Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets

Kia, Demis A.; Zhang, David; Guelfi, Sebastian; Manzoni, Claudia; Hubbard, Leon; Reynolds, Regina H.; Ryten, Mina; Ferrari, Raffaele; Williams, Nigel; Trabzuni, Daniah; Hardy, John; Wood, Nicholas W.; Noyce, Alastair; Kaiyrzhanov, Rauan; Middlehurst, Ben; Tan, Manuela; Houlden, Henry; Morris, Huw; Plun‐Favreau, Hélène; Holmans, Peter; Brás, José; Quinn, John P.; Mok, Kin Y.; Kinghorn, Kerri J.; Billingsley, Kimberley; Lewis, Patrick A.; Schreglmann, Sebastian R; Guerreiro, Rita; Lovering, Ruth C.; R’Bibo, Lea; Rizig, Mie; Escott‐Price, Valentina; Chelban, Viorica; Foltynie, Thomas; Brice, Alexis; Danjou, Fabrice; Lesage, Suzanne; Corvol, Jean‐Christophe; Martínez, María Teresa González; Schulte, Claudia; Brockmann, Kathrin; Simón‐Sánchez, Javier; Heutink, Peter; Rizzu, Patrizia; Sharma, Manu; Gasser, Thomas; Nicolas, Aude; Cookson, Mark; Bandrés‐Ciga, Sara; Blauwendraat, Cornelis; Craig, David W.; Faghri, Faraz; Gibbs, J. Raphael; Hernandez, Dena G.; Keuren‐Jensen, Kendall Van; Liu, Zhandong; Leonard, Hampton; Nalls, Mike A.; Robak, Laurie; Lubbe, Steven; Finkbeiner, Steven; Mencacci, Niccolò E.; Lungu, Codrin; Singleton, Andrew B.; Scholz, Sonja W.; Reed, Xylena; Alcalay, Roy N.; Gan‐Or, Ziv; Rouleau, Guy A.; Krohn, Lynne; Hilten, Jacobus J. van; Marinus, Johan; Adarmes‐Gómez, Astrid; Aguilar, Miquel; Álvarez, Victoria; Álvarez, Victoria; Barrero, Francisco Javier; Yarza, Jesús Alberto Bergareche; Bernal‐Bernal, Inmaculada; Blázquez, Marta; Bonilla‐Toribio, Marta; Botía, Juan A.; Boungiorno, María Teresa; Buiza‐Rueda, Dolores; Cámara, Ana; Carrillo, Fátima; Carrión‐Claro, Mario; Cerdan, Debora; Clarimón, Jordi; Compta, Yaroslau; Díez-Fairén, Mónica; Dols‐Icardo, Oriol; Duarte, Jacinto; Durán, Raquel; Escamilla‐Sevilla, Francisco; Ezquerra, Mario; Feliz, Cici; Fernández, Manel; Fernández‐Santiago, Rubén; García, Ciara; García‐Ruiz, Pedro J.; Gómez‐Garre, Pilar; Heredia, Maria Jose Gómez; Aramburu, Isabel González; Pagola, Ana Gorostidi; Hoenicka, Janet; Infante, Jon; Jiménez‐Escrig, Adriano; Kulisevsky, Jaime; Labrador‐Espinosa, Miguel A.; López‐Sendón, José; Arregui, Adolfo López de Munaín; Macías, Daniel; Torres, Irene Martínez; Marín, Juan; Martı́, Marı́a José; Martínez‐Castrillo, Juan Carlos; Méndez‐del‐Barrio, Carlota; González, Manuel Menéndez; Mínguez, Marina Mata Adolfo; Mir, Pablo; Rezola, Elisabet Mondragón; Muñoz, Esteban; Pagonabarraga, Javier; Pástor, Pau; Errázquin, Francisco; Periñán, María Teresa; Ruíz‐Martínez, Javier; Ruz, Clara; Rodríguez, A; Sierra, María; Suárez-Sanmartín, Esther; Tabernero, C; Tartari, Juan Pablo; Tejera‐Parrado, Cristina; Tolosa, Eduard; Valldeoriola, Francesc; Vargas‐González, Laura; Vela, Lydia; Vives, Francisco; Zimprich, Alexander; Pihlstrøm, Lasse; Toft, Mathias; Kõks, Sulev; Taba, Pille; Hassin‐Baer, Sharon; Weale, Michael E.; Ramasamy, Adaikalavan; Smith, Colin; Guelfi, Manuel Sebastian; D’Sa, Karishma; Forabosco, Paola

doi:10.1001/jamaneurol.2020.5257

Cited by 133 publications

(93 citation statements)

References 38 publications

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“…Among the 18 genes we identified, eight genes ( MMRN1 , CD38 , NUPL2 , GPNMB , RNF40 , VKORC1 , ZSWIM7 , and CENPV ) were significantly heritable in CMC dorsolateral prefrontal cortex and qualified for the TWAS analyses. According to the published results, seven of the above eight genes associated with PD risk at an FDR level of 0.05 (Supplementary Table 5 ), including two genes ( CD38 , and GPNMB ) with solid evidence for colocalization (PPH4 > 0.75) 27 . At the same time, numerous previously reported PD risk loci did not implicate in our TWAS.…”

Section: Discussionmentioning

confidence: 98%

“…In parallel to ours, Kia and colleagues 27 conducted TWAS using expression weights from the CommonMind Consortium (CMC) dorsolateral prefrontal cortex to identify genes associated with PD. While considering the essential role of epigenetic features in predicting gene expression, our approach integrated the epigenetic information in the original TWAS to find gene–trait associations.…”

Section: Discussionmentioning

confidence: 99%

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A transcriptome-wide association study identifies susceptibility genes for Parkinson’s disease

Shi

Zhang

Zou

et al. 2021

npj Parkinsons Dis.

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Genome-wide association study (GWAS) has seen great strides in revealing initial insights into the genetic architecture of Parkinson’s disease (PD). Since GWAS signals often reside in non-coding regions, relatively few of the associations have implicated specific biological mechanisms. Here, we aimed to integrate the GWAS results with large-scale expression quantitative trait loci (eQTL) in 13 brain tissues to identify candidate causal genes for PD. We conducted a transcriptome-wide association study (TWAS) for PD using the summary statistics of over 480,000 individuals from the most recent PD GWAS. We identified 18 genes significantly associated with PD after Bonferroni corrections. The most significant gene, LRRC37A2, was associated with PD in all 13 brain tissues, such as in the hypothalamus (P = 6.12 × 10−22) and nucleus accumbens basal ganglia (P = 5.62 × 10−21). We also identified eight conditionally independent genes, including four new genes at known PD loci: CD38, LRRC37A2, RNF40, and ZSWIM7. Through conditional analyses, we demonstrated that several of the GWAS significant signals on PD could be driven by genetically regulated gene expression. The most significant TWAS gene LRRC37A2 accounts for 0.855 of the GWAS signal at its loci, and ZSWIM7 accounts for all the GWAS signals at its loci. We further identified several phenotypes previously associated with PD by querying the single nucleotide polymorphisms (SNPs) in the final model of the identified genes in phenome databases. In conclusion, we prioritized genes that are likely to affect PD by using a TWAS approach and identified phenotypes associated with PD.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

A transcriptome-wide association study identifies susceptibility genes for Parkinson’s disease

Shi

Zhang

Zou

et al. 2021

npj Parkinsons Dis.

View full text Add to dashboard Cite

show abstract

“…Furthermore, the integration of genome-wide association studies, together with expression and epigenetic datasets, has recently suggested that gene regulation data may be used to identify candidate the genes and genomic processes underlying the risk of sporadic PD [ 42 ] ( Table 1 ). In particular, Kia and colleagues, using various complementary bioinformatics tools, integrated GWAS, the transcriptome-wide association study (TWAS) and methylation data and identified 11 candidate genes whose regulatory changes in expression, splicing or methylation are associated with the risk of PD.…”

Section: Parkinson’s Diseasementioning

confidence: 99%

Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases

Cognata

Morello

Cavallaro

2021

IJMS

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Molecular and clinical heterogeneity is increasingly recognized as a common characteristic of neurodegenerative diseases (NDs), such as Alzheimer’s disease, Parkinson’s disease and amyotrophic lateral sclerosis. This heterogeneity makes difficult the development of early diagnosis and effective treatment approaches, as well as the design and testing of new drugs. As such, the stratification of patients into meaningful disease subgroups, with clinical and biological relevance, may improve disease management and the development of effective treatments. To this end, omics technologies—such as genomics, transcriptomics, proteomics and metabolomics—are contributing to offer a more comprehensive view of molecular pathways underlying the development of NDs, helping to differentiate subtypes of patients based on their specific molecular signatures. In this article, we discuss how omics technologies and their integration have provided new insights into the molecular heterogeneity underlying the most prevalent NDs, aiding to define early diagnosis and progression markers as well as therapeutic targets that can translate into stratified treatment approaches, bringing us closer to the goal of personalized medicine in neurology.

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“…Especially, GBA1 is well-known as a responsible gene for Gaucher disease, the most common lysosomal storage disorder. Moreover, the recent expansion of genetic, transcriptomic, and epigenetic studies in sporadic PD has nominated an increasing number of lysosomal pathway genes as a risk factor for PD (17)(18)(19). Endolysosomal dysfunctions are also frequently described in other neurodegenerative diseases such as Alzheimer's disease (AD), Huntington's disease (HD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), all of which accompany neuronal accumulation of misfolded proteins (20,21).…”

Section: Introductionmentioning

confidence: 99%

Targeting of Lysosomal Pathway Genes for Parkinson's Disease Modification: Insights From Cellular and Animal Models

Abe

Kuwahara

2021

Front. Neurol.

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Previous genetic studies on hereditary Parkinson's disease (PD) have identified a set of pathogenic gene mutations that have strong impacts on the pathogenicity of PD. In addition, genome-wide association studies (GWAS) targeted to sporadic PD have nominated an increasing number of genetic variants that influence PD susceptibility. Although the clinical and pathological characteristics in hereditary PD are not identical to those in sporadic PD, α-synuclein, and LRRK2 are definitely associated with both types of PD, with LRRK2 mutations being the most frequent cause of autosomal-dominant PD. On the other hand, a significant portion of risk genes identified from GWAS have been associated with lysosomal functions, pointing to a critical role of lysosomes in PD pathogenesis. Experimental studies have suggested that the maintenance or upregulation of lysosomal activity may protect against neuronal dysfunction or degeneration. Here we focus on the roles of representative PD gene products that are implicated in lysosomal pathway, namely LRRK2, VPS35, ATP13A2, and glucocerebrosidase, and provide an overview of their disease-associated functions as well as their cooperative actions in the pathogenesis of PD, based on the evidence from cellular and animal models. We also discuss future perspectives of targeting lysosomal activation as a possible strategy to treat neurodegeneration.

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Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets

Cited by 133 publications

References 38 publications

A transcriptome-wide association study identifies susceptibility genes for Parkinson’s disease

A transcriptome-wide association study identifies susceptibility genes for Parkinson’s disease

Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases

Targeting of Lysosomal Pathway Genes for Parkinson's Disease Modification: Insights From Cellular and Animal Models

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