Association of seven functional polymorphisms of one-carbon metabolic pathway with total plasma homocysteine levels and susceptibility to Parkinson's disease among South Indians

Kumudini, Nadella; Addepally, Uma; Naushad, Shaik Mohammad; Mridula, Rukmini; Borgohain, Rupam; Kutala, Vijay Kumar

doi:10.1016/j.neulet.2014.03.044

Cited by 23 publications

(17 citation statements)

References 30 publications

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“…On the other hand, the trivariate analysis showed gene-gene interactions between the cSHMT 1420 C[T, MTRR 66 A[G and RFC1 80 G[A. This was similar to already reported interaction model on one-carbon metabolism in relation to PD risk [26]. None of the genetic variants of xenobiotic metabolic pathway showed potential gene-gene interactions in CAD and PD (Fig.…”

Section: Mdr Modelssupporting

confidence: 87%

“…This polymorphism conferred significant protection against CAD and PD. In a recent study on PD, it was observed that SHMT 1420 C[T controls MTRR 66 A[G and MTHFR 677 C[T-mediated increase in homocysteine, specifically in men [26]. Similar protective role of cSHMT 1420 C[T was observed in autism, a pervasive developmental disorder prevalent in male children [29].…”

Section: Discussionmentioning

confidence: 74%

“…PD is a neurological disorder characterized by ''Lewy body'' formation in substantia nigra with subsequent loss of dopaminergic neuronal function and associated with phenotypic features such as tremors, rigidity and bradykinesia. It was shown from our study on the South Indian population that Parkinson's subjects exhibited hyperhomocysteinemia and MTRR 66 A[G increases PD risk while cSHMT 1420 C[T reduces risk by modulating homocysteine levels [26]. In the same cohort, COMT H108L was reported as risk factor for PD [27].…”

Section: Introductionmentioning

confidence: 70%

“…The case-control datasets of our ten published studies from the Nizam's Institute of Medical Sciences (NIMS), Hyderabad, India were chosen for the analysis [17][18][19][20][21][23][24][25][26][27]. For each of the four disease models, the subjects involved were identified individually and the case-control statistics differ between each of the disease.…”

Section: Dataset Collectionmentioning

confidence: 99%

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Multifactor dimensionality reduction analysis to elucidate the cross-talk between one-carbon and xenobiotic metabolic pathways in multi-disease models

et al. 2015

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Putatively functional polymorphisms of one-carbon and xenobiotic metabolic pathways influence susceptibility for wide spectrum of diseases. The current study was aimed to explore gene-gene interactions among these two metabolic pathways in four diseases i.e. breast cancer, systemic lupus erythematosus (SLE), coronary artery disease (CAD) and Parkinson's disease (PD). Multifactor dimensionality reduction analysis was carried out on four case-control datasets. Cross-talk was observed between one-carbon and xenobiotic pathways in breast cancer (RFC 80 G>A, COMT H108L and TYMS 5'-UTR 28 bp tandem repeat) and SLE (CYP1A1 m1, MTRR 66 A>G and GSTT1). Gene-gene interactions within one-carbon metabolic pathway were observed in CAD (GCPII 1561 C>T, SHMT 1420 C>T and MTHFR 677 C>T) and PD (cSHMT 1420 C>T, MTRR 66 A>G and RFC1 80 G>A). These interaction models showed good predictability of risk for PD (The area under the receiver operating characteristic curve (C) = 0.83) and SLE (C = 0.73); and moderate predictability of risk for breast cancer (C = 0.64) and CAD (C = 0.63). Cross-talk between one-carbon and xenobiotic pathways was observed in diseases with female preponderance. Gene-gene interactions within one-carbon metabolic pathway were observed in diseases with male preponderance.

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Section: Mdr Modelssupporting

confidence: 87%

Section: Discussionmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 70%

Section: Dataset Collectionmentioning

confidence: 99%

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Multifactor dimensionality reduction analysis to elucidate the cross-talk between one-carbon and xenobiotic metabolic pathways in multi-disease models

et al. 2015

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“…The etiology of sporadic PD is complex involving several mechanisms such as oxidative stress [3], excitotoxicity [4], altered dopamine metabolism, and deficient detoxification of xenobiotic agents [5]. Earlier, we have reported gene-gene interactions between methionine synthase (MTRR) A66G and cytosolic serine hydroxymethyltransferase (cSHMT) C1420T in modulating PD risk [6]. MTRR A66G was associated with increased risk for PD, while cSHMT C1420T reduced the risk by modulating homocysteine levels [6].…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of four disease prediction models of Parkinson’s disease

et al. 2015

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Parkinson's disease (PD) is a multi-factorial disorder with high-penetrant mutations accounting for small percentage of PD. Our previous studies demonstrated individual association of genetic variants in folate, xenobiotic, and dopamine metabolic pathways with PD risk. The rational of the study was to develop a risk prediction model for PD using these genetic polymorphisms along with synuclein (SNCA) polymorphism. We have generated additive, multifactor dimensionality reduction (MDR), recursive partitioning (RP), and artificial neural network (ANN) models using 21 SNPs as inputs and disease outcome as output. The clinical utility of all these models was assessed by plotting receiver operating characteristics curves where in area under the curve (AUC) was used as an index of diagnostic utility of the model. The additive model was the simplest and exhibited an AUC of 0.72. The MDR model showed significant gene-gene interactions between SNCA, DRD4VNTR, and DRD2A polymorphisms. The RP model showed SHMT C1420T as important determinant of PD risk. This variant allele was found to be protective and this protection was nullified by MTRR A66G. Inheritance of SHMT wild allele and SNCA intronic polymorphism was shown to increase the risk of PD. The ANN model showed higher diagnostic utility (AUC = 0.86) compared to all the models and was able to explain 56.6% cases of sporadic PD. To conclude, the ANN model developed using SNPs in folate, xenobiotic, and dopamine pathways along with SNCA has higher clinical utility in predicting PD risk compared to other models.

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One‐carbon metabolism pathway genes and their non‐association with the development of amyotrophic lateral sclerosis

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et al. 2022

J of Cellular Biochemistry

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Although of unknown etiology, some mechanisms associated with the metabolic cycle of folate are speculated to be related to the genesis of amyotrophic lateral sclerosis (ALS). Thus, the aim of the study was to analyze the role of genetic polymorphisms rs1051266 in SLC19A1 gene and rs1805087 in MTR gene and their associations with ALS development. A case–control study was conducted with 101 individuals with ALS and 119 individuals without diagnosis of neurodegenerative diseases, from the Brazilian central population. The polymorphisms were determined using the polymerase chain reaction‐restriction fragment length polymorphism technique. The results showed no statistically significant differences, even when genotypes were analyzed by the dominant, recessive, codominant, and overdominant inheritance models. It was observed a statistical significance relating alcohol consumption with individuals in the case group (p = 0.01). Therefore, the need for more studies to evaluate the influence of genetic variants is highlighted, seeking to provide information on the etiopathogenesis of ALS.

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Association of seven functional polymorphisms of one-carbon metabolic pathway with total plasma homocysteine levels and susceptibility to Parkinson's disease among South Indians

Cited by 23 publications

References 30 publications

Multifactor dimensionality reduction analysis to elucidate the cross-talk between one-carbon and xenobiotic metabolic pathways in multi-disease models

Multifactor dimensionality reduction analysis to elucidate the cross-talk between one-carbon and xenobiotic metabolic pathways in multi-disease models

Comparative analysis of four disease prediction models of Parkinson’s disease

One‐carbon metabolism pathway genes and their non‐association with the development of amyotrophic lateral sclerosis

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