Evaluation of Parkinson Disease Risk Variants as Expression-QTLs

The recent Parkinson Disease GWAS Consortium meta-analysis and replication study reports association at several previously confirmed risk loci SNCA, MAPT, GAK/DGKQ, and HLA and identified a novel risk locus at RIT2. To further explore functional consequences of these associations, we investigated modification of gene expression in prefrontal cortex brain samples of pathologically confirmed PD cases (N = 26) and controls (N = 24) by 67 associated SNPs in these 5 loci. Association between the eSNPs and expression was evaluated using a 2-degrees of freedom test of both association and difference in association between cases and controls, adjusted for relevant covariates. SNPs at each of the 5 loci were tested for cis-acting effects on all probes within 250 kb of each locus. Trans-effects of the SNPs on the 39,122 probes passing all QC on the microarray were also examined. From the analysis of cis-acting SNP effects, several SNPs in the MAPT region show significant association to multiple nearby probes, including two strongly correlated probes targeting the gene LOC644246 and the duplicated genes LRRC37A and LRRC37A2, and a third uncorrelated probe targeting the gene DCAKD. Significant cis-associations were also observed between SNPs and two probes targeting genes in the HLA region on chromosome 6. Expanding the association study to examine trans effects revealed an additional 23 SNP-probe associations reaching statistical significance (p<2.8×10−8) including SNPs from the SNCA, MAPT and RIT2 regions. These findings provide additional context for the interpretation of PD associated SNPs identified in recent GWAS as well as potential insight into the mechanisms underlying the observed SNP associations.

[1]  J. Vance,et al.  Gene Expression Profiles in Parkinson Disease Prefrontal Cortex Implicate FOXO1 and Genes under Its Transcriptional Regulation , 2012, PLoS genetics.

[2]  Eden R Martin,et al.  Meta‐analysis of Parkinson's Disease: Identification of a novel locus, RIT2 , 2012, Annals of neurology.

[3]  N. Ertekin-Taner Gene expression endophenotypes: a novel approach for gene discovery in Alzheimer's disease , 2011, Molecular Neurodegeneration.

[4]  Mohamad Saad,et al.  Imputation of sequence variants for identification of genetic risks for Parkinson's disease: a meta-analysis of genome-wide association studies , 2011, The Lancet.

[5]  Mohamad Saad,et al.  Genome-wide association study confirms BST1 and suggests a locus on 12q24 as the risk loci for Parkinson's disease in the European population. , 2011, Human molecular genetics.

[6]  Matti Pirinen,et al.  Dissection of the genetics of Parkinson's disease identifies an additional association 5′ of SNCA and multiple associated haplotypes at 17q21 , 2010, Human molecular genetics.

[7]  I. Ferrer,et al.  Neuropathology of sporadic Parkinson disease before the appearance of parkinsonism: preclinical Parkinson disease , 2011, Journal of Neural Transmission.

[8]  J. Nutt,et al.  Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson’s disease , 2010, Nature Genetics.

[9]  Silke Szymczak,et al.  Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility , 2010, PloS one.

[10]  Luigi Ferrucci,et al.  Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain , 2010, PLoS genetics.

[11]  R. Guigó,et al.  Transcriptome genetics using second generation sequencing in a Caucasian population , 2010, Nature.

[12]  Eden R Martin,et al.  Genome‐Wide Association Study Confirms SNPs in SNCA and the MAPT Region as Common Risk Factors for Parkinson Disease , 2010, Annals of human genetics.

[13]  Sonja W. Scholz,et al.  Genome-Wide Association Study reveals genetic risk underlying Parkinson’s disease , 2009, Nature Genetics.

[14]  H. Shill,et al.  Unified staging system for Lewy body disorders: correlation with nigrostriatal degeneration, cognitive impairment and motor dysfunction , 2009, Acta Neuropathologica.

[15]  D. Stephan,et al.  Genetic control of human brain transcript expression in Alzheimer disease. , 2009, American journal of human genetics.

[16]  Audrey Kauffmann,et al.  Bioinformatics Applications Note Arrayqualitymetrics—a Bioconductor Package for Quality Assessment of Microarray Data , 2022 .

[17]  K. Doheny,et al.  Genomewide association study for susceptibility genes contributing to familial Parkinson disease , 2009, Human Genetics.

[18]  M. Stephens,et al.  High-Resolution Mapping of Expression-QTLs Yields Insight into Human Gene Regulation , 2008, PLoS genetics.

[19]  Zhaoshi Jiang,et al.  Evolutionary toggling of the MAPT 17q21.31 inversion region , 2008, Nature Genetics.

[20]  Eden R Martin,et al.  A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms , 2008, Genetic epidemiology.

[21]  Hitoshi Takahashi,et al.  The Lewy body in Parkinson's disease: Molecules implicated in the formation and degradation of α‐synuclein aggregates , 2007, Neuropathology : official journal of the Japanese Society of Neuropathology.

[22]  D. Koller,et al.  Population genomics of human gene expression , 2007, Nature Genetics.

[23]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[24]  Sonja W. Scholz,et al.  Genome-wide genotyping in Parkinson's disease and neurologically normal controls: first stage analysis and public release of data , 2006, The Lancet Neurology.

[25]  Mariza de Andrade,et al.  High-resolution whole-genome association study of Parkinson disease. , 2005, American journal of human genetics.

[26]  H. Stefánsson,et al.  A common inversion under selection in Europeans , 2005, Nature Genetics.

[27]  D. Kleinjan,et al.  Long-range control of gene expression: emerging mechanisms and disruption in disease. , 2005, American journal of human genetics.

[28]  H. Braak,et al.  Staging of brain pathology related to sporadic Parkinson’s disease , 2003, Neurobiology of Aging.

[29]  M F Huque,et al.  Some comments on frequently used multiple endpoint adjustment methods in clinical trials. , 1997, Statistics in medicine.