Gene-Environment Interactions for Parkinson's Disease.

OBJECTIVE: Parkinson's disease (PD) is a neurodegenerative disorder with complex etiology. Multiple genetic and environmental factors have been associated with PD, but most PD risk remains unexplained. The aim of this study was to test for statistical interactions between PD-related genetic and environmental exposures in the 23andMe, Inc. research dataset. METHODS: Using a validated PD polygenic risk score and common PD-associated variants in the GBA gene, we explored interactions between genetic susceptibility factors and 7 lifestyle and environmental factors: body mass index (BMI), type 2 diabetes (T2D), tobacco use, caffeine consumption, pesticide exposure, head injury, and physical activity (PA). RESULTS: We observed that T2D, as well as higher BMI, caffeine consumption, and tobacco use, were associated with lower odds of PD, whereas head injury, pesticide exposure, GBA carrier status, and PD polygenic risk score were associated with higher odds. No significant association was observed between PA and PD. In interaction analyses, we found statistical evidence for an interaction between polygenic risk of PD and the following environmental/lifestyle factors: T2D (p = 6.502 × 10-8), PA (p = 8.745 × 10-5), BMI (p = 4.314 × 10-4), and tobacco use (p = 2.236 × 10-3). Although BMI and tobacco use were associated with lower odds of PD regardless of the extent of individual genetic liability, the direction of the relationship between odds of PD and T2D, as well as PD and PA, varied depending on polygenic risk score. INTERPRETATION: We provide preliminary evidence that associations between some environmental and lifestyle factors and PD may be modified by genotype. ANN NEUROL 2024;95:677-687.

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.

Characterizing the Genetic Architecture of Parkinson's Disease in Latinos.

OBJECTIVE: This work was undertaken in order to identify Parkinson's disease (PD) risk variants in a Latino cohort, to describe the overlap in the genetic architecture of PD in Latinos compared to European-ancestry subjects, and to increase the diversity in PD genome-wide association (GWAS) data. METHODS: We genotyped and imputed 1,497 PD cases and controls recruited from nine clinical sites across South America. We performed a GWAS using logistic mixed models; variants with a p-value <1 × 10-5 were tested in a replication cohort of 1,234 self-reported Latino PD cases and 439,522 Latino controls from 23andMe, Inc. We also performed an admixture mapping analysis where local ancestry blocks were tested for association with PD status. RESULTS: One locus, SNCA, achieved genome-wide significance (p-value <5 × 10-8 ); rs356182 achieved genome-wide significance in both the discovery and the replication cohorts (discovery, G allele: 1.58 OR, 95% CI 1.35-1.86, p-value 2.48 × 10-8 ; 23andMe, G allele: 1.26 OR, 95% CI 1.16-1.37, p-value 4.55 × 10-8 ). In our admixture mapping analysis, a locus on chromosome 14, containing the gene STXBP6, achieved significance in a joint test of ancestries and in the Native American single-ancestry test (p-value <5 × 10-5 ). A second locus on chromosome 6, containing the gene RPS6KA2, achieved significance in the African single-ancestry test (p-value <5 × 10-5 ). INTERPRETATION: This study demonstrated the importance of the SNCA locus for the etiology of PD in Latinos. By leveraging the demographic history of our cohort via admixture mapping, we identified two potential PD risk loci that merit further study. ANN NEUROL 2021;90:353-365.

Advancing drug discovery using the power of the human genome.

Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Evaluating Lipid-Lowering Drug Targets for Parkinson's Disease Prevention with Mendelian Randomization.

Long-term exposure to lipid-lowering drugs might affect Parkinson's disease (PD) risk. We conducted Mendelian randomization analyses where genetic variants indexed expected effects of modulating lipid-lowering drug targets on PD. Statin exposure was not predicted to increase PD risk, although results were not precise enough to support benefits for prevention clearly (odds ratio [OR] = 0.83; 95% confidence interval [CI] = 0.65, 1.07). Other target results were null, except for variants indicating Apolipoprotein-A5 or Apolipoprotein-C3 inhibition might confer protection. These findings suggest peripheral lipid variation may not have a prominent role in PD etiology, but some related drug targets could influence PD via alternate pathways. ANN NEUROL 2020;88:1043-1047.

Fine-Mapping of SNCA in Rapid Eye Movement Sleep Behavior Disorder and Overt Synucleinopathies.

OBJECTIVE: Rapid eye movement sleep behavior disorder (RBD) is a prodromal synucleinopathy, as >80% will eventually convert to overt synucleinopathy. We performed an in-depth analysis of the SNCA locus to identify RBD-specific risk variants. METHODS: Full sequencing and genotyping of SNCA was performed in isolated/idiopathic RBD (iRBD, n = 1,076), Parkinson disease (PD, n = 1,013), dementia with Lewy bodies (DLB, n = 415), and control subjects (n = 6,155). The iRBD cases were diagnosed with RBD prior to neurodegeneration, although some have since converted. A replication cohort from 23andMe of PD patients with probable RBD (pRBD) was also analyzed (n = 1,782 cases; n = 131,250 controls). Adjusted logistic regression models and meta-analyses were performed. Effects on conversion rate were analyzed in 432 RBD patients with available data using Kaplan-Meier survival analysis. RESULTS: A 5'-region SNCA variant (rs10005233) was associated with iRBD (odds ratio [OR] = 1.43, p = 1.1E-08), which was replicated in pRBD. This variant is in linkage disequilibrium (LD) with other 5' risk variants across the different synucleinopathies. An independent iRBD-specific suggestive association (rs11732740) was detected at the 3' of SNCA (OR = 1.32, p = 4.7E-04, not statistically significant after Bonferroni correction). Homozygous carriers of both iRBD-specific SNPs were at highly increased risk for iRBD (OR = 5.74, p = 2E-06). The known top PD-associated variant (3' variant rs356182) had an opposite direction of effect in iRBD compared to PD. INTERPRETATION: There is a distinct pattern of association at the SNCA locus in RBD as compared to PD, with an opposite direction of effect at the 3' of SNCA. Several 5' SNCA variants are associated with iRBD and with pRBD in overt synucleinopathies. ANN NEUROL 2020;87:584-598.

Genetic modifiers of risk and age at onset in GBA associated Parkinson's disease and Lewy body dementia.

Parkinson's disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson's disease, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson's disease and Lewy body dementia. These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known Parkinson's disease risk variants. Using multiple, large case-control datasets, totalling 217 165 individuals (22 757 Parkinson's disease cases, 13 431 Parkinson's disease proxy cases, 622 Lewy body dementia cases and 180 355 controls), we identified 1691 Parkinson's disease cases, 81 Lewy body dementia cases, 711 proxy cases and 7624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent Parkinson's disease-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall Parkinson's disease genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S induced pluripotent cell-derived neurons were shown to have decreased cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated Parkinson's disease risk and age at onset, although the total contribution of common genetics variants is not large. We further demonstrate that common variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have implications for selection of GBA carriers for therapeutic interventions.

Parkinson's disease determinants, prediction and gene-environment interactions in the UK Biobank.

OBJECTIVE: To systematically investigate the association of environmental risk factors and prodromal features with incident Parkinson's disease (PD) diagnosis and the interaction of genetic risk with these factors. To evaluate whether existing risk prediction algorithms are improved by the inclusion of genetic risk scores. METHODS: We identified individuals with an incident diagnosis of PD (n=1276) and controls (n=500 406) in UK Biobank. We determined the association of risk factors with incident PD using adjusted logistic regression models. We constructed polygenic risk scores (PRSs) using external weights and selected the best PRS from a subset of the cohort (30%). The PRS was used in a separate testing set (70%) to examine gene-environment interactions and compare predictive models for PD. RESULTS: Strong evidence of association (false discovery rate <0.05) was found between PD and a positive family history of PD, a positive family history of dementia, non-smoking, low alcohol consumption, depression, daytime somnolence, epilepsy and earlier menarche. Individuals with the highest 10% of PRSs had increased risk of PD (OR 3.37, 95% CI 2.41 to 4.70) compared with the lowest risk decile. A higher PRS was associated with earlier age at PD diagnosis and inclusion of the PRS in the PREDICT-PD algorithm led to a modest improvement in model performance. We found evidence of an interaction between the PRS and diabetes. INTERPRETATION: Here, we used UK Biobank data to reproduce several well-known associations with PD, to demonstrate the validity of a PRS and to demonstrate a novel gene-environment interaction, whereby the effect of diabetes on PD risk appears to depend on background genetic risk for PD.

The Parkinson's Disease Mendelian Randomization Research Portal.

BACKGROUND: Mendelian randomization is a method for exploring observational associations to find evidence of causality. OBJECTIVE: To apply Mendelian randomization between risk factors/phenotypic traits (exposures) and PD in a large, unbiased manner, and to create a public resource for research. METHODS: We used two-sample Mendelian randomization in which the summary statistics relating to single-nucleotide polymorphisms from 5,839 genome-wide association studies of exposures were used to assess causal relationships with PD. We selected the highest-quality exposure genome-wide association studies for this report (n = 401). For the disease outcome, summary statistics from the largest published PD genome-wide association studies were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted method, followed by a range of sensitivity analyses. We used a false discovery rate of 5% from the inverse variance weighted analysis to prioritize exposures of interest. RESULTS: We observed evidence for causal associations between 12 exposures and risk of PD. Of these, nine were effects related to increasing adiposity and decreasing risk of PD. The remaining top three exposures that affected PD risk were tea drinking, time spent watching television, and forced vital capacity, but these may have been biased and were less convincing. Other exposures at nominal statistical significance included inverse effects of smoking and alcohol. CONCLUSIONS: We present a new platform which offers Mendelian randomization analyses for a total of 5,839 genome-wide association studies versus the largest PD genome-wide association studies available (https://pdgenetics.shinyapps.io/MRportal/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Parkinson's disease age at onset genome-wide association study: Defining heritability, genetic loci, and α-synuclein mechanisms.

BACKGROUND: Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. OBJECTIVES: To identify the genetic determinants of PD age at onset. METHODS: Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. RESULTS: We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. CONCLUSIONS: Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society.

The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa.

Antibiotic resistance carries a fitness cost that must be overcome in order for resistance to persist over the long term. Compensatory mutations that recover the functional defects associated with resistance mutations have been argued to play a key role in overcoming the cost of resistance, but compensatory mutations are expected to be rare relative to generally beneficial mutations that increase fitness, irrespective of antibiotic resistance. Given this asymmetry, population genetics theory predicts that populations should adapt by compensatory mutations when the cost of resistance is large, whereas generally beneficial mutations should drive adaptation when the cost of resistance is small. We tested this prediction by determining the genomic mechanisms underpinning adaptation to antibiotic-free conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that carry costly antibiotic resistance mutations. Whole-genome sequencing revealed that populations founded by high-cost rifampicin-resistant mutants adapted via compensatory mutations in three genes of the RNA polymerase core enzyme, whereas populations founded by low-cost mutants adapted by generally beneficial mutations, predominantly in the quorum-sensing transcriptional regulator gene lasR. Even though the importance of compensatory evolution in maintaining resistance has been widely recognized, our study shows that the roles of general adaptation in maintaining resistance should not be underestimated and highlights the need to understand how selection at other sites in the genome influences the dynamics of resistance alleles in clinical settings.

Discriminating selection on lateral plate phenotype and its underlying gene, Ectodysplasin, in threespine stickleback.

When a signature of natural selection is discovered on a gene that is pleiotropic or in tight linkage with other genes, it is challenging to determine which of the affected phenotypes is under selection. One way to make progress is to employ methods for analyzing natural selection on correlated traits, including both genotype and phenotype. We used this approach in threespine stickleback to estimate selection on a rapidly evolving trait, lateral armor plates, while controlling for variation at its major underlying gene, Ectodysplasin (Eda), and vice versa. This allowed for independent estimates of selection on lateral plates and on Eda via other traits. Previously, we demonstrated allele frequency changes at Eda in a pond experiment. Here we show that this resulted from selection on both plates and on Eda, implying additional selection on other phenotypic traits affected by the same gene. This represents the first evidence for direct selection on lateral plates independent of selection on the Eda locus and highlights the value of measuring selection on both phenotypes and genotypes in studies of adaptation.

Analysis of rare Parkinson's disease variants in millions of people.

Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of rare PD variants. We assessed a total of 27,590 PD cases, 6701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies. The meta-analysis resulted in five significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. Another eight variants are strong candidate variants for their association with PD. Here, we provide the largest rare variant meta-analysis to date, providing information on confirmed and newly identified variants for their association with PD using several large databases. Additionally we also show the complexities of studying rare variants in large-scale cohorts.

Identifying drug targets for schizophrenia through gene prioritization.

Background: Schizophrenia genome-wide association studies (GWASes) have identified >250 significant loci and prioritized >100 disease-related genes. However, gene prioritization efforts have mostly been restricted to locus-based methods that ignore information from the rest of the genome. Methods: To more accurately characterize genes involved in schizophrenia etiology, we applied a combination of highly-predictive tools to a published GWAS of 67,390 schizophrenia cases and 94,015 controls. We combined both locus-based methods (fine-mapped coding variants, distance to GWAS signals) and genome-wide methods (PoPS, MAGMA, ultra-rare coding variant burden tests). To validate our findings, we compared them with previous prioritization efforts, known neurodevelopmental genes, and results from the PsyOPS tool. Results: We prioritized 62 schizophrenia genes, 41 of which were also highlighted by our validation methods. In addition to DRD2, the principal target of antipsychotics, we prioritized 9 genes that are targeted by approved or investigational drugs. These included drugs targeting glutamatergic receptors (GRIN2A and GRM3), calcium channels (CACNA1C and CACNB2), and GABAB receptor (GABBR2). These also included genes in loci that are shared with an addiction GWAS (e.g. PDE4B and VRK2). Conclusions: We curated a high-quality list of 62 genes that likely play a role in the development of schizophrenia. Developing or repurposing drugs that target these genes may lead to a new generation of schizophrenia therapies. Rodent models of addiction more closely resemble the human disorder than rodent models of schizophrenia. As such, genes prioritized for both disorders could be explored in rodent addiction models, potentially facilitating drug development.

Multi-ancestry genome-wide association meta-analysis of Parkinson's disease.

Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations.

Bidirectional relationship between olfaction and Parkinson's disease.

Background: Hyposmia (loss of smell) is a common early symptom of Parkinson's disease (PD). The shared genetic architecture between hyposmia and PD is unknown. Methods: We leveraged genome-wide association study (GWAS) results for self-assessment of 'ability to smell' and PD diagnosis. Linkage disequilibrium score regression (LDSC) and Local Analysis of [co]Variant Association (LAVA) were used to identify genome-wide and local genetic correlations. Mendelian randomization was used to identify potential causal relationships. Results: LDSC found that sense of smell negatively correlated at a genome-wide level with PD. LAVA found negative correlations in four genetic loci near GBA1, ANAPC4, SNCA, and MAPT. Using Mendelian randomization we found evidence for strong causal relationship between PD and liability towards poorer sense of smell, but weaker evidence for the reverse direction. Conclusions: Hyposmia and PD share genetic liability in only a subset of the major PD risk genes. While there was definitive evidence that PD can lower the sense of smell, there was only suggestive evidence for the reverse. This work highlights the heritability of olfactory function and its relationship with PD heritability and provides further insight into the association between PD and hyposmia.

Analysis of rare Parkinson's disease variants in millions of people.

Objective: Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of rare PD variants. Methods: We assessed a total of 27,590 PD cases, 6,701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies. Results: The meta-analysis resulted in 11 significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. At least 9 previously reported pathogenic or risk variants for PD did not pass Bonferroni correction in this analysis. Conclusions: Here, we provide the largest rare variant meta-analysis to date, providing thorough information of variants confirmed, newly identified, or rebutted for their association with PD.

Correlations in sleeping patterns and circadian preference between spouses.

Spouses may affect each other's sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = -0.11; -0.12, -0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (-0.15; -0.26, -0.04) and snoring (-0.15; -0.27, -0.04). Findings support the notion that an individual's sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.

Evaluating the performance of polygenic risk profiling across diverse ancestry populations in Parkinson's disease.

Objective: This study aims to address disparities in risk prediction by evaluating the performance of polygenic risk score (PRS) models using the 90 risk variants across 78 independent loci previously linked to Parkinson's disease (PD) risk across seven diverse ancestry populations. Methods: We conducted a multi-stage study, testing PRS models in predicting PD status across seven different ancestries applying three approaches: 1) PRS adjusted by gender and age; 2) PRS adjusted by gender, age and principal components (PCs); and 3) PRS adjusted by gender, age and percentage of population admixture. These models were built using the largest four population-specific summary statistics of PD risk to date (base data) and individual level data obtained from the Global Parkinson's Genetics Program (target data). We performed power calculations to estimate the minimum sample size required to conduct these analyses. A total of 91 PRS models were developed to investigate cumulative known genetic variation associated with PD risk and age of onset in a global context. Results: We observed marked heterogeneity in risk estimates across non-European ancestries, including East Asians, Central Asians, Latino/Admixed Americans, Africans, African admixed, and Ashkenazi Jewish populations. Risk allele patterns for the 90 risk variants yielded significant differences in directionality, frequency, and magnitude of effect. PRS did not improve in performance when predicting disease status using similar base and target data across multiple ancestries, demonstrating that cumulative PRS models based on current known risk are inherently biased towards European populations. We found that PRS models adjusted by percentage of admixture outperformed models that adjusted for conventional PCs in highly admixed populations. Overall, the clinical utility of our models in individually predicting PD status is limited in concordance with the estimates observed in European populations. Interpretation: This study represents the first comprehensive assessment of how PRS models predict PD risk and age at onset in a multi-ancestry fashion. Given the heterogeneity and distinct genetic architecture of PD across different populations, our assessment emphasizes the need for larger and diverse study cohorts of individual-level target data and well-powered ancestry-specific summary statistics. Our current understanding of PD status unraveled through GWAS in European populations is not generally applicable to other ancestries. Future studies should integrate clinical and *omics level data to enhance the accuracy and predictive power of PRS across diverse populations.

Association of Essential Tremor With Novel Risk Loci: A Genome-Wide Association Study and Meta-analysis.

Importance: Essential tremor (ET) is one of the most common movement disorders, affecting 5% of the general population older than 65 years. Common variants are thought to contribute toward susceptibility to ET, but no variants have been robustly identified. Objective: To identify common genetic factors associated with risk of ET. Design, Setting, and Participants: Case-control genome-wide association study. Inverse-variance meta-analysis was used to combine cohorts. Multicenter samples collected from European populations were collected from January 2010 to September 2019 as part of an ongoing study. Included patients were clinically diagnosed with or reported having ET. Control individuals were not diagnosed with or reported to have ET. Of 485 250 individuals, data for 483 054 passed data quality control and were used. Main Outcomes and Measures: Genotypes of common variants associated with risk of ET. Results: Of the 483 054 individuals included, there were 7177 with ET (3693 [51.46%] female; mean [SD] age, 62.66 [15.12] years), and 475 877 control individuals (253 785 [53.33%] female; mean [SD] age, 56.40 [17.6] years). Five independent genome-wide significant loci and were identified and were associated with approximately 18% of ET heritability. Functional analyses found significant enrichment in the cerebellar hemisphere, cerebellum, and axonogenesis pathways. Genetic correlation (r), which measures the degree of genetic overlap, revealed significant common variant overlap with Parkinson disease (r, 0.28; P = 2.38 × 10-8) and depression (r, 0.12; P = 9.78 × 10-4). A separate fine-mapping of transcriptome-wide association hits identified genes such as BACE2, LRRN2, DHRS13, and LINC00323 in disease-relevant brain regions, such as the cerebellum. Conclusions and Relevance: The results of this genome-wide association study suggest that a portion of ET heritability can be explained by common genetic variation and can help identify new common genetic risk factors for ET.