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

BACKGROUND: There is mounting evidence for a connection between the gut and Parkinson's disease (PD). Dysbiosis of gut microbiota could explain several features of PD. OBJECTIVE: The objective of this study was to determine if PD involves dysbiosis of gut microbiome, disentangle effects of confounders, and identify candidate taxa and functional pathways to guide research. METHODS: A total of 197 PD cases and 130 controls were studied. Microbial composition was determined by 16S rRNA gene sequencing of DNA extracted from stool. Metadata were collected on 39 potential confounders including medications, diet, gastrointestinal symptoms, and demographics. Statistical analyses were conducted while controlling for potential confounders and correcting for multiple testing. We tested differences in the overall microbial composition, taxa abundance, and functional pathways. RESULTS: Independent microbial signatures were detected for PD (P = 4E-5), participants' region of residence within the United States (P = 3E-3), age (P = 0.03), sex (P = 1E-3), and dietary fruits/vegetables (P = 0.01). Among patients, independent signals were detected for catechol-O-methyltransferase-inhibitors (P = 4E-4), anticholinergics (P = 5E-3), and possibly carbidopa/levodopa (P = 0.05). We found significantly altered abundances of the Bifidobacteriaceae, Christensenellaceae, [Tissierellaceae], Lachnospiraceae, Lactobacillaceae, Pasteurellaceae, and Verrucomicrobiaceae families. Functional predictions revealed changes in numerous pathways, including the metabolism of plant-derived compounds and xenobiotics degradation. CONCLUSION: PD is accompanied by dysbiosis of gut microbiome. Results coalesce divergent findings of prior studies, reveal altered abundance of several taxa, nominate functional pathways, and demonstrate independent effects of PD medications on the microbiome. The findings provide new leads and testable hypotheses on the pathophysiology and treatment of PD. © 2017 International Parkinson and Movement Disorder Society.

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.

Identification of a novel Parkinson's disease locus via stratified genome-wide association study.

BACKGROUND: Parkinson's disease (PD) is complex and heterogeneous. The numerous susceptibility loci that have been identified reaffirm the complexity of PD but do not fully explain it; e.g., it is not known if any given PD susceptibility gene is associated with all PD or a disease subtype. We also suspect that important disease genes may have escaped detection because of this heterogeneity. We used presence/absence of family history to subdivide the cases and performed genome-wide association studies (GWAS) in Sporadic-PD and Familial-PD separately. The aim was to uncover new genes and gain insight into the genetic architecture of PD. RESULTS: Employing GWAS on the NeuroGenetics Research Consortium (NGRC) dataset stratified by family history (1565 Sporadic-PD, 435 Familial-PD, 1986 controls), we identified a novel locus on chromosome 1p21 in Sporadic-PD (PNGRC = 4 × 10(-8)) and replicated the finding (P(Replication) = 6 × 10(-3); P(Pooled) = 4 × 10(-10)) in 1528 Sporadic-PD and 796 controls from the National Institutes of Neurologic Disease and Stroke (NINDS) Repository. This is the fifth PD locus to be mapped to the short arm of chromosome 1. It is flanked by S1PR1 and OLFM3 genes, and is 200 kb from a multiple sclerosis susceptibility gene. The second aim of the study was to extend the stratified GWAS to the well-established PD genes. SNCA_ rs356220 was associated with both Sporadic-PD (OR = 1.37, P = 1 × 10(-9)) and Familial-PD (OR = 1.40, P = 2 × 10(-5)). HLA_rs3129882 was more strongly associated with Sporadic-PD (OR = 1.38, P = 5 × 10(-10)) than Familial-PD (OR = 1.12, P = 0.15). In the MAPT region, virtually every single nucleotide polymorphism (SNP) had a stronger effect-size and lower P-value in Familial-PD (peak P = 8 × 10(-7)) than in Sporadic-PD (peak P = 2 × 10(-5)). CONCLUSIONS: We discovered and replicated a new locus for Sporadic-PD which had escaped detection in un-stratified GWAS. This demonstrates that by stratifying on a key variable the power gained due to diminished heterogeneity can sometimes outweigh the power lost to reduced sample size. We also detected distinct patterns of disease associations for previously established PD susceptibility genes, which gives an insight to the genetic architecture of the disease and could aid in the selection of appropriate study population for future studies.

Association of Parkinson disease with structural and regulatory variants in the HLA region.

Historically, association of disease with the major histocompatibility complex (HLA) genes has been tested with HLA alleles that encode antigen-binding affinity. The association with Parkinson disease (PD), however, was discovered with noncoding SNPs in a genome-wide association study (GWAS). We show here that several HLA-region SNPs that have since been associated with PD form two blocks tagged by rs3129882 (p = 9 × 10(-11)) and by rs9268515 and/or rs2395163 (p = 3 × 10(-11)). We investigated whether these SNP-associations were driven by HLA-alleles at adjacent loci. We imputed class I and class II HLA-alleles for 2000 PD cases and 1986 controls from the NeuroGenetics Research Consortium GWAS and sequenced a subset of 194 cases and 204 controls. We were therefore able to assess accuracy of two imputation algorithms against next-generation-sequencing while taking advantage of the larger imputed data sets for disease study. Additionally, we imputed HLA alleles for 843 cases and 856 controls from another GWAS for replication. PD risk was positively associated with the B(∗)07:02_C(∗)07:02_DRB5(∗)01_DRB1(∗)15:01_DQA1(∗)01:02_DQB1(∗)06:02 haplotype and negatively associated with the C(∗)03:04, DRB1(∗)04:04 and DQA1(∗)03:01 alleles. The risk haplotype and DQA1(∗)03:01 lost significance when conditioned on the SNPs, but C(∗)03:04 (OR = 0.72, p = 8 × 10(-6)) and DRB1(∗)04:04 (OR = 0.65, p = 4 × 10(-5)) remained significant. Similarly, rs3129882 and the closely linked rs9268515 and rs2395163 remained significant irrespective of HLA alleles. rs3129882 and rs2395163 are expression quantitative trait loci (eQTLs) for HLA-DR and HLA-DQ (9 × 10(-5) ≥ PeQTL ≥ 2 × 10(-79)), suggesting that HLA gene expression might influence PD. Our data suggest that PD is associated with both structural and regulatory elements in HLA. Furthermore, our study demonstrates that noncoding SNPs in the HLA region can be associated with disease irrespective of HLA alleles, and that observed associations with HLA alleles can sometimes be secondary to a noncoding variant.