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Lung cancer's enduring global significance necessitates ongoing advancements in diagnostics and therapeutics. Recent spotlight on proteomic and genetic biomarker research offers a promising avenue for understanding lung cancer biology and guiding treatments. This review elucidates genetic and proteomic lung cancer biomarker progress and their treatment implications. Technological strides in mass spectrometry-based proteomics and next-generation sequencing enable pinpointing of genetic abnormalities and abnormal protein expressions, furnishing vital data for precise diagnosis, patient classification, and customized treatments. Biomarker-driven personalized medicine yields substantial treatment improvements, elevating survival rates and minimizing adverse effects. Integrating omics data (genomics, proteomics, etc.) enhances understanding of lung cancer's intricate biological milieu, identifying novel treatment targets and biomarkers, fostering precision medicine. Liquid biopsies, non-invasive tools for real-time treatment monitoring and early resistance detection, gain popularity, promising enhanced management and personalized therapy. Despite advancements, biomarker repeatability and validation challenges persist, necessitating interdisciplinary efforts and large-scale clinical trials. Integrating artificial intelligence and machine learning aids analyzing vast omics datasets and predicting treatment responses. Single-cell omics reveal cellular connections and intratumoral heterogeneity, valuable for combination treatments. Biomarkers enable accurate diagnosis, tailored medicines, and treatment response tracking, significantly impacting personalized lung cancer care. This approach spurs patient-centered trials, empowering active patient engagement. Lung cancer proteomic and genetic biomarkers illuminate disease biology and treatment prospects. Progressing towards individualized efficient therapies is imminent, alleviating lung cancer's burden through ongoing research, omics integration, and technological strides.

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BACKGROUND: Glioblastoma multiforme (GBM) is one of the most malignant types of central nervous system tumors. GBM patients usually have a poor prognosis. Identification of genes associated with the progression of the disease is essential to explain the mechanisms or improve the prognosis of GBM by catering to targeted therapy. It is crucial to develop a methodology for constructing a biological network and analyze it to identify potential biomarkers associated with disease progression. METHODS: Gene expression datasets are obtained from TCGA data repository to carry out this study. A survival analysis is performed to identify survival associated genes of GBM patient. A gene co-expression network is constructed based on Pearson correlation between the gene's expressions. Various topological measures along with set operations from graph theory are applied to identify most influential genes linked with the progression of the GBM. RESULTS: Ten key genes are identified as a potential biomarkers associated with GBM based on centrality measures applied to the disease network. These genes are SEMA3B, APS, SLC44A2, MARK2, PITPNM2, SFRP1, PRLH, DIP2C, CTSZ, and KRTAP4.2. Higher expression values of two genes, SLC44A2 and KRTAP4.2 are found to be associated with progression and lower expression values of seven gens SEMA3B, APS, MARK2, PITPNM2, SFRP1, PRLH, DIP2C, and CTSZ are linked with the progression of the GBM. CONCLUSIONS: The proposed methodology employing a network topological approach to identify genetic biomarkers associated with cancer.

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BACKGROUND: The introduction of new targeted therapies for RET-altered lung and thyroid cancers (LC/TC) has impacted pathologists' practice by making genomic testing more relevant. Variations in health systems and treatment access result in distinct clinical challenges and barriers. This study aimed to assess practice gaps and challenges experienced by pathologists involved in the diagnosis of RET-altered LC/TC, including biomarker testing, to inform educational solutions. METHODS: Pathologists in Germany, Japan, the UK, and US participated in this ethics-approved mixed-methods study, which included interviews and surveys (data collected January-March 2020). Qualitative data was thematically analysed, quantitative data was analysed with chi-square and Kruskal-Wallis H-tests, and both were triangulated. RESULTS: A total of 107 pathologists took part in this study. Knowledge gaps were reported regarding genomic testing for LC/TC in Japan (79/60%), the UK (73/66%), and the US (53/30%). Skill gaps were reported when selecting genomic biomarker tests to diagnose TC in Japan (79%), the UK (73%) and US (57%) and when performing specific biomarker tests, especially in Japan (82% for RET) and in the UK (75% for RET). Japanese participants (80%) reported uncertainty about what information to share with the multidisciplinary team to ensure optimal patient-centered care. At the time of data collection, pathologists in Japan faced access barriers to using RET biomarker tests: only 28% agreed that there are relevant RET genomic biomarker tests available in Japan, versus 67% to 90% in other countries. CONCLUSIONS: This study identified areas where pathologists need additional continuing professional development opportunities to enhance their competencies and better support delivery of care to patients with RET-altered lung or thyroid tumours. Addressing identified gaps and improving competencies of pathologists in this field should be emphasised in continuing medical education curricula and through quality improvement initiatives. Strategies deployed on an institutional and health system level should aim to improve interprofessional communication and genetic biomarker testing expertise.

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BACKGROUND: Sorafenib and lenvatinib are tyrosine kinase inhibitors widely used in the targeted therapy to treat advanced hepatocellular carcinoma (aHCC). The GALNT14-rs9679162 genotype is a predictor of therapeutic outcome in multiple gastrointestinal cancers. OBJECTIVE: To investigate the predictive role of the GALNT14-rs9679162 genotype in aHCC treated with sorafenib or lenvatinib. METHODS: Totally 350 real-world patients with aHCC received sorafenib or lenvatinib were enrolled for GALNT14-rs9679162 genotyping and outcome analysis. Kaplan-Meier and Cox regression analysis were conducted to evaluate therapeutic outcomes. Cell-based assays were performed to determine the underlying mechanism. RESULTS: Kaplan-Meier and Cox regression analysis showed that the "GG" genotype was not associated with overall survival (OS) when all patients were included. However, it was associated with shorter OS in specific clinical subgroups, including anti-hepatitis C virus antibody-positive (n= 108; P= 0.005) and hepatitis B surface antigen-negative (n= 117; P= 0.002) patients. Intriguingly, hepatitis B virus X protein trans-suppressed the GALNT14 promoter, thereby reducing the elevated expression of GALNT14 in hepatoma cells, which partially contributed to the inability of the GALNT14-rs9679162 genotypes to predict the outcome of hepatitis B-related HCC. Finally, by analyzing the outcomes of 52 patients with aHCC treated with lenvatinib, patients with the "GG" genotype were associated with a favorable/shorter time-to-response (P= 0.013). CONCLUSIONS: The GALNT14-rs9679162 "GG" genotype predicted shorter OS in patients with HBsAg-negative aHCC treated with sorafenib, but predicted a favorable response in all patients with aHCC treated with lenvatinib.

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Antipsychotic-induced akathisia (AIA) is a movement disorder characterized by a subjective feeling of inner restlessness or nervousness with an irresistible urge to move, resulting in repetitive movements of the limbs and torso, while taking antipsychotics (APs). In recent years, there have been some associative genetic studies of the predisposition to the development of AIA. Objective: The goal of our study was to review the results of associative genetic and genome-wide studies and to systematize and update the knowledge on the genetic predictors of AIA in patients with schizophrenia (Sch). Methods: We searched full-text publications in PubMed, Web of Science, Springer, Google Scholar, and e-Library databases from 1977 to 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) quality scale was used for the critical selection of the studies. Results: We identified 37 articles, of which 3 were included in the review. Thus, the C allele of rs1800498 (59414 C>T) and the A allele of rs1800497 (17316 G>A) (TaqIA) from the DRD2 gene as well as the TT genotype rs13212041 (77461407 C>T) from the HTR1B gene were found to be associated with AIA. Conclusions: Uncovering the genetic biomarkers of AIA may provide a key to developing a strategy for the personalized prevention and treatment of this adverse neurological drug reaction of APs in patients with Sch in real clinical practice.

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Coronary Artery Diseases (CAD) remains the top among Non-communicable Diseases (NCDs). Variations in Apolipoprotein E (APOE) and Paroxonase 1 (PON1) have been associated with Myocardial Infarction (MI) in several populations. However, despite the high prevalence of CAD, no such study has been reported in the Pashtun ethnic population of Pakistan. We have conducted a two-stage (i.e., screening and validation) case-control study in which 200 cases and 100 control subjects have been recruited. In the first stage, Whole Exome Sequencing (WES) was used to screen for pathogenic variants of Myocardial Infarction (MI). In the second stage, selected variants of both APOE and PON1 genes (rs7412, rs429358, rs854560, and rs662) were analyzed through MassARRAY genotyping. Risk Allele Frequencies (RAFs) distribution and association of the selected SNPs with MI were determined using the Chi-square test and logistic regression analysis. WES identified a total of 12 sequence variants in APOE and 16 in PON1. Genotyping results revealed that APOE variant rs429358 (ɛ4 allele and ɛ3/ɛ4 genotype) showed significant association in MI patients (OR = 2.11, p value = 0.03; 95% CI = 1.25-2.43); whereas no significant difference (p˃ 0.05) was observed for rs7412. Similarly, the R allele of PON1 Q192R (rs662) was significantly associated with cases (OR = 1.353, p value = 0.048; 95% CI = 0.959-1.91), with particular mention of RR genotype (OR = 1.523, p value = 0.006; 95% CI = 1.087-2.132). Multiple logistic regression analysis showed that rs429358 (C allele) and rs662 (R allele) have a significantly higher risk of MI after adjustment for the conventional risk factors. Our study findings suggested that the rs429358 variant of APOE and PON1 Q192R are associated with MI susceptibility in the Pashtun ethnic population of Pakistan.

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BACKGROUND: The utilization of basket trials in oncology has gained popularity because of the drive for precision medicine and the increasing ease of genetically profiling tumors. However, it is unknown if this has translated into patient benefit, either through higher response rates because of precision treatment or because of increasing options for less-common tumor types that are less represented in oncology drug trials. We sought to characterize basket studies for oncology drugs targeting a genetic biomarker, determine the responses for various tumor types and genetic biomarkers, and test for correlation between the number of participants in each tumor basket and the incidence of the respective tumor. METHODS: We conducted a retrospective cross-sectional review of oncology basket trials on Embase or clinicaltrials.gov with published data. We included studies that reported on oncology drugs that target a genetic biomarker. We examined the response for basket trial participants, stratified by tumor type and genetic biomarker and the correlation between the number of participants in each tumor basket and the incidence of the respective tumor. RESULTS: The overall response rate for all 25 included trials was 23%. The response for each genetic biomarker ranged from 0 to 69%, and for half of the genetic biomarkers, the response rate ranged from 0 to 100%, depending on tumor type. There is low correlation between the number of participants in each tumor basket and the incidence of the respective tumor (66.41 + -0.20x, R2 = 0.003, p = 0.75). CONCLUSION: While there has been an increase in the number of published basket trials and individuals included in these trials, the response rate is low, but varies widely, depending on tumor type and genetic biomarker.

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BACKGROUND/AIM: Surface biomarkers, such as CD44 and CD133, have been demonstrated to be expressed in prostate cancer cells, and our previous study has shown that prostate cancer cell lines could be divided into three groups according to the single and combined expression pattern of CD44 and 133. In order to refine prognostication in prostate cancer cells, we further investigated genetic biomarkers, prostate cancer antigen 3 (PCA3), kallikrein 4 (KLK4), and KLK9 in different prostate cancer cell lines. MATERIALS AND METHODS: CWR22Rv1, PC3, and DU145 cell lines were cultured until 95% confluence. The single expression of CD44 or CD133 and their combined expression were analyzed by flow cytometry, and gene expression of b-actin, PCA3, KLK4, and KLK9 was analyzed by real-time polymerase chain reaction. RESULTS: The single expression of CD133 was less than 4% in all cell lines examined. PC3 and DU145 cells displayed a high expression of CD44 (>91%), whereas CWR22Rv1 was the only cell line that demonstrated a high co-expression of both CD44 and CD133 (>91%). In addition, PC3 and DU145 displayed low expression of PCA3, KLK4, and KLK9 when compared with their own b-actin expression. In contrast, CWR22Rva showed high expression of PCA3 and KLK4 although KLK9 expression was also low. CONCLUSION: Both surface and genetic biomarkers should be validated for a more accurate prognosis in prostate cancer.

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BACKGROUND: Nitric oxide (NO) is an important autocrine and paracrine signaling molecule that plays a crucial role in cardiovascular physiology and pathology regulation. NO is an important molecule involved in regulation of cerebral and extra cerebral cranial blood flow and arterial diameters. Reduced bioavailability of NO in the endothelium is an important precursor for impaired vasodilation and arterial hypertension (AH). Furthermore, NO is involved in nociceptive processing. A NO-induced biphasic response with immediate and a delayed headache is typical for chronic tension-type headaches (TTH) in humans. The aim was to study the association of allelic variants and genotypes of the single nucleotide variant (SNV) rs3782218 of the NOS1 gene with the TTH and AH overlap syndrome development in middle age adults. MATERIALS AND METHODS: We observed 91 Caucasian participants who resided in Krasnoyarsk city: group 1 (TTH and AH overlap syndrome)-30 patients; group 2 (AH without headache)-30 patients; group 3 (control)-31 healthy volunteers. The diagnosis of AH was based on criteria of the European Society of Cardiology and the European Society of Hypertension (2018) и criteria of the Russian Society of Cardiology (2020). Diagnosis of TTH was based on criteria of the International Classification of Headache Disorders (2018). Real-time polymerase chain reaction was used for the determination of allelic variants and genotypes of the SNV rs3782218 of the NOS1 gene in all groups of participants. RESULTS: The frequency of the minor allele T of rs3782218 was statistically significantly higher by 16.7 times in group 1 (TTH and AH) compared to group 3 (control): 26.7% versus 1.6%, respectively (p-value = 0.000065) and 3.2 times higher in group 1 (TTH and AH) compared to group 2 (AH without headache): 26.7% versus 8.3%, respectively (p-value = 0.008). The frequency of the heterozygous (CT) genotype was statistically significantly higher in group 1 (TTH and AH) compared to group 3 (control): 40.0% versus 3.2% (p-value = 0.000454) and in group 1 (TTH and AH) compared to group 2 (AH without headache): 40.0% versus 16.7% (p-value = 0.045). The minor allele T was statistically significantly associated with a high risk of developing the TTH and AH overlap syndrome compared with the controls (odds ratio (OR) = 22.2 (95% confidential interval (CI): 2.8-173.5)) and compared with AH without headache (OR = 4.0 (95% CI: 1.4-11.8)). Although the frequency of the minor allele T was 5.2 times higher in group 2 (AH without headache) compared with group 3 (control), there were not statistically significantly differences (p-value = 0.086). CONCLUSION: Thus, the minor allele T of rs3782218 of the NOS1 gene is an important genetic biomarker for a high risk of developing the TTH and AH overlap syndrome in hypertensive patients.

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Background: Axial spondyloarthritis (axSpA) is a chronic inflammatory condition of the spine. In addition to musculoskeletal symptoms, there are also extra-articular manifestations. The aim of this study was to search for new biomarkers associated with the clinical presentation and treatment response in axSpA patients. Methods: In this study, 106 axSpA patients and 110 healthy controls were enrolled. Six single-nucleotide polymorphisms (SNPs) were selected for genotyping: ERAP1 rs2287987, ERAP2 rs2549782, TNF rs1800629, TNFRSF1A rs767455, TNFRSF1B rs1061622, and FCGR2A rs1801274. Participants were examined at baseline and after 12 and 24 weeks of anti-TNF therapy. Results: SNPs associated with high axSpA initial activity were TNFRSF1A rs767455 and TNFRSF1B rs1061622 (p < 0.008). The ERAP1 rs2287987 AA genotype was more frequently observed in patients with enthesitis (AA vs. G+, p = 0.049), while the TNFRSF1B rs1061622 GG genotype was more common in participants with uveitis (GG vs. TT, p = 0.042). Potential in predicting anti-TNF treatment response was demonstrated by ERAP1 rs2287987, ERAP2 rs2549782, TNFRSF1B rs1061622, and FCGR2A rs1801274. Conclusions: SNPs can be used to identify patients at risk of severe disease to initiate treatment earlier. Genetic testing will allow clinicians to choose the right drug for the patient.

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Background: Neoadjuvant chemoradiotherapy (nCRT) prior to surgery is considered standard therapy for locally advanced rectal cancer. Unfortunately, most patients with rectal cancer are resistant to radiotherapy. This might be a genetic cause. The role of certain rectal cancer-causing genes has not been completely elucidated. This study aims to investigate the genes responsible for locally advanced rectal cancer patients not reacting to radiotherapy. Methods: Whole exome sequencing of the DNA samples was performed on the samples. Bioinformatic analysis on the subjects was established. Individual genetic information was screened to identify differently expressed genes that more frequently appeared in non-complete response (NCR) compared to complete response (CR) patients after nCRT. All variations were verified by Sanger sequencing. Results: Genotyping information and pathway analyses of the samples indicated genes such as FLCN, CALML5, and ANTXR1 to be commonly mutated in CR group, whereas genes such as GALNTL14, CNKSR1, ACD, and CUL3 were more commonly mutated in the NCR group. Chi-square test revealed some significant variants (<0.05) such as rs3744124 (FLCN), rs28365986 (ANTXR1), rs10904516 (CALML5), rs3738952 (CUL3), rs13394 and rs2293013 (PIH1D1), rs2274531 (GPA33), rs4963048 (BRSK2), rs17883366 (IL3RA), rs2297575 (PSMD5), rs2288101 (GALNT14), and rs11954652 (DCTN4). Conclusion: Identifying an array of genes that separate NCRs from CRs would lead to finding genetic biomarkers for early detection of rectal cancer patients that are resistant to nCRT. A further investigation to validate the significance of genetic biomarkers to segregate NCRs from CRs should be performed with a larger CRC dataset. Protein expression levels, as well as transcriptomic analysis, would also help us understand the mechanism of how these genes could play a role in preventing radiation therapy to patients. This would be essential to prevent redundant radiation therapy.

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Nasopharyngeal carcinoma (NPC) is an epithelial tumor with high prevalence in southern China and Southeast Asia. NPC is well associated with the Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) 30 bp deletion by having its vital role in increased tumorigenicity and decreased immune recognition of EBV-related tumors. This study developed an InnoPrimers-duplex qPCR for detection of NPC blood circulating LMP1 30 bp deletion genetic biomarker for early diagnosis and treatment response prediction of NPC patients. The analytical and diagnostic evaluation and treatment response prediction were conducted using NPC patients' whole blood (WB) and tissue samples and non-NPC cancer patients and healthy individuals' WB samples. The assay was able to detect as low as 20 ag DNA per reaction (equivalent to 173 copies) with high specificity against broad reference microorganisms and archive NPC biopsy tissue and FNA samples. The diagnostic sensitivity and specificity were 83.3% and 100%, respectively. The 30 bp deletion genetic biomarker was found to be a good prognostic biomarker associated with overall clinical outcome of NPC WHO type III patients. This sensitive and specific assay can help clinicians in early diagnosis and treatment response prediction of NPC patients, which will enhance treatment outcome and lead to better life-saving.

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BACKGROUND: Cancers of unknown primary (CUP) are highly aggressive tumours with limited molecular characterization. These tumours can be particularly sensitive to immune checkpoint inhibitors (ICI) by mounting a seemingly more effective anti-tumour immune response. Unlike other tumour lineages, the biological basis and clinical efficacy of ICI in CUP remain largely unknown. MATERIALS AND METHODS: The cBioPortal database was accessed to select eligible cases from the MSK-IMPACTTM Clinical Sequencing Cohort. The tumour cell genomic correlates of response and resistance to ICI in patients with CUP were compared to those with ICI-eligible tumours: cervical cancer, gastric cancer, renal cell carcinoma, hepatocellular carcinoma, non-small-cell lung cancer, melanoma, Merkel cell carcinoma and urothelial bladder cancer. RESULTS: Among a total of 234 patients with CUP, the identified genomic alterations were mainly mutation correlates of resistance to ICI, notably mutations in oncogenic signalling pathways including KRAS, STK11 and EGFR (24.7%, 10.9% and 4.2%, respectively). Compared to other tumours considered eligible for ICI, CUP presents a higher prevalence of alterations in the oncogenic signalling pathways KRAS and STK11. CUP patients treated with ICI had similar median overall survival with and without genomic correlates of response and resistance to ICI. An exploratory analysis showed that patients with TMB >10 mutations had a trend for better outcomes. CONCLUSIONS: A tumour mutation burden >10 mutations per megabase can provide a potential genomic correlate of response to ICI in patients with CUP. Further research is warranted to validate these findings.

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Addiction is characterized by drug-craving, compulsive drug-taking, and relapse, and results from the interaction between multiple genetic and environmental factors. Reward pathways play an important role in mediating drug-seeking and drug-taking behaviors, and relapse. The objective of this study was to identify heroin addicts who carry specific genetic variants in their dopaminergic reward systems. A total of 326 heroin-dependent patients undergoing methadone maintenance therapy (MMT) were recruited from the Addiction Center of the China Medical University Hospital. A heroin-use and craving questionnaire was used to evaluate the urge for heroin, the daily or weekly frequency of heroin usage, daily life disturbance, anxiety, and the ability to overcome heroin use. A general linear regression model was used to assess the associations of genetic polymorphisms in one's dopaminergic reward system with heroin-use and craving scores. Results: The most significant results were obtained for rs2240158 in GRIN3B (p = 0.021), rs3983721 in GRIN3A (p = 0.00326), rs2129575 in TPH2 (p = 0.033), rs6583954 in CYP2C19 (p = 0.033), and rs174699 in COMT (p = 0.036). These were all associated with heroin-using and craving scores with and without adjustments for age, sex, and body mass index. We combined five variants, and the ensuing dose-response effect indicated that heroin-craving scores increased with the numbers of risk alleles (p for trend = 0.0008). These findings will likely help us to understand the genetic mechanism of craving, which will help in predicting the risk of relapse in clinical practice and the potential for therapies to target craving in heroin addiction.

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Attention-deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by a persistent pattern of inattention, hyperactivity, and impulsivity. Since the diagnosis of ADHD is defined by operational diagnostic criteria consisting of several clinical symptoms, a number of heterogeneous mechanisms have been considered to be implicated in its pathophysiology. Although no clinically reliable biomarkers are available for the diagnosis of ADHD, several plausible candidate biomarkers have been proposed based on recent advances in biochemistry and molecular biology. This review article summarizes potential peripheral biomarkers associated with ADHD, mainly from recently published case-control studies. These include 1) biochemical markers: neurotransmitters and their receptors, neurotrophic factors, serum electrolytes, and inflammation markers; 2) genetic and epigenetic markers: microRNA, mRNA expression, and peripheral DNA methylation; 3) physiological markers: eye movement and electroencephalography. It also discusses the limitations and future directions of these potential biomarkers for application in clinical practice.

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(1) Background: Although panic disorder (PD) is one of the most common anxiety disorders severely impacting quality of life, no effective genetic testing exists; known data on possible genetic biomarkers is often scattered and unsystematic which complicates further studies. (2) Methods: We used PathwayStudio 12.3 (Elsivier, Netherlands) to acquire literature data for further manual review and analysis. 229 articles were extracted, 55 articles reporting associations, and 32 articles reporting no associations were finally selected. (3) Results: We provide exhaustive information on genetic biomarkers associated with PD known in the scientific literature. Data is presented in two tables. Genes COMT and SLC6A4 may be considered the most promising for PD diagnostic to date. (4) Conclusions: This review illustrates current progress in association studies of PD and may indicate possible molecular mechanisms of its pathogenesis. This is a possible basis for data analysis, novel experimental studies, or developing test systems and personalized treatment approaches.

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BACKGROUND: Migraine is a polygenetic disease, considered as a channelopathy. The dysregulation of ion functioning due to genetic changes may activate the trigeminovascular system and induce migraine attack both migraine with aura (MA) and without aura (MO). OBJECTIVES: The aim of the study was to analyze the following variants of genes encoding ion channels and associated protein: c.3199G>A SCN1A, c.56G>A SCN2A, c.28A>G and c.328T>C KCNK18, c.3053A>G TRPA1, c.31-1811C>T STX1A in migraine patients. PATIENTS AND METHODS: The study included 170 migraine patients and 173 controls. HRMA and Sanger sequencing were used for genotyping. Meta-analysis was performed for c.28A>G, c.328T>C KCNK18, and c.31-1811C>T STX1A. RESULTS: AA genotype of c.56G>A SCN2A was found only in migraine patients. Patients with c.328T>C KCNK18 mutation had an increased risk of developing migraine before the age of 18. Moreover, individuals with AA/TC haplotype of KCNK18 had higher attack frequency than those with AA/TT (p<0.05). T allele of c.31-1811C>T STX1A was more frequent in MA patients than MO (p<0.05). The c.3053A>G TRPA1 polymorphism was more common in patients with migraine onset before the age of 15 (p<0.05), while c.31-1811C>T STX1A and c.3199G>A SCN1A before the age of 10 (p<0.01). Meta-analysis showed a significant association of c.31-1811C>T STX1A polymorphism with migraine overall (OR=1.22, p=0.0086), MA, and MO. No association was found for c.28A>G KCNK18, c.328T>C KCNK18, and migraine overall. CONCLUSION: Changes in genes encoding ion channels or proteins regulating their functioning may increase the risk of migraines and correlate with clinical features of disease, e.g. age of onset and attack frequency.

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The rs2229611 SNP (G6PC:c.*23T>C) in the 3'UTR region of the G6PC gene affects the stability of the glucose-6-phosphatase mRNA and occurs in a higher frequency in patients with glycogenosis Ia (GSD Ia) in some populations. Herein, a group of Brazilian patients (n = 116) was analyzed by NGS and the frequency of rs2229611:T>C was determined. The linkage disequilibrium (LD) between pathogenic variants and the rs2229611:T>C SNP was evaluated. The results showed that the rs2229611:T>C is associated to GSD Ia and is in LD with the most frequent pathogenic variants in Brazilian patients with GSD Ia.

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Epilepsy, a neurological disease characterized by recurrent seizures, is highly heterogeneous in nature. Based on the prevalence, epilepsy is classified into two types: common and rare epilepsies. Common epilepsies affecting nearly 95% people with epilepsy, comprise generalized epilepsy which encompass idiopathic generalized epilepsy like childhood absence epilepsy, juvenile myoclonic epilepsy, juvenile absence epilepsy and epilepsy with generalized tonic-clonic seizure on awakening and focal epilepsy like temporal lobe epilepsy and cryptogenic focal epilepsy. In 70% of the epilepsy cases, genetic factors are responsible either as single genetic variant in rare epilepsies or multiple genetic variants acting along with different environmental factors as in common epilepsies. Genetic testing and precision treatment have been developed for a few rare epilepsies and is lacking for common epilepsies due to their complex nature of inheritance. Precision medicine for common epilepsies require a panoramic approach that incorporates polygenic background and other non-genetic factors like microbiome, diet, age at disease onset, optimal time for treatment and other lifestyle factors which influence seizure threshold. This review aims to comprehensively present a state-of-art review of all the genes and their genetic variants that are associated with all common epilepsy subtypes. It also encompasses the basis of these genes in the epileptogenesis. Here, we discussed the current status of the common epilepsy genetics and address the clinical application so far on evidence-based markers in prognosis, diagnosis, and treatment management. In addition, we assessed the diagnostic predictability of a few genetic markers used for disease risk prediction in individuals. A combination of deeper endo-phenotyping including pharmaco-response data, electro-clinical imaging, and other clinical measurements along with genetics may be used to diagnose common epilepsies and this marks a step ahead in precision medicine in common epilepsies management.

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