Length Polymorphism and Methylation Status of UPS29 Minisatellite of the ACAP3 Gene as Molecular Biomarker of Epilepsy. Sex Differences in Seizure Types and Symptoms

Abstract

Epilepsy is a neurological disease with different clinical forms and inter-individuals heterogeneity, which may be associated with genetic and/or epigenetic polymorphisms of tandem-repeated noncoding DNA. These polymorphisms may serve as predictive biomarkers of various forms of epilepsy. ACAP3 is the protein regulating morphogenesis of neurons and neuronal migration and is an integral component of important signaling pathways. This study aimed to carry out an association analysis of the length polymorphism and DNA methylation of the UPS29 minisatellite of the ACAP3 gene in patients with epilepsy. We revealed an association of short UPS29 alleles with increased risk of development of symptomatic and cryptogenic epilepsy in women, and also with cerebrovascular pathologies, structural changes in the brain, neurological status, and the clinical pattern of seizures in both women and men. The increase of frequency of hypomethylated UPS29 alleles in men with symptomatic epilepsy, and in women with both symptomatic and cryptogenic epilepsy was observed. For patients with hypomethylated UPS29 alleles, we also observed structural changes in the brain, neurological status, and the clinical pattern of seizures. These associations had sex-specific nature similar to a genetic association. In contrast with length polymorphism epigenetic changes affected predominantly the long UPS29 allele. We suppose that genetic and epigenetic alterations UPS29 can modify ACAP3 expression and thereby affect the development and clinical course of epilepsy.

Methylation Biomarkers Associated With Drug-Resistant Epilepsy

“…According to previous studies 14,19,22 , we did not observe differences in methylation of Reelin, EPHX1 , or CPA6 in DRE. However, ACAP3 was hypomethylated in the cortex, as described previously 15 .…”

“…In the present study we analyzed differential methylation associated with DRE. Unlike previous studies [10][11][12][13][14][15][16][17][18][19][20][21][22][23] , we analyzed different tissues simultaneously, searched for markers of response to surgery, validated part of the results with an alternative technique and studied the epigenetic clock.…”

“…Different epigenetic mechanisms are involved in epilepsy: DNA methylation, histone modifications, chromatin remodeling, and noncoding RNAs 10,11 . DNA methylation is the most stable epigenetic mark and is the most studied in DRE [10][11][12][13][14][15][16][17][18][19][20][21][22][23] . Hence, previous studies have found methylation differences associated with epilepsy in blood 13 and brain samples 16,20 .…”

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

“…Sun et al [ 97 ] reported that TRPM2 was significantly regulated in diabetes and obesity. Findings were implied by Richter et al [ 98 ], Suchkova et al [ 99 ], Qureshi et al [ 100 ], Wang et al [ 101 ], Wang et al [ 102 ], Aoki-Suzuki et al [ 103 ], Ohno et al [ 104 ], Richter et al [ 98 ], Rahman and Copeland [ 105 ], Congiu et al [ 106 ], Ji et al [ 107 ], Wollmer et al [ 108 ], Yamazaki et al [ 109 ], Bardien et al [ 110 ], Comella Bolla et al [ 111 ], Horvath et al [ 112 ], Watanabe et al [ 113 ], Kushima et al [ 114 ], Grünblatt et al [ 115 ], and Sato and Kawata [ 116 ] when they found that TAOK2 , ACAP3 , PLXNA3 , PLXNA4 , DCTN1 , NTNG2 , LRP4 , AGRN (agrin), TAOK2 , POLG (DNA polymerase gamma, catalytic subunit), KCNK2 , OPRK1 , ABCA2 , ABCA7 , LRRK2 , CD200 , PAK3 , PADI2 , EPHB1 , CHAT (choline O-acetyltransferase) and SLC18A1 plays a substantial role in the patients with neurological and neuropsychiatric disorders. Studies showed that biomarkers include PLD2 [ 117 ], FLNA (filamin A) [ 118 ], SMURF1 [ 119 ], LINGO1 [ 120 ], CACNA1H [ 121 ], NLRP6 [ 122 ], NLRC3 [ 123 ], CXCR2 [ 124 ] and C5AR1 [ 125 ] plays an important role in progression of hypertension.…”

Bioinformatics Analysis of Key Genes and Pathways for Obesity Associated Type 2 Diabetes Mellitus as a Therapeutic Target

“…Sun et al [96] found that TRPM2 was significantly associated in obesity associated type 2 diabetes mellitus. Richter et al [97], Suchkova et al [98], Qureshi et al [99], Wang et al [100], Wang et al [101], Aoki-Suzuki et al [102], Ohno et al [103], Richter et al [104], Rahman and Copeland [105], Congiu et al [106], Ji et al [107], Wollmer et al [108], Yamazaki et al [109], Bardien et al [110], Comella Bolla et al [111], Horvath et al [112], Watanabe et al [113], Kushima et al [114], Grünblatt et al [115] and Sato and Kawata [116] have shown that TAOK2, ACAP3, PLXNA3, PLXNA4, DCTN1, NTNG2, LRP4, AGRN (agrin), TAOK2, POLG (DNA polymerase gamma, catalytic subunit), KCNK2, OPRK1, ABCA2, ABCA7, LRRK2, CD200, PAK3, PADI2, EPHB1, CHAT (choline O-acetyltransferase) and SLC18A1 key for progression of neurological and neuropsychiatric disorders, but these genes might be liable for obesity associated type 2 diabetes mellitus. PLD2 [117], FLNA (filamin A) [118], SMURF1 [119], LINGO1 [120], CACNA1H [121], NLRP6 [122], NLRC3 [123], CXCR2 [124] and C5AR1 [125] are involved in hypertension, but these genes might be essential for progression of obesity associated type 2 diabetes mellitus.…”