthy volunteers. Besides, the sensitivity and specificity of arachidonic acid as diagnostic factor of PD in validation set were 100% and 94.10%. Similarly, the sensitivity and specificity of 13-hydroxy-octadecatrienoic acid were 100% and 82.40% for identifying PD. This target fatty acid metabolomics demonstrated a series of plasma fatty acid metabolite as PD candidate marker with high efficiency and provided insights into the understanding of PD metabolic regulation.

Genetic overlap between Alzheimer's disease and blood lipid levels

Late-onset Alzheimer's disease (AD) has a significant genetic component, but the molecular mechanisms through which genetic risk factors contribute to AD pathogenesis are unclear. We screened for genetic sharing between AD and the blood levels of 615 metabolites to elucidate how the polygenic architecture of AD affects metabolomic profiles. We retrieved summary statistics from genome-wide association studies of AD and the metabolite blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 31 metabolites, all of which were lipids, we identified and replicated genetic sharing with AD. We also found a positive genetic concordance - implying that genetic risk factors for AD are associated with higher blood levels - for 16 of the 31 replicated metabolites. In the brain, lipids and their intermediate metabolites have essential structural and functional roles, such as forming and dynamically regulating synaptic membranes. Our results imply that genetic risk factors for AD affect lipid levels, which may be leveraged to develop novel treatment strategies for AD.

Shared Genetic Etiology between Alzheimer's Disease and Blood Levels of Specific Cytokines and Growth Factors

Late-onset Alzheimer’s disease (AD) has a significant genetic and immunological component, but the molecular mechanisms through which genetic and immunity-related risk factors and their interplay contribute to AD pathogenesis are unclear. Therefore, we screened for genetic sharing between AD and the blood levels of a set of cytokines and growth factors to elucidate how the polygenic architecture of AD affects immune marker profiles. For this, we retrieved summary statistics from Finnish genome-wide association studies of AD and 41 immune marker blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 15 cytokines and growth factors, we identified genetic sharing with AD. We also found positive and negative genetic concordances—implying that genetic risk factors for AD are associated with higher and lower blood levels—for several immune markers and were able to relate some of these results to the literature. Our results imply that genetic risk factors for AD also affect specific immune marker levels, which may be leveraged to develop novel treatment strategies for AD.