Parkinson disease polygenic risk score is associated with Parkinson disease status and age at onset but not with alpha-synuclein cerebrospinal fluid levels

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson's disease

The objective of this study was to investigate the association between a Parkinson's disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD. We included data from 4367 patients with idiopathic PD, 159 patients with GBA1-PD, and 3090 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The association between PGS and lifestyle factors on AAO was assessed with linear and Cox proportional hazards models. The PGS showed a negative association with AAO (β = - 1.07, p = 6 × 10-7) in patients with idiopathic PD. The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p = 0.0001), 44% (p < 2 × 10-16), and 55% (p < 2 × 10-16), compared to no use. An additive effect of aspirin (β = 7.62, p = 9 × 10-7) and PGS (β = - 1.58, p = 0.0149) was found for AAO without an interaction (p = 0.9993) in the linear regressions, and similar effects were seen for tobacco. In contrast, no association between aspirin intake and AAO was found in GBA1-PD (p > 0.05). In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect.

Genetic analysis and natural history of Parkinson's disease due to the LRRK2 G2019S variant

The LRRK2 G2019S variant is the most common cause of monogenic Parkinson's disease (PD); however, questions remain regarding the penetrance, clinical phenotype and natural history of carriers. We performed a 3.5-year prospective longitudinal online study in a large number of 1286 genotyped LRRK2 G2019S carriers and 109 154 controls, with and without PD, recruited from the 23andMe Research Cohort. We collected self-reported motor and non-motor symptoms every 6 months, as well as demographics, family histories and environmental risk factors. Incident cases of PD (phenoconverters) were identified at follow-up. We determined lifetime risk of PD using accelerated failure time modelling and explored the impact of polygenic risk on penetrance. We also computed the genetic ancestry of all LRRK2 G2019S carriers in the 23andMe database and identified regions of the world where carrier frequencies are highest. We observed that despite a 1 year longer disease duration (P = 0.016), LRRK2 G2019S carriers with PD had similar burden of motor symptoms, yet significantly fewer non-motor symptoms including cognitive difficulties, REM sleep behaviour disorder (RBD) and hyposmia (all P-values ≤ 0.0002). The cumulative incidence of PD in G2019S carriers by age 80 was 49%. G2019S carriers had a 10-fold risk of developing PD versus non-carriers. This rose to a 27-fold risk in G2019S carriers with a PD polygenic risk score in the top 25% versus non-carriers in the bottom 25%. In addition to identifying ancient founding events in people of North African and Ashkenazi descent, our genetic ancestry analyses infer that the G2019S variant was later introduced to Spanish colonial territories in the Americas. Our results suggest LRRK2 G2019S PD appears to be a slowly progressive predominantly motor subtype of PD with a lower prevalence of hyposmia, RBD and cognitive impairment. This suggests that the current prodromal criteria, which are based on idiopathic PD, may lack sensitivity to detect the early phases of LRRK2 PD in G2019S carriers. We show that polygenic burden may contribute to the development of PD in the LRRK2 G2019S carrier population. Collectively, the results should help support screening programmes and candidate enrichment strategies for upcoming trials of LRRK2 inhibitors in early-stage disease.

Genetics in Parkinson's disease, state-of-the-art and future perspectives

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disorder and is clinically characterized by the presence of motor (bradykinesia, rigidity, rest tremor and postural instability) and non-motor symptoms (cognitive impairment, autonomic dysfunction, sleep disorders, depression and hyposmia). The aetiology of PD is unknown except for a small but significant contribution of monogenic forms.

SOURCES OF DATA

No new data were generated or analyzed in support of this review.

AREAS OF AGREEMENT

Up to 15% of PD patients carry pathogenic variants in PD-associated genes. Some of these genes are associated with mendelian inheritance, while others act as risk factors. Genetic background influences age of onset, disease course, prognosis and therapeutic response.

AREAS OF CONTROVERSY

Genetic testing is not routinely offered in the clinical setting, but it may have relevant implications, especially in terms of prognosis, response to therapies and inclusion in clinical trials. Widely adopted clinical guidelines on genetic testing are still lacking and open to debate. Some new genetic associations are still awaiting confirmation, and selecting the appropriate genes to be included in diagnostic panels represents a difficult task. Finally, it is still under study whether (and to which degree) specific genetic forms may influence the outcome of PD therapies.

GROWING POINTS

Polygenic Risk Scores (PRS) may represent a useful tool to genetically stratify the population in terms of disease risk, prognosis and therapeutic outcomes.

AREAS TIMELY FOR DEVELOPING RESEARCH

The application of PRS and integrated multi-omics in PD promises to improve the personalized care of patients.

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.

The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson's disease

Objective

To investigate the association between a Parkinson's disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD.

Methods

We included data from 4375 patients with idiopathic PD, 167 patients with GBA1-PD, and 3091 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The PGS was calculated based on a previously proposed composition of 1805 variants. The association between PGS and lifestyle factors (i.e., coffee, tobacco, and aspirin) on AAO was assessed with linear and Cox proportional hazards models.

Results

The PGS showed a negative association with AAO (β=-1.07, p=6×10-7). The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p=0.0001), 45% (p<2×10-16), and 55% (p<2×10-16), respectively, compared to no use. An additive effect of aspirin (β=7.61, p=8×10-7) and PGS (β=-1.63, p=0.0112) was found for AAO without an interaction (p=0.9789) in the linear regressions, and similar effects were seen for tobacco. Aspirin is shown to be a better predictor of AAO (R2=0.1740) compared to coffee and tobacco use (R2=0.0243, R2=0.0295) or the PGS (R2=0.0141). In contrast, no association between aspirin and AAO was found in GBA1-PD (p>0.05).

Interpretation

In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect. External validation of our findings is needed.

Defining the Riddle in Order to Solve It: There Is More Than One "Parkinson's Disease"

BACKGROUND

More than 200 years after James Parkinsondescribed a clinical syndrome based on his astute observations, Parkinson's disease (PD) has evolved into a complex entity, akin to the heterogeneity of other complex human syndromes of the central nervous system such as dementia, motor neuron disease, multiple sclerosis, and epilepsy. Clinicians, pathologists, and basic science researchers evolved arrange of concepts andcriteria for the clinical, genetic, mechanistic, and neuropathological characterization of what, in their best judgment, constitutes PD. However, these specialists have generated and used criteria that are not necessarily aligned between their different operational definitions, which may hinder progress in solving the riddle of the distinct forms of PD and ultimately how to treat them.

OBJECTIVE

This task force has identified current in consistencies between the definitions of PD and its diverse variants in different domains: clinical criteria, neuropathological classification, genetic subtyping, biomarker signatures, and mechanisms of disease. This initial effort for "defining the riddle" will lay the foundation for future attempts to better define the range of PD and its variants, as has been done and implemented for other heterogeneous neurological syndromes, such as stroke and peripheral neuropathy. We strongly advocate for a more systematic and evidence-based integration of our diverse disciplines by looking at well-defined variants of the syndrome of PD.

CONCLUSION

Accuracy in defining endophenotypes of "typical PD" across these different but interrelated disciplines will enable better definition of variants and their stratification in therapeutic trials, a prerequisite for breakthroughs in the era of precision medicine. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Artificial intelligence-based clustering and characterization of Parkinson's disease trajectories

Parkinson's disease (PD) is a highly heterogeneous disease both with respect to arising symptoms and its progression over time. This hampers the design of disease modifying trials for PD as treatments which would potentially show efficacy in specific patient subgroups could be considered ineffective in a heterogeneous trial cohort. Establishing clusters of PD patients based on their progression patterns could help to disentangle the exhibited heterogeneity, highlight clinical differences among patient subgroups, and identify the biological pathways and molecular players which underlie the evident differences. Further, stratification of patients into clusters with distinct progression patterns could help to recruit more homogeneous trial cohorts. In the present work, we applied an artificial intelligence-based algorithm to model and cluster longitudinal PD progression trajectories from the Parkinson's Progression Markers Initiative. Using a combination of six clinical outcome scores covering both motor and non-motor symptoms, we were able to identify specific clusters of PD that showed significantly different patterns of PD progression. The inclusion of genetic variants and biomarker data allowed us to associate the established progression clusters with distinct biological mechanisms, such as perturbations in vesicle transport or neuroprotection. Furthermore, we found that patients of identified progression clusters showed significant differences in their responsiveness to symptomatic treatment. Taken together, our work contributes to a better understanding of the heterogeneity encountered when examining and treating patients with PD, and points towards potential biological pathways and genes that could underlie those differences.

Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine

Parkinson's Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated with disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods to detect associations between genetic variants and the disease phenotypes in existing PD GWAS. Secondly, we discuss the potential of machine learning approaches to better quantify disease phenotypes and to move beyond disease understanding towards a better-personalized treatment of the disease.

Genome Sequencing in the Parkinson Disease Clinic

Background and Objectives

Genetic variants affect both Parkinson disease (PD) risk and manifestations. Although 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 examine interest in comprehensive genetic testing among patients with PD and document reactions to possible findings from genome sequencing in 2 academic movement disorder clinics.

Methods

In 203 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. Based on the results, 231 patients (age = 67 years, 63% male) were surveyed on interest in genetic testing and responses to vignettes covering (1) familial risk of PD (LRRK2); (2) risk of PD dementia (GBA); (3) PD genetic risk score; and (4) secondary, medically actionable variants (BRCA1).

Results

Genome sequencing revealed a LRRK2 variant in 3% and a GBA risk variant in 10% of our clinical sample. The genetic risk score was normally distributed, identifying 41 subjects with a high risk of PD. Medically actionable findings were discovered in 2 subjects (1%). In our survey, the majority (82%) responded that they would share a LRRK2 variant with relatives. Most registered unchanged or increased interest in testing when confronted with a potential risk for dementia or medically actionable findings, and most (75%) expressed interest in learning their PD genetic risk score.

Discussion

Our results highlight broad interest in comprehensive genetic testing among patients with PD and may facilitate integration of genome sequencing in clinical practice.

Mitochondrial and autophagy-lysosomal pathway polygenic risk scores predict Parkinson's disease

Polygenic Risk Scores (PRS), which allow assessing an individuals' genetic risk for a complex disease, are calculated as the weighted number of genetic risk alleles in an individual's genome, with the risk alleles and their weights typically derived from the results of genome-wide association studies (GWAS). Among a wide range of applications, PRS can be used to identify at-risk individuals and select them for further clinical follow-up. Pathway PRS are genetic scores based on single nucleotide polymorphisms (SNPs) assigned to genes involved in major disease pathways. The aim of this study is to assess the predictive utility of PRS models constructed based on SNPs corresponding to two cardinal pathways in Parkinson's disease (PD) including mitochondrial PRS (Mito PRS) and autophagy-lysosomal PRS (ALP PRS). PRS models were constructed using the clumping-and-thresholding method in a German population as prediction dataset that included 371 cases and 249 controls, using SNPs discovered by the most recent PD-GWAS. We showed that these pathway PRS significantly predict the PD status. Furthermore, we demonstrated that Mito PRS are significantly associated with later age of onset in PD patients. Our results may add to the accumulating evidence for the contribution of mitochondrial and autophagy-lysosomal pathways to PD risk and facilitate biologically relevant risk stratification of PD patients.

Detection and assessment of alpha-synuclein in Parkinson disease

PURPOSE

Different studies have reported varying alpha-synuclein values in the cerebrospinal fluid (CSF), serum, and plasma, making determination of the alpha-synuclein cutoff value for Parkinson's disease difficult and rendering identifying the cause of variation essential.

METHOD

We searched PubMed from inception to June 2021 and identified 76 eligible studies. Included studies reported data on total, phosphorylated, and oligomeric alpha-synuclein in the CSF, serum, or plasma from individuals with Parkinson's disease and healthy controls. The mean or median alpha-synuclein values from the included studies were summarized and categorized through laboratory assays to visualize potential trends.

RESULTS

The enzyme-linked immunosorbent assay (ELISA) is the most common assay used to determine alpha-synuclein concentrations. Less common assays include Luminex, single molecule arrays, electrochemiluminescence, and immunomagnetic reduction (IMR). IMR is a single-antibody and wash-free immunoassay designed for determining the extremely low concentration of bio-molecules. For patients with Parkinson's disease, the median or mean testing values ranged from 60.9 to 55,000 pg/mL in the CSF, 0.446 to 1,777,100 pg/mL in plasma, and 0.0292 to 38,200,000 pg/mL in serum. The antibody selection was diverse between studies. The tendency of distribution was more centralized among studies that used the same kit. Studies adopting specific antibodies or in-house assays contribute to the extreme values. Only a few studies on phosphorylated and oligomeric alpha-synuclein were included.

CONCLUSION

The type of assay and antibody selection in the laboratory played major roles in the alpha-synuclein variation. Studies that used the same assay and kit yielded relatively unanimous results. Furthermore, IMR may be a promising assay for plasma and serum alpha-synuclein quantification. A consensus on sample preparation and testing protocol unification is warranted in the future.

Genetic Variability of the Vitamin D Receptor Affects Susceptibility to Parkinson’s Disease and Dopaminergic Treatment Adverse Events

Vitamin D is a lipid-soluble molecule and an important transcriptional regulator in many tissues and organs, including the brain. Its role has been demonstrated also in Parkinson’s disease (PD) pathogenesis. Vitamin D receptor (VDR) is responsible for the initiation of vitamin D signaling cascade. The aim of this study was to assess the associations of VDR genetic variability with PD risk and different PD-related phenotypes. We genotyped 231 well characterized PD patients and 161 healthy blood donors for six VDR single nucleotide polymorphisms, namely rs739837, rs4516035, rs11568820, rs731236, rs2228570, and rs1544410. We observed that VDR rs2228570 is associated with PD risk (p < 0.001). Additionally, we observed associations of specific VDR genotypes with adverse events of dopaminergic treatment. VDR rs1544410 (GG vs. GA + AA: p = 0.005; GG vs. GA: p = 0.009) was associated with the occurrence of visual hallucinations and VDR rs739837 (TT vs. GG: p = 0.036), rs731236 (TT vs. TC + CC: p = 0.011; TT vs. TC: p = 0.028; TT vs. CC: p = 0.035), and rs1544410 (GG vs. GA: p = 0.014) with the occurrence of orthostatic hypotension. We believe that the reported study may support personalized approach to PD treatment, especially in terms of monitoring vitamin D level and vitamin D supplementation in patients with high risk VDR genotypes.

Genetics of cognitive dysfunction in Parkinson's disease

Presentation and progression of cognitive symptoms in Parkinson's disease are highly variable. PD is a genetically complex disorder with multiple genetic risk factors and understanding the role that genes play in cognitive outcomes is important for patient counseling and treatment. Currently, there are seven well-described genes that increase the risk for PD, with variable levels of penetrance: SNCA, LRRK2, VPS35, PRKN, PINK1, DJ1 and GBA. In addition, large, genome-wide association studies have identified multiple loci in our DNA which increase PD risk. In this chapter, we summarize what is currently known about each of the seven strongly-associated PD genes and select PD risk variants, including PITX3, TMEM106B, SNCA Rep1, APOɛ4, COMT and MAPT H1/H1, along with their respective relationships to cognition.

Association between Polygenic Risk Scores for ADHD and Asthma: A Birth Cohort Investigation

OBJECTIVE

Shared genetic mechanisms have been hypothesized to explain the comorbidity between ADHD and asthma. To evaluate their genetic overlap, we relied on data from the 1982 Pelotas birth cohort to test the association between polygenic risk scores (PRSs) for ADHD (ADHD-PRSs) and asthma, and PRSs for asthma (asthma-PRSs) and ADHD.

METHOD

We analyzed data collected at birth, 2, 22, and 30 years from 3,574 individuals.

RESULTS

Subjects with ADHD had increased risk of having asthma (OR 1.92, 95% CI 1.01-3.66). The association was stronger for females. Our results showed no evidence of association between ADHD-PRSs and asthma or asthma-PRSs and ADHD. However, an exploratory analysis suggested that adult ADHD might be genetically associated with asthma.

CONCLUSION

Our results do not support a shared genetic background between both conditions. Findings should be viewed in light of important limitations, particularly the sample size and the self-reported asthma diagnosis. Studies in larger datasets are required to better explore the genetic overlap between adult ADHD and asthma.

Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.

The effect of polygenic risk on white matter microstructural degeneration in Parkinson's disease: A longitudinal Diffusion Tensor Imaging study

BACKGROUND AND PURPOSE

This study was undertaken to investigate the effect of genetic risk on whole brain white matter (WM) integrity in patients with Parkinson disease (PD).

METHODS

Data were acquired from the Parkinson's Progression Markers Initiative (PPMI) database. Polygenic load was estimated by calculating weighted polygenic risk scores (PRS) using (i) all available 26 PD-risk single nucleotide polymorphisms (SNPs) (PRS1) and (ii) 23 SNPs with minor allele frequency (MAF) > 0.05 (PRS2). According to the PRS2, and combined with clinical and diffusion tensor imaging (DTI) data over 3-year follow-up, 60 PD patients were screened and assigned to the low-PRS group (n = 30) and high-PRS group (n = 30) to investigate intergroup differences in clinical profiles and WM microstructure measured by DTI cross-sectionally and longitudinally.

RESULTS

PRS were associated with younger age at onset in patients with PD (PRS1, Spearman ρ = -0.190, p = 0.003; PRS2, Spearman ρ = -0.189, p = 0.003). The high-PRS group showed more extensive WM microstructural degeneration compared with the low-PRS group, mainly involving the anterior thalamic radiation (AThR) and inferior fronto-occipital fasciculus (IFOF) (p < 0.05). Furthermore, WM microstructural changes in AThR correlated with declining cognitive function (r = -0.401, p = 0.028) and increasing dopaminergic deficits in caudate (r = -0.405, p = 0.030).

CONCLUSIONS

These findings suggest that PD-associated polygenic load aggravates the WM microstructural degeneration and these changes may lead to poor cognition with continuous dopamine depletion. This study provides advanced evidence that combined with a cumulative PRS and DTI methods may predict disease progression in PD patients.

Validity and Prognostic Value of a Polygenic Risk Score for Parkinson's Disease

Idiopathic Parkinson’s disease (PD) is a complex multifactorial disorder caused by the interplay of both genetic and non-genetic risk factors. Polygenic risk scores (PRSs) are one way to aggregate the effects of a large number of genetic variants upon the risk for a disease like PD in a single quantity. However, reassessment of the performance of a given PRS in independent data sets is a precondition for establishing the PRS as a valid tool to this end. We studied a previously proposed PRS for PD in a separate genetic data set, comprising 1914 PD cases and 4464 controls, and were able to replicate its ability to differentiate between cases and controls. We also assessed theoretically the prognostic value of the PD-PRS, i.e., its ability to predict the development of PD in later life for healthy individuals. As it turned out, the PD-PRS alone can be expected to perform poorly in this regard. Therefore, we conclude that the PD-PRS could serve as an important research tool, but that meaningful PRS-based prognosis of PD at an individual level is not feasible.

Mapping the Diverse and Inclusive Future of Parkinson's Disease Genetics and Its Widespread Impact

Over the last decades, genetics has been the engine that has pushed us along on our voyage to understand the etiology of Parkinson's disease (PD). Although a large number of risk loci and causative mutations for PD have been identified, it is clear that much more needs to be done to solve the missing heritability mystery. Despite remarkable efforts, as a field, we have failed in terms of diversity and inclusivity. The vast majority of genetic studies in PD have focused on individuals of European ancestry, leading to a gap of knowledge on the existing genetic differences across populations and PD as a whole. As we move forward, shedding light on the genetic architecture contributing to PD in non-European populations is essential, and will provide novel insight into the generalized genetic map of the disease. In this review, we discuss how better representation of understudied ancestral groups in PD genetics research requires addressing and resolving all the challenges that hinder the inclusion of these populations. We further provide an overview of PD genetics in the clinics, covering the current challenges and limitations of genetic testing and counseling. Finally, we describe the impact of worldwide collaborative initiatives in the field, shaping the future of the new era of PD genetics as we advance in our understanding of the genetic architecture of PD.

Variant rs6749447 (T > G) in the serine threonine kinase gene is associated with cardiovascular complications, the Tampere adult population cardiovascular risk study

We have previously shown an association of STK39 (serine threonine kinase) rs6749447 (T > G) with hypertension in the Tampere adult population cardiovascular risk study in 50-year-old subjects. These 1196 subjects were followed up to the age of 65 years to determine whether rs6749447 is also associated with coronary artery disease (CAD), transient ischemic attack (TIA), or early cardiovascular death.DNA samples were collected by buccal swabs and genotypes were determined by PCR. Hypertension, TIA, and CAD were determined by questionnaire and the National Hospital Discharge Registry. Outcomes for death were collected from the National Statistics Centre. Linkage disequilibrium analysis and gene expression correlations for rs6749447 were done in silico.After following the subjects up to the age of 60 years the rs6749447 G-allele still associated with hypertension (P = .009). The variation did not associate with CAD (P = .959). The risk for TIA was 5.2-fold among G-allele carriers compared to TT genotype even after adjusting for body mass index (P = .036, 95% CI 1.11-24.59). After follow-up of the subjects to the age of 65 years, adjusting for body mass index, the G-allele was associated with 3.2-fold risk of premature cardiovascular death (P = .049, 95% CI 1.00-10.01).In conclusion, the STK39 genetic variant rs6749447 was significantly associated with TIA and premature cardiovascular death in a Finnish cohort. The in silico results of linkage disequilibrium and gene expression analyses also showed associations that were distinct from the retention of salt effect on kidneys proposed earlier for this intronic variation.

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.

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinson's disease

Background

Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinson’s disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD.

Results

Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered.

Conclusions

Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00357-w.

Prediction of Parkinson's Disease Risk Based on Genetic Profile and Established Risk Factors

Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors. Methods: Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors. Results: The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population. Conclusions: These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD.

Polygenic Risk Scores in a Prospective Parkinson's Disease Cohort

BACKGROUND

Ethnic-specific genetic risk assessment framework for Parkinson's disease (PD) is lacking for the Asian population.

OBJECTIVE

We investigated the association of a polygenic risk score (PRS) with PD incidence in a population-based Asian prospective cohort.

METHODS

Genetic, dietary, and lifestyle information were prospectively collected from 25,646 participants within the Singapore Chinese Health Study cohort. PRS was constructed with Asian-specific and top genome-wide association study variants. The association between PRS and PD incidence was evaluated with multivariable Cox proportional hazard models, Kaplan-Meier survival analysis, and concordance statistics.

RESULTS

A total of 333 incident cases were identified after a follow-up period of more than 20 years. Participants with PRS in the top tertile (hazard ratio [HR], 1.81; 95% confidence interval [CI], 1.37-2.39) and middle tertile (HR, 1.35; 95% CI, 1.00-1.83) are at higher risk of developing PD after adjusting for dietary and lifestyle risk factors, with a shorter time to PD event in a Kaplan-Meier survival analysis (P < 0.001).

CONCLUSION

We identified a PRS that was significantly associated with PD incidence in a prospective Chinese cohort after adjusting for dietary and lifestyle factors. © 2021 International Parkinson and Movement Disorder Society.

Trans-Ethnic Fine-Mapping of the Major Histocompatibility Complex Region Linked to Parkinson's Disease

BACKGROUND

Despite evidence for the role of human leukocyte antigen (HLA) in the genetic predisposition to Parkinson's disease (PD), the complex haplotype structure and highly polymorphic feature of the major histocompatibility complex (MHC) region has hampered a unified insight on the genetic risk of PD. In addition, a majority of the reports focused on Europeans, lacking evidence on other populations.

OBJECTIVES

The aim of this study is to elucidate the genetic features of the MHC region associated with PD risk in trans-ethnic cohorts.

METHODS

We conducted trans-ethnic fine-mapping of the MHC region for European populations (14,650 cases and 1,288,625 controls) and East Asian populations (7712 cases and 27,372 controls). We adopted a hybrid fine-mapping approach including both HLA genotype imputation of genome-wide association study (GWAS) data and direct imputation of HLA variant risk from the GWAS summary statistics.

RESULTS

Through trans-ethnic MHC fine-mapping, we identified the strongest associations at amino acid position 13 of HLA-DRβ1 (P = 6.0 × 10-15 ), which explains the majority of the risk in HLA-DRB1. In silico prediction revealed that HLA-DRB1 alleles with histidine at amino acid position 13 (His13) had significantly weaker binding affinity to an α-synuclein epitope than other alleles (P = 9.6 × 10-4 ). Stepwise conditional analysis suggested additional independent associations at Ala69 in HLA-B (P = 1.0 × 10-7 ). A subanalysis in Europeans suggested additional independent associations at non-HLA genes in the class III MHC region (EHMT2; P = 2.5 × 10-7 ).

CONCLUSIONS

Our study highlights the shared and distinct genetic features of the MHC region in patients with PD across ethnicities. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Genetics of Parkinson's Disease and Implications for Clinical Practice

The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.

Interaction of CSF α-synuclein and amyloid beta in cognition and cortical atrophy

INTRODUCTION

Lewy body-related pathology is commonly observed at autopsy in individuals with dementia, but in vivo biomarkers for α-synucleinopathy are lacking.

METHODS

Baseline cerebrospinal fluid (CSF) biomarkers, polygenic risk score (PRS) for Parkinson's disease (PRS-PD) and Alzheimer's disease (PRS-AD), longitudinal cognitive scores, and magnetic resonance imaging were measured in 217 participants from the Alzheimer's Disease Neuroimaging Initiative. Linear mixed models were used to find the relationship of CSF biomarkers and the PRS with cognition and cortical atrophy.

RESULTS

Higher PRS-PD and PRS-AD were associated with lower CSF α-synuclein and amyloid beta (Aβ), respectively. Lower CSF α-synuclein and the interaction of CSF α-synuclein and Aβ were associated with lower cognitive scores and global cortical atrophy most prominently in the occipital cortex.

DISCUSSION

Lower CSF α-synuclein could be a biomarker for α-synucleinopathy, and the simultaneous evaluation of CSF biomarkers for AD and CSF α-synuclein could reveal the independent and interactive effects on cognition and cortical atrophy.

Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

Advancing Personalized Medicine in Common Forms of Parkinson's Disease through Genetics: Current Therapeutics and the Future of Individualized Management

Parkinson’s disease (PD) is a condition with heterogeneous clinical manifestations that vary in age at onset, rate of progression, disease course, severity, motor and non-motor symptoms, and a variable response to antiparkinsonian drugs. It is considered that there are multiple PD etiological subtypes, some of which could be predicted by genetics. The characterization and prediction of these distinct molecular entities provides a growing opportunity to use individualized management and personalized therapies. Dissecting the genetic architecture of PD is a critical step in identifying therapeutic targets, and genetics represents a step forward to sub-categorize and predict PD risk and progression. A better understanding and separation of genetic subtypes has immediate implications in clinical trial design by unraveling the different flavors of clinical presentation and development. Personalized medicine is a nascent area of research and represents a paramount challenge in the treatment and cure of PD. This manuscript summarizes the current state of precision medicine in the PD field and discusses how genetics has become the engine to gain insights into disease during our constant effort to develop potential etiological based interventions.

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.

Genetic Risk Profiling in Parkinson's Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways

Parkinson's disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ''complex'' PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies and how this may be utilized to generate polygenic risk scores (PRS), which may be used in the prediction of risk and trajectory of PD. We also comment on how pathway-specific genetic profiling can be used to gain insight into PD-related biological pathways, and how this may be further utilized to nominate causal PD genes and potentially druggable therapeutic targets. Finally, we outline the current limits of our understanding of PD genetics and the potential contribution of variation currently uncaptured in genetic studies, focusing here on uncatalogued structural variants.

The PARK2 Mutation Associated with Parkinson's Disease Enhances the Vulnerability of Peripheral Blood Lymphocytes to Paraquat

Parkinson's disease (PD) is the second most common neurodegenerative disease in middle-aged and elderly people. However, the etiology and pathogenesis of PD are still unclear and there is a lack of reliable biomarkers for early molecular diagnosis. Parkin (encoded by PARK2) is a ubiquitin E3 ligase that participates in mitochondrial homeostasis, the ubiquitin-proteasome pathway, oxidative stress response, and cell death pathways, which are involved in the pathogenesis of PD. However, Parkin is also expressed in peripheral blood lymphocytes (PBLs). In this study, permanent lymphocyte lines were established from the peripheral blood of sporadic PD (sPD) patients, PARK2 mutation carriers, and healthy controls. Reactive oxygen species (ROS), function of the mitochondrial respiratory chain complex I, and apoptosis were analyzed in the PBLs. There was no significant difference in ROS, mitochondrial respiratory chain complex I, and apoptosis between the experimental groups and the control group without paraquat treatment. Compared with the control group of healthy subjects, we found an increase of ROS (control 100 ± 0, sPD 275.53 ± 79.11, and C441R 340 ± 99.67) and apoptosis, as well as a decline in the function of mitochondrial respiratory chain complex I in PBLs of PARK2 mutation carriers and sPD after the treatment of paraquat (control 0.65 ± 0.08, sPD 0.44 ± 0.08, and C441R 0.32 ± 0.08). Moreover, overexpression of the wild-type (WT) PARK2 in HeLa cells and immortalized PBLs could rescue mitochondrial function and partially inhibit apoptosis following paraquat treatment, while the C441R mutation could not. Thus, ROS levels, activity of mitochondrial respiratory chain complex I, and apoptosis of PBLs are potential diagnostic biomarkers of PD.

The multi-faceted role of mitochondria in the pathology of Parkinson's disease

Mitochondria are essential for neuronal function. They produce ATP to meet energy demands, regulate homeostasis of ion levels such as calcium and regulate reactive oxygen species that cause oxidative cellular stress. Mitochondria have also been shown to regulate protein synthesis within themselves, as well as within the nucleus, and also influence synaptic plasticity. These roles are especially important for neurons, which have higher energy demands and greater susceptibility to stress. Dysfunction of mitochondria has been associated with several neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease, Huntington's disease, Glaucoma and Amyotrophic Lateral Sclerosis. The focus of this review is on how and why mitochondrial function is linked to the pathology of Parkinson's disease (PD). Many of the PD-linked genetic mutations which have been identified result in dysfunctional mitochondria, through a wide-spread number of mechanisms. In this review, we describe how susceptible neurons are predisposed to be vulnerable to the toxic events that occur during the neurodegenerative process of PD, and how mitochondria are central to these pathways. We also discuss ways in which proteins linked with familial PD control mitochondrial function, both physiologically and pathologically, along with their implications in genome-wide association studies and risk assessment. Finally, we review potential strategies for disease modification through mitochondrial enhancement. Ultimately, agents capable of both improving and/or restoring mitochondrial function, either alone, or in conjunction with other disease-modifying agents may halt or slow the progression of neurodegeneration in Parkinson's disease.

Polygenic risk and pleiotropy in neurodegenerative diseases

In this paper we explore the phenomenon of pleiotropy in neurodegenerative diseases, focusing on Alzheimer's disease (AD). We summarize the various techniques developed to investigate pleiotropy among traits, elaborating in the polygenic risk scores (PRS) analysis. PRS was designed to assess a cumulative effect of a large number of SNPs for association with a disease and, later for disease risk prediction. Since genetic predictions rely on heritability, we discuss SNP-based heritability from genome-wide association studies and its contribution to the prediction accuracy of PRS. We review work examining pleiotropy in neurodegenerative diseases and related phenotypes and biomarkers. We conclude that the exploitation of pleiotropy may aid in the identification of novel genes and provide further insights in the disease mechanisms, and along with PRS analysis, may be advantageous for precision medicine.

Revision of Diagnosis in Early Parkinsonism with Abnormal Dopamine Transporter Imaging

BACKGROUND

In patients with early parkinsonism, misdiagnosis may occur in >30% of cases. This can have detrimental consequences clinically and in clinical trials. Dopamine transporter (DAT) SPECT imaging can help improve diagnostic accuracy.

OBJECTIVE

To describe characteristics of individuals initially diagnosed with idiopathic Parkinson's disease (iPD) and with abnormal DAT SPECT imaging who had a change in diagnosis on follow-up.

METHODS

Data were obtained from the biomarker study Parkinson's Progression Markers Initiative (PPMI). PPMI is a multicenter, observational study that enrolled 423 individuals with a diagnosis of iPD of ≤2 years duration and with abnormal DAT SPECT imaging. Participants were assessed at least annually, and diagnosis was documented by the site neurologist. Characteristics of those that had a change in diagnosis were compared to those with stable diagnosis.

RESULTS

390 subjects were included. Eight (2%) had a change in diagnosis. The diagnosis was changed to multiple system atrophy in 5 cases, dementia with Lewy bodies in 2, and corticobasal degeneration in 1. Revision of diagnosis occurred 2-5.2 years from enrollment. Mean motor score was higher (26.9 vs 20.6; p = 0.01), DAT binding lower (1.056 vs 1.406; p = 0.01), genetic risk score lower (-0.016 vs -0.022; p = 0.0470), and olfaction score higher (28.75 vs 22.05; p = 0.03) in those whose diagnosis changed compared to those who did not.

CONCLUSION

Diagnosis remained stable in most individuals with early parkinsonism diagnosed with iPD and with abnormal DAT imaging. A small number had a revision in diagnosis. Clinical and biomarker abnormalities were greater at baseline in those whose diagnosis changed.

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, looking for not only motor symptomatology but also non-motor complications, including cognitive decline, sleep problems and mood disturbances. Being neurodegenerative in nature, PD is expected to inflict a continuous degradation in patients' condition over time. The rate of symptoms progression, however, is found to be even more chaotic than the vastly different phenotypes that can be expressed in the initial stages of PD. In this work, an analysis of baseline PD characteristics is performed using machine learning techniques, to identify prognostic factors for early rapid progression of PD symptoms. Using open data from the Parkinson's Progression Markers Initiative (PPMI) study, an extensive set of baseline patient evaluation outcomes is examined to isolate determinants of rapid progression within the first two and four years of PD. The rate of symptoms progression is estimated by tracking the change of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score over the corresponding follow-up period. Patients are ranked according to their progression rates and those who expressed the highest rates of MDS-UPDRS total score increase per year of follow-up period are assigned into the rapid progression class, using 5- and 10-quantiles partition. Classification performance against the rapid progression class was evaluated in a per quantile partition analysis scheme and in quantile-independent approach, respectively. The results shown a more accurate patient discrimination with quantile partitioning, however, a much more compact subset of baseline factors is extracted in the latter, making a more suitable for actual interventions in practice. Classification accuracy improved in all cases when using the longer 4-year follow-up period to estimate PD progression, suggesting that a prolonged patient evaluation can provide better outcomes in identifying rapid progression phenotype. Non-motor symptoms are found to be the main determinants of rapid symptoms progression in both follow-up periods, with autonomic dysfunction, mood impairment, anxiety, REM sleep behavior disorders, cognitive decline and memory impairment being alarming signs at baseline evaluation, along with rigidity symptoms, certain laboratory blood test results and genetic mutations.

Whole Exome Sequencing Study of Parkinson Disease and Related Endophenotypes in the Italian Population

Parkinson Disease (PD) is a complex neurodegenerative disorder characterized by large genetic heterogeneity and missing heritability. Since the genetic background of PD can partly vary among ethnicities and neurological scales have been scarcely investigated in a PD setting, we performed an exploratory Whole Exome Sequencing (WES) analysis of 123 PD patients from mainland Italy, investigating scales assessing motor (UPDRS), cognitive (MoCA), and other non-motor symptoms (NMS). We performed variant prioritization, followed by targeted association testing of prioritized variants in 446 PD cases and 211 controls. Then we ran Exome-Wide Association Scans (EWAS) within sequenced PD cases (N = 113), testing both motor and non-motor PD endophenotypes, as well as their associations with Polygenic Risk Scores (PRS) influencing brain subcortical volumes. We identified a variant associated with PD, rs201330591 in GTF2H2 (5q13; alternative T allele: OR [CI] = 8.16[1.08; 61.52], FDR = 0.048), which was not replicated in an independent cohort of European ancestry (1,148 PD cases, 503 controls). In the EWAS, polygenic analyses revealed statistically significant multivariable associations of amygdala- [β(SE) = -0.039(0.013); FDR = 0.039] and caudate-PRS [0.043(0.013); 0.028] with motor symptoms. All subcortical PRSs in a multivariable model notably increased the variance explained in motor (adjusted-R2 = 38.6%), cognitive (32.2%) and other non-motor symptoms (28.9%), compared to baseline models (~20%). Although, the small sample size warrants further replications, these findings suggest shared genetic architecture between PD symptoms and subcortical structures, and provide interesting clues on PD genetic and neuroimaging features.

Ethical issues in susceptibility genetic testing for late-onset neurodegenerative diseases

Genome-wide association studies have revolutionized our understanding of the genetic architecture of complex traits and diseases over the last decade. This knowledge is enabling clinicians, researchers, and direct-to-consumer genetics companies to conduct disease susceptibility testing based on powerful methods such as polygenic risk scoring. However, these technologies raise a set of complex ethical, legal, social, and policy considerations. Here we review and discuss a series of ethical dilemmas associated with susceptibility genetic testing for the two most common late-onset neurodegenerative diseases, Alzheimer's and Parkinson's disease, including testing in asymptomatic individuals. Among others, these include informed consent, disclosure of results and unexpected findings, mandatory screening, privacy and confidentiality, and stigma and genetic discrimination. Importantly, appropriate counseling is a deciding factor for the ethical soundness of genetic testing, which poses a challenge for the regulation of these tests and the training of healthcare professionals. As genetic knowledge about these diseases continues growing and genetic testing becomes more widespread, it is increasingly important to raise awareness among researchers, medical practitioners, genetic counselors, and decision makers about the ethical, legal, and social issues associated with genetic testing for polygenic diseases.

Association of Acquired and Heritable Factors With Intergenerational Differences in Age at Symptomatic Onset of Alzheimer Disease Between Offspring and Parents With Dementia

IMPORTANCE

Acquired and heritable traits are associated with dementia risk; however, how these traits are associated with age at symptomatic onset (AAO) of Alzheimer disease (AD) is unknown. Identifying the associations of acquired and heritable factors with variability in intergenerational AAO of AD could facilitate diagnosis, assessment, and counseling of the offspring of parents with AD.

OBJECTIVE

To quantify the associations of acquired and heritable factors with intergenerational differences in AAO of AD.

DESIGN, SETTING, AND PARTICIPANTS

This nested cohort study used data from the Knight Alzheimer Disease Research Center that included community-dwelling participants with symptomatic AD, parental history of dementia, and available DNA data who were enrolled in prospective studies of memory and aging from September 1, 2005, to August 31, 2016. Clinical, biomarker, and genetic data were extracted on January 17, 2017, and data analyses were conducted from July 1, 2017, to August 20, 2019.

MAIN OUTCOMES AND MEASURES

The associations of acquired (ie, years of education; body mass index; history of cardiovascular disease, hypertension, hypercholesterolemia, diabetes, active depression within 2 years, traumatic brain injury, tobacco use, and unhealthy alcohol use; and retrospective determination of AAO) and heritable factors (ie, ethnicity/race, paternal or maternal inheritance, parental history of early-onset dementia, APOE ε4 allele status, and AD polygenic risk scores) to intergenerational difference in AAO of AD were quantified using stepwise forward multivariable regression. Missense or frameshift variants within genes associated with AD pathogenesis were screened using whole-exome sequencing.

RESULTS

There were 164 participants with symptomatic AD, known parental history of dementia, and available DNA data (mean [SD] age, 70.9 [8.3] years; 90 [54.9%] women) included in this study. Offspring were diagnosed with symptomatic AD a mean (SD) 6.1 (10.7) years earlier than their parents (P < .001). The adjusted R2 for measured acquired and heritable factors for intergenerational difference in AAO of AD was 0.29 (F8,155 = 9.13; P < .001). Paternal (β = -9.52 [95% CI, -13.79 to -5.25]) and maternal (β = -6.68 [95% CI, -11.61 to -1.75]) history of dementia, more years of education (β = -0.58 [95% CI -1.08 to -0.09]), and retrospective determination of AAO (β = -3.46 [95% CI, -6.40 to -0.52]) were associated with earlier-than-expected intergenerational difference in AAO of AD. Parental history of early-onset dementia (β = 21.30 [95% CI, 15.01 to 27.59]), presence of 1 APOE ε4 allele (β = 5.00 [95% CI, 2.11 to 7.88]), and history of hypertension (β = 3.81 [95% CI, 0.88 to 6.74]) were associated with later-than-expected intergenerational difference in AAO of AD. Missense or frameshift variants within genes associated with AD pathogenesis were more common in participants with the greatest unexplained variability in intergenerational AAO of AD (19 of 48 participants [39.6%] vs 26 of 116 participants [22.4%]; P = .03).

CONCLUSIONS AND RELEVANCE

Acquired and heritable factors were associated with a substantial proportion of variability in intergenerational AAO of AD. Variants in genes associated with AD pathogenesis may contribute to unexplained variability, justifying further study.

Longitudinal analyses of cerebrospinal fluid α-Synuclein in prodromal and early Parkinson's disease

BACKGROUND

Aggregation of α-synuclein is central to the pathophysiology of PD. Biomarkers related to α-synuclein may be informative for PD diagnosis/progression.

OBJECTIVES

To analyze α-synuclein in CSF in drug-naïve PD, healthy controls, and prodromal PD in the Parkinson's Progression Markers Initiative.

METHODS

Over up to 36-month follow-up, CSF total α-synuclein and its association with MDS-UPDRS motor scores, cognitive assessments, and dopamine transporter imaging were assessed.

RESULTS

The inception cohort included PD (n = 376; age [mean {standard deviation} years]: 61.7 [9.62]), healthy controls (n = 173; age, 60.9 [11.3]), hyposmics (n = 16; age, 68.3 [6.15]), and idiopathic rapid eye movement sleep behavior disorder (n = 32; age, 69.3 [4.83]). Baseline CSF α-synuclein was lower in manifest and prodromal PD versus healthy controls. Longitudinal α-synuclein decreased significantly in PD at 24 and 36 months, did not change in prodromal PD over 12 months, and trended toward an increase in healthy controls. The decrease in PD was not shown when CSF samples with high hemoglobin concentration were removed from the analysis. CSF α-synuclein changes did not correlate with longitudinal MDS-UPDRS motor scores or dopamine transporter scan.

CONCLUSIONS

CSF α-synuclein decreases early in the disease, preceding motor PD. CSF α-synuclein does not correlate with progression and therefore does not reflect ongoing dopaminergic neurodegeneration. Decreased CSF α-synuclein may be an indirect index of changes in the balance between α-synuclein secretion, solubility, or aggregation in the brain, reflecting its overall turnover. Additional biomarkers more directly related to α-synuclein pathophysiology and disease progression and other markers to be identified by, for example, proteomics and metabolomics are needed. © 2019 International Parkinson and Movement Disorder Society.

Effect of polygenic load on striatal dopaminergic deterioration in Parkinson disease

OBJECTIVE

To investigate the effect of polygenic load on the progression of striatal dopaminergic dysfunction in patients with Parkinson disease (PD).

METHODS

Using data from 335 patients with PD in the Parkinson's Progression Markers Initiative (PPMI) database, we investigated the longitudinal association of PD-associated polygenic load with changes in striatal dopaminergic activity as measured by ¹²³I-N-3-fluoropropyl-2-β-carboxymethoxy-3β-(4-iodophenyl) nortropane (¹²³I-FP-CIT) SPECT over 4 years. PD-associated polygenic load was estimated by calculating weighted genetic risk scores (GRS) using 1) all available 27 PD-risk single nucleotide polymorphisms (SNPs) in the PPMI database (GRS1) and 2) 23 SNPs with minor allele frequency >0.05 (GRS2).

RESULTS

GRS1 and GRS2 were correlated with younger age at onset in patients with PD (GRS1, Spearman ρ = -0.128, p = 0.019; GRS2, Spearman ρ = -0.109, p = 0.047). Although GRS1 did not show an association with changes in striatal ¹²³I-FP-CIT availability, GRS2 was associated with a slower decline of striatal dopaminergic activity (interactions with disease duration in linear mixed model; caudate nucleus, estimate = 0.399, SE = 0.165, p = 0.028; putamen, estimate = 0.396, SE = 0.137, p = 0.016).

CONCLUSIONS

Our results suggest that genetic factors for PD risk may have heterogeneous effects on striatal dopaminergic degeneration, and some factors may be associated with a slower decline of dopaminergic activity. Composition of PD progression-specific GRS may be useful in predicting disease progression in patients.

Association of the Polygenic Risk Score with the Incidence Risk of Parkinson's Disease and Cerebrospinal Fluid α-Synuclein in a Chinese Cohort

Parkinson's disease (PD) is attributed to interactions among genes and environmental and lifestyle factors, but the genetic architecture of PD is complex and not completely understood. To evaluate whether the genetic profile modifies PD development and cerebrospinal fluid (CSF) pathological biomarkers, we enrolled 418 PD patients and 426 age- and sex-matched normal controls. Forty-six single nucleotide polymorphisms (SNPs) that were reported to be significantly associated with PD in large-scale genome-wide association studies (GWASs) were genotyped and analysed. The alleles associated with PD were used to build polygenic risk score (PRS) models to represent polygenic risk. The Cox proportional hazards model and receiver operating characteristic (ROC) analyses were used to evaluate the prediction value of the PRS for PD risk and age at onset. The CSF α-synuclein levels were measured in a subgroup of control subjects (n = 262), and its relationship with the PRS was analysed. We found that some SNPs identified from other populations had significant correlations with PD in our Chinese cohort. The PRS we built had prediction value for PD risk and age at onset. The CSF α-synuclein level had no correlation with the PRS in normal subjects.

Impact of Dopamine Oxidation on Dopaminergic Neurodegeneration

Parkinson's disease (PD) is the second most common neurodegenerative disease. The characteristic feature of PD is the progressive degeneration of the dopaminergic (DAergic) neurons in the substantia nigra (SN). DAergic neurons in the SN accumulate black and insoluble membrane structures known as neuromelanin during aging. The oxidation of dopamine (DA) to form neuromelanin generates many o-quinones, including DA o-quinones, aminochrome, and 5,6-indolequinone. The focus of this review is to discuss the role of DA oxidation in association with PD. The oxidation of DA produces oxidative products, inducing mitochondrial dysfunction, impaired protein degradation, α-synuclein aggregation into neurotoxic oligomers, and oxidative stress, in vitro. Recent studies have demonstrated that the DA content is critical for both DJ-1 knockout and A53T α-synuclein transgenic mice to develop PD pathological features, providing evidence for DA action in PD pathogenesis in vivo. The effects of L-DOPA, as the most effective anti-PD drug, are also briefly discussed.

Transplantation of Human Neural Progenitor Cells (NPC) into Putamina of Parkinsonian Patients: A Case Series Study, Safety and Efficacy Four Years after Surgery

Individuals with Parkinson’s disease (PD) suffer from motor and mental disturbances due to degeneration of dopaminergic and non-dopaminergic neuronal systems. Although they provide temporary symptom relief, current treatments fail to control motor and non-motor alterations or to arrest disease progression. Aiming to explore safety and possible motor and neuropsychological benefits of a novel strategy to improve the PD condition, a case series study was designed for brain grafting of human neural progenitor cells (NPCs) to a group of eight patients with moderate PD. A NPC line, expressing Oct-4 and Sox-2, was manufactured and characterized. Using stereotactic surgery, NPC suspensions were bilaterally injected into patients’ dorsal putamina. Cyclosporine A was given for 10 days prior to surgery and continued for 1 month thereafter. Neurological, neuropsychological, and brain imaging evaluations were performed pre-operatively, 1, 2, and 4 years post-surgery. Seven of eight patients have completed 4-year follow-up. The procedure proved to be safe, with no immune responses against the transplant, and no adverse effects. One year after cell grafting, all but one of the seven patients completing the study showed various degrees of motor improvement, and five of them showed better response to medication. PET imaging showed a trend toward enhanced midbrain dopaminergic activity. By their 4-year evaluation, improvements somewhat decreased but remained better than at baseline. Neuropsychological changes were minor, if at all. The intervention appears to be safe. At 4 years post-transplantation we report that undifferentiated NPCs can be delivered safely by stereotaxis to both putamina of patients with PD without causing adverse effects. In 6/7 patients in OFF condition improvement in UPDRS III was observed. PET functional scans suggest enhanced putaminal dopaminergic neurotransmission that could correlate with improved motor function, and better response to L-DOPA. Patients’ neuropsychological scores were unaffected by grafting. Trial Registration: Fetal derived stem cells for Parkinson’s disease https://doi.org/10.1186/ISRCTN39104513Reg#ISRCTN39104513

The Genetics of Dementia with Lewy Bodies: Current Understanding and Future Directions

PURPOSE OF REVIEW

Dementia with Lewy bodies (DLB) is a neurodegenerative disease that can be clinically and pathologically similar to Parkinson's disease (PD) and Alzheimer's disease (AD). Current understanding of DLB genetics is insufficient and has been limited by sample size and difficulty in diagnosis. The first genome-wide association study (GWAS) in DLB was performed in 2017; a time at which the post-GWAS era has been reached in many diseases.

RECENT FINDINGS

DLB shares risk loci with AD, in the APOE E4 allele, and with PD, in variation at GBA and SNCA. Interestingly, the GWAS suggested that DLB may also have genetic risk factors that are distinct from those in AD and PD. Although off to a slow start, recent studies have reinvigorated the field of DLB genetics and these results enable us to start to have a more complete understanding of the genetic architecture of this disease.

Cellular and Molecular Basis of Neurodegeneration in Parkinson Disease

It has been 200 years since Parkinson disease (PD) was described by Dr. Parkinson in 1817. The disease is the second most common neurodegenerative disease characterized by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Although the pathogenesis of PD is still unknown, the research findings from scientists are conducive to understand the pathological mechanisms. It is well accepted that both genetic and environmental factors contribute to the onset of PD. In this review, we summarize the mutations of main seven genes (α-synuclein, LRRK2, PINK1, Parkin, DJ-1, VPS35 and GBA1) linked to PD, discuss the potential mechanisms for the loss of dopaminergic neurons (dopamine metabolism, mitochondrial dysfunction, endoplasmic reticulum stress, impaired autophagy, and deregulation of immunity) in PD, and expect the development direction for treatment of PD.