Erin M. Hill-Burns

Comprehensive research synopsis and systematic meta-analyses in Parkinson's disease genetics : The PDGene database

More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinsons disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of ∼27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P<5×10−8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3×10−8). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinsons disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNPs main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2df<5×10−8 in GWAIS, and OR = 0.41, P = 3×10−8 in heavy coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that are missed in GWAS. Both adenosine antagonists (caffeine-like) and glutamate antagonists (GRIN2A-related) are being tested in clinical trials for treatment of PD. GRIN2A may be a useful pharmacogenetic marker for subdividing individuals in clinical trials to determine which medications might work best for which patients.

Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome

There is mounting evidence for a connection between the gut and Parkinsons disease (PD). Dysbiosis of gut microbiota could explain several features of PD.

A genetic basis for the variable effect of smoking/nicotine on Parkinson's disease.

Prior studies have established an inverse association between cigarette smoking and the risk of developing Parkinson’s disease (PD), and currently, the disease-modifying potential of the nicotine patch is being tested in clinical trials. To identify genes that interact with the effect of smoking/nicotine, we conducted genome-wide interaction studies in humans and in Drosophila. We identified SV2C, which encodes a synaptic-vesicle protein in PD-vulnerable substantia nigra (P=1 × 10−7 for gene–smoking interaction on PD risk), and CG14691, which is predicted to encode a synaptic-vesicle protein in Drosophila (P=2 × 10−11 for nicotine–paraquat interaction on gene expression). SV2C is biologically plausible because nicotine enhances the release of dopamine through synaptic vesicles, and PD is caused by the depletion of dopamine. Effect of smoking on PD varied by SV2C genotype from protective to neutral to harmful (P=5 × 10−10). Taken together, cross-validating evidence from humans and Drosophila suggests SV2C is involved in PD pathogenesis and it might be a useful marker for pharmacogenomics studies involving nicotine.

Evidence for More than One Parkinson's Disease-Associated Variant within the HLA Region

Parkinsons disease (PD) was recently found to be associated with HLA in a genome-wide association study (GWAS). Follow-up GWASs replicated the PD-HLA association but their top hits differ. Do the different hits tag the same locus or is there more than one PD-associated variant within HLA? We show that the top GWAS hits are not correlated with each other (0.00≤r2≤0.15). Using our GWAS (2000 cases, 1986 controls) we conducted step-wise conditional analysis on 107 SNPs with P<10−3 for PD-association; 103 dropped-out, four remained significant. Each SNP, when conditioned on the other three, yielded PSNP1 = 5×10−4, PSNP2 = 5×10−4, PSNP3 = 4×10−3 and PSNP4 = 0.025. The four SNPs were not correlated (0.01≤r2≤0.20). Haplotype analysis (excluding rare SNP2) revealed increasing PD risk with increasing risk alleles from OR = 1.27, P = 5×10−3 for one risk allele to OR = 1.65, P = 4×10−8 for three. Using additional 843 cases and 856 controls we replicated the independent effects of SNP1 (Pconditioned-on-SNP4 = 0.04) and SNP4 (Pconditioned-on-SNP1 = 0.04); SNP2 and SNP3 could not be replicated. In pooled GWAS and replication, SNP1 had ORconditioned-on-SNP4 = 1.23, Pconditioned-on-SNP4 = 6×10−7; SNP4 had ORconditioned-on-SNP1 = 1.18, Pconditioned-on-SNP1 = 3×10−3; and the haplotype with both risk alleles had OR = 1.48, P = 2×10−12. Genotypic OR increased with the number of risk alleles an individual possessed up to OR = 1.94, P = 2×10−11 for individuals who were homozygous for the risk allele at both SNP1 and SNP4. SNP1 is a variant in HLA-DRA and is associated with HLA-DRA, DRB5 and DQA2 gene expression. SNP4 is correlated (r2 = 0.95) with variants that are associated with HLA-DQA2 expression, and with the top HLA SNP from the IPDGC GWAS (r2 = 0.60). Our findings suggest more than one PD-HLA association; either different alleles of the same gene, or separate loci.

Identification of genetic modifiers of age-at-onset for familial Parkinson’s disease

Parkinson’s disease (PD) is the most common cause of neurodegenerative movement disorder and the second most common cause of dementia. Genes are thought to have a stronger effect on age-at-onset of PD than on risk, yet there has been a phenomenal success in identifying risk loci but not age-at-onset modifiers. We conducted a genome-wide study for age-at-onset. We analysed familial and non-familial PD separately, per prior evidence for strong genetic effect on age-at-onset in familial PD. GWAS was conducted in 431 unrelated PD individuals with at least one affected relative (familial PD) and 1544 non-familial PD from the NeuroGenetics Research Consortium (NGRC); an additional 737 familial PD and 2363 non-familial PD were used for replication. In familial PD, two signals were detected and replicated robustly: one mapped to LHFPL2 on 5q14.1 (PNGRC = 3E-8, PReplication = 2E-5, PNGRC + Replication = 1E-11), the second mapped to TPM1 on 15q22.2 (PNGRC = 8E-9, PReplication = 2E-4, PNGRC + Replication = 9E-11). The variants that were associated with accelerated onset had low frequencies (<0.02). The LHFPL2 variant was associated with earlier onset by 12.33 [95% CI: 6.2; 18.45] years in NGRC, 8.03 [2.95; 13.11] years in replication, and 9.79 [5.88; 13.70] years in the combined data. The TPM1 variant was associated with earlier onset by 15.30 [8.10; 22.49] years in NGRC, 9.29 [1.79; 16.79] years in replication, and 12.42 [7.23; 17.61] years in the combined data. Neither LHFPL2 nor TPM1 was associated with age-at-onset in non-familial PD. LHFPL2 (function unknown) is overexpressed in brain tumours. TPM1 encodes a highly conserved protein that regulates muscle contraction, and is a tumour-suppressor gene.

Glutamate receptor gene GRIN2A, coffee, and Parkinson disease.

1 Division of Genetics, Wadsworth Center, New York State Department of Health, Albany, New York, United States of America, 2 New England Research Institutes Inc., Watertown, Massachusetts, United States of America, 3 Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, United States of America, 4 Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, United States of America, 5 VA Puget Sound Health Care System and Department of Neurology, University of Washington, Seattle, Washington, United States of America, 6 Department of Biomedical Science, School of Public Health, State University of New York, Albany, New York, United States of America

An attempt to replicate interaction between coffee and CYP1A2 gene in connection to Parkinson's disease.

Popat et al. [1] recently reported evidence for interaction between Cytochrome P450 1A2 (CYP1A2) genotype and coffee on the risk of developing Parkinson’s disease (PD). This finding is particularly intriguing because caffeine consumption is inversely associated with risk of developing PD, and CYP1A2 is involved in metabolism of caffeine. Popat et al also suggested that the coffee–PD association was strongest among homozygous carriers of the slow-metabolizer CYP1A2_ rs762551_CC genotype. In an accompanying editorial [2] Mellick and Ross point out that caffeine-metabolism genes have not been found to associate with PD in genome-wide studies. Were the genes missed because coffee and interaction were not in the analytical model? Considering the high potential significance of this observation, we attempted to replicate it using 1458 persons with PD and 931 controls from the NeuroGenetics Research Consortium (NGRC), all Caucasian of European Origin, with detailed life-time coffee consumption data [3] and genotyped using Illumina HumanOmni1-Quad_v1-0_B genotyping array [4]. rs2472304 was genotyped, rs762551 and rs2470890 were imputed with high accuracy (imputation-information-score>0.98) [5]. The study was approved by Institutional Review Boards. We first tested interaction under the same model as Popat et al. adjusting for age and sex while stratifying coffee-consumption as ever/never (Table 1). In addition, we reanalyzed the data with coffee stratified as high/low (defined at median), which is a more sensitive measure for NGRC due to high coffee-consumption and few non-coffee-drinkers in NGRC. We also tried models where principal components and smoking were added as covariates. As noted by Mellick and Ross [3] both population structure (genetic mixtures) and smoking could confound these results. Inclusion of principal components corrects for population structure in European-Americans due to Jewish/non-Jewish ancestry and European country-of-origin [4]. Inclusion of smoking as a covariate helps assess if results are affected by the correlation between smoking and coffee-drinking, and the inverse association of smoking with PD [3]. Unfortunately, we did not replicate the reported interactions under any of the models, nor did we find a stronger PD-coffee association among slow-metabolizers (Table 1). Table 1 Test results for SNPxCoffee interaction and genotype-specific PD-coffee association

Stool Immune Profiles Evince Gastrointestinal Inflammation in Parkinson's Disease: Stool Inflammatory Profiles in PD Patients

Background: Gastrointestinal symptoms are common in Parkinsons disease and frequently precede the development of motor impairments. Intestinal inflammation has been proposed as a driver of disease pathology, and evaluation of inflammatory mediators in stool could possibly identify valuable early‐stage biomarkers. We measured immune‐ and angiogenesis‐related proteins in human stool to examine inflammatory profiles associated with Parkinsons disease.