Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder, primarily characterized by motor dysfunction resulting from the degeneration of dopaminergic neurons. Early and accurate diagnosis is crucial for effective treatment; however, the overlap of symptoms with other disorders frequently results in misdiagnosis. This study aims to identify reliable biomarkers for the early PD diagnosis through a comprehensive literature review and bioinformatics analysis. We initially identified 32 genes strongly associated with PD, from published studies and database annotations. Further bioinformatics validation using protein-protein interaction networks and external gene expression datasets revealed additional candidate genes, including GBA1 and LRRK2, which are relevant to both familial and sporadic forms of PD. Enrichment analyses of these genes, emphasizing pathways related to mitochondrial function, autophagy and neurodegeneration-related pathways. Our findings highlight the promise of genetic biomarkers in improving diagnostic precision and guiding therapeutic approaches, thereby enhancing clinical outcomes for patients with PD. Ongoing validation of these results is essential for integrating biomarkers into standard clinical practice, with the ultimate goal of revolutionizing the diagnosis and management of PD.
{"title":"Exploring Parkinson's disease: Insights from genetic biomarkers and protein-protein interactions","authors":"Zahra Parani , Yeganeh Sorayaei , Mohammad Shokrzadeh , Nargess Abdali , Elham Rismani","doi":"10.1016/j.humgen.2025.201523","DOIUrl":"10.1016/j.humgen.2025.201523","url":null,"abstract":"<div><div>Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder, primarily characterized by motor dysfunction resulting from the degeneration of dopaminergic neurons. Early and accurate diagnosis is crucial for effective treatment; however, the overlap of symptoms with other disorders frequently results in misdiagnosis. This study aims to identify reliable biomarkers for the early PD diagnosis through a comprehensive literature review and bioinformatics analysis. We initially identified 32 genes strongly associated with PD, from published studies and database annotations. Further bioinformatics validation using protein-protein interaction networks and external gene expression datasets revealed additional candidate genes, including GBA1 and LRRK2, which are relevant to both familial and sporadic forms of PD. Enrichment analyses of these genes, emphasizing pathways related to mitochondrial function, autophagy and neurodegeneration-related pathways. Our findings highlight the promise of genetic biomarkers in improving diagnostic precision and guiding therapeutic approaches, thereby enhancing clinical outcomes for patients with PD. Ongoing validation of these results is essential for integrating biomarkers into standard clinical practice, with the ultimate goal of revolutionizing the diagnosis and management of PD.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201523"},"PeriodicalIF":0.7,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi Drug Resistance (MDR) of cancer cells is the most important cause for the failure of chemotherapy in treating cancer patients. Hence, identification of appropriate drug resistance biomarkers is the need of the hour to optimize treatment regimen. The goal of this study is to identify critical genes and pathways that could be used to predict the drug resistance in colon cancer patients. In this study, gene expression datasets of colon cancer patients and cell lines treated with 5-fluorouracil, irinotecan and oxaliplatin were obtained. Differential gene expression analysis was performed and the hub genes associated with drug resistance were identified through network analysis. The functional and pathway enrichment of the genes were performed. ABCC4, AKR1C3, CASP3, CASP4, IFITM1, IFITM2, IFITM3, IFI6, IFI44, IFI16, IFI27 and SLC1A7 were found to be highly interacting (Hub) genes in the network analysis. Two significant modules were predicted in the generated network by module analysis. The genes of module 2 were observed to be highly interacting with each other in the pathway cross talk analysis. Among the identified genes, IFI44 was significantly associated with the patients' overall survival. In addition, IFI44 found to be associated with immune infiltration in the tumor microenvironment. In addition, B-cell receptor signalling pathway, galactose metabolism, steroid hormone biosynthesis and folate biosynthesis pathway can be targeted for improving the efficacy of chemotherapeutic drugs, while treating multidrug resistant colon cancer. Hence, IFI44 could be used as a biomarker for identifying drug resistance. Further, experimental studies are required to validate our findings.
{"title":"Identification of key players in drug resistant colon cancer - An integrative network pharmacology approach","authors":"Jeevitha Priya Manoharan , Neha Saravanakumar , Hema Palanisamy , Subramanian Vidyalakshmi","doi":"10.1016/j.humgen.2025.201521","DOIUrl":"10.1016/j.humgen.2025.201521","url":null,"abstract":"<div><div>Multi Drug Resistance (MDR) of cancer cells is the most important cause for the failure of chemotherapy in treating cancer patients. Hence, identification of appropriate drug resistance biomarkers is the need of the hour to optimize treatment regimen. The goal of this study is to identify critical genes and pathways that could be used to predict the drug resistance in colon cancer patients. In this study, gene expression datasets of colon cancer patients and cell lines treated with 5-fluorouracil, irinotecan and oxaliplatin were obtained. Differential gene expression analysis was performed and the hub genes associated with drug resistance were identified through network analysis. The functional and pathway enrichment of the genes were performed. ABCC4, AKR1C3, CASP3, CASP4, IFITM1, IFITM2, IFITM3, IFI6, IFI44, IFI16, IFI27 and SLC1A7 were found to be highly interacting (Hub) genes in the network analysis. Two significant modules were predicted in the generated network by module analysis. The genes of module 2 were observed to be highly interacting with each other in the pathway cross talk analysis. Among the identified genes, IFI44 was significantly associated with the patients' overall survival. In addition, IFI44 found to be associated with immune infiltration in the tumor microenvironment. In addition, B-cell receptor signalling pathway, galactose metabolism, steroid hormone biosynthesis and folate biosynthesis pathway can be targeted for improving the efficacy of chemotherapeutic drugs, while treating multidrug resistant colon cancer. Hence, IFI44 could be used as a biomarker for identifying drug resistance. Further, experimental studies are required to validate our findings.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201521"},"PeriodicalIF":0.7,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diabetes is a lifestyle disorder with the highest mortality rate, and mitochondria play a crucial role in the susceptibility and severity of diabetes. This study examined the relationship between mitochondrial genomic variants and lifestyle factors in patients with type 2 diabetes (T2D) within a rural central Indian population. We enrolled 156 participants with diabetes and 108 healthy participants, analysing their anthropometric measurements, lifestyle habits, and mitochondrial DNA (mtDNA) variants. A total of 74 variants were identified, with the D-loop region showing the highest mutation rates. When correlated with BMI, waist-to-hip ratio, and sedentary behaviour, these factors were significantly higher in the diabetes group than in the control group. The variants A10398G and C10400T in ND3 and C16223T in the D-loop were significantly associated with T2D, while T16093C and A3384G were more common in healthy controls, indicating a protective role. Analysing haplogroups revealed that the M haplogroup was the most prevalent, followed by U and H, with H being significantly more common in the healthy group. Additionally, lifestyle factors such as a high-carbohydrate diet and tobacco use contributed to disease progression. This study underscores that certain novel variants are linked to decreased susceptibility to T2D and highlights the complex interaction between mtDNA variants, lifestyle factors, and T2D in the Indian population.
{"title":"Mitochondrial ND3, tRNA (Leu) and hypervariable region I: Variants in type II diabetes patients from the central rural Indian population.","authors":"Tejas Tajane , Mamata Chandrakar , Prafulla Ambulkar , Pranita Waghmare , Bharati Taksande , Jwalant Waghmare","doi":"10.1016/j.humgen.2025.201520","DOIUrl":"10.1016/j.humgen.2025.201520","url":null,"abstract":"<div><div>Diabetes is a lifestyle disorder with the highest mortality rate, and mitochondria play a crucial role in the susceptibility and severity of diabetes. This study examined the relationship between mitochondrial genomic variants and lifestyle factors in patients with type 2 diabetes (T2D) within a rural central Indian population. We enrolled 156 participants with diabetes and 108 healthy participants, analysing their anthropometric measurements, lifestyle habits, and mitochondrial DNA (mtDNA) variants. A total of 74 variants were identified, with the D-loop region showing the highest mutation rates. When correlated with BMI, waist-to-hip ratio, and sedentary behaviour, these factors were significantly higher in the diabetes group than in the control group. The variants A10398G and C10400T in ND3 and C16223T in the D-loop were significantly associated with T2D, while T16093C and A3384G were more common in healthy controls, indicating a protective role. Analysing haplogroups revealed that the M haplogroup was the most prevalent, followed by U and H, with H being significantly more common in the healthy group. Additionally, lifestyle factors such as a high-carbohydrate diet and tobacco use contributed to disease progression. This study underscores that certain novel variants are linked to decreased susceptibility to T2D and highlights the complex interaction between mtDNA variants, lifestyle factors, and T2D in the Indian population.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201520"},"PeriodicalIF":0.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-28DOI: 10.1016/j.humgen.2025.201519
Annamalai R , Venkatramanaiah C , Marimuthu Raja , Santhosh Kumar Yasam , Sujhithra A , Catherine Rexy , Vignesh Narasimman , D. Danis Vijay
Background & aim
Knee osteoarthritis (KOA)1 is a common degenerative joint disease characterized by progressive cartilage breakdown that leads to pain and reduced mobility. Although genetic predisposition including the double von Willebrand factor A (DVWA; rs7639618) gene polymorphism has been implicated in KOA, previous case–control studies have reported inconsistent findings. This updated meta-analysis aims to clarify the association between the DVWA (rs7639618) gene polymorphism and KOA susceptibility.
Materials & methods
A systematic search was performed in Pub Med, Web of Science, Science Direct, and Google Scholar for case–control studies published up to June 2025. Eligible studies reported genotype and allele distributions for rs7639618 in KOA cases and controls. Study quality was assessed using the Newcastle–Ottawa Scale (NOS).2 Odds ratios (ORs)3 with 95 % confidence intervals (CIs)4 were calculated under allele, recessive, dominant, and over-dominant models. Heterogeneity was evaluated using the Q test and I2 statistic, and random- or fixed-effects models were applied accordingly. Subgroup analyses were conducted by ethnicity, and publication bias was assessed with funnel plots and Egger's test. Sensitivity analysis was carried out by excluding each study.
Results
Thirteen studies comprising 7110 KOA cases and 6931 controls were included. Pooled analyses across all genetic models showed no statistically significant association between rs7639618 and KOA susceptibility. For the allele contrast model, the overall OR was 1.03 (95 % CI: 0.90–1.19); for the recessive model, OR was 1.06 (95 % CI: 0.90–1.25); for the dominant model, OR was 1.08 (95 % CI: 0.85–1.38); and for the over-dominant model, OR was 0.98 (95 % CI: 0.91–1.05). Subgroup analyses revealed no increased risk in either Asian or Caucasian populations. Sensitivity analysis confirmed the stability of the results, and no significant publication bias was detected.
Conclusion
The findings of this meta-analysis suggest that the DVWA (rs7639618) polymorphism is not significantly associated with KOA susceptibility in the overall population or within specific ethnic groups. Despite the rigorous methodology and comprehensive analysis, the presence of substantial heterogeneity in some genetic models underscores the need for further well-designed, large-scale studies across diverse populations.
{"title":"Association of DVWA (rs7639618) gene polymorphisms with knee osteoarthritis susceptibility: An updated systematic review and meta-analysis","authors":"Annamalai R , Venkatramanaiah C , Marimuthu Raja , Santhosh Kumar Yasam , Sujhithra A , Catherine Rexy , Vignesh Narasimman , D. Danis Vijay","doi":"10.1016/j.humgen.2025.201519","DOIUrl":"10.1016/j.humgen.2025.201519","url":null,"abstract":"<div><h3>Background & aim</h3><div>Knee osteoarthritis (KOA)<span><span><sup>1</sup></span></span> is a common degenerative joint disease characterized by progressive cartilage breakdown that leads to pain and reduced mobility. Although genetic predisposition including the double von Willebrand factor A (DVWA; rs7639618) gene polymorphism has been implicated in KOA, previous case–control studies have reported inconsistent findings. This updated meta-analysis aims to clarify the association between the DVWA (rs7639618) gene polymorphism and KOA susceptibility.</div></div><div><h3>Materials & methods</h3><div>A systematic search was performed in Pub Med, Web of Science, Science Direct, and Google Scholar for case–control studies published up to June 2025. Eligible studies reported genotype and allele distributions for rs7639618 in KOA cases and controls. Study quality was assessed using the Newcastle–Ottawa Scale (NOS).<span><span><sup>2</sup></span></span> Odds ratios (ORs)<span><span><sup>3</sup></span></span> with 95 % confidence intervals (CIs)<span><span><sup>4</sup></span></span> were calculated under allele, recessive, dominant, and over-dominant models. Heterogeneity was evaluated using the Q test and I<sup>2</sup> statistic, and random- or fixed-effects models were applied accordingly. Subgroup analyses were conducted by ethnicity, and publication bias was assessed with funnel plots and Egger's test. Sensitivity analysis was carried out by excluding each study.</div></div><div><h3>Results</h3><div>Thirteen studies comprising 7110 KOA cases and 6931 controls were included. Pooled analyses across all genetic models showed no statistically significant association between rs7639618 and KOA susceptibility. For the allele contrast model, the overall OR was 1.03 (95 % CI: 0.90–1.19); for the recessive model, OR was 1.06 (95 % CI: 0.90–1.25); for the dominant model, OR was 1.08 (95 % CI: 0.85–1.38); and for the over-dominant model, OR was 0.98 (95 % CI: 0.91–1.05). Subgroup analyses revealed no increased risk in either Asian or Caucasian populations. Sensitivity analysis confirmed the stability of the results, and no significant publication bias was detected.</div></div><div><h3>Conclusion</h3><div>The findings of this meta-analysis suggest that the DVWA (rs7639618) polymorphism is not significantly associated with KOA susceptibility in the overall population or within specific ethnic groups. Despite the rigorous methodology and comprehensive analysis, the presence of substantial heterogeneity in some genetic models underscores the need for further well-designed, large-scale studies across diverse populations.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201519"},"PeriodicalIF":0.7,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Colorectal cancer (CRC) progression involves complex molecular mechanisms that remain incompletely understood. This study investigated the expression and functional significance of calumenin (CALU) in CRC pathogenesis. Bioinformatic analyses revealed significant CALU upregulation in CRC compared to normal tissues, with expression increasing progressively from primary to metastatic tumors. Protein-protein interaction networks positioned CALU as a hub gene interacting with multiple cancer-associated proteins. Single-cell RNA sequencing revealed cell-type-specific CALU expression patterns, with the highest levels observed in tumor-derived colonic goblet cells, colonocytes, and fibroblasts. MicroRNA target prediction algorithms identified miR-30a as a potential CALU regulator, which we confirmed through luciferase reporter assays. In CRC tissues and cell lines, miR-30a expression was significantly downregulated and inversely correlated with CALU levels. Functionally, restoration of miR-30a expression in CRC cells suppressed CALU expression, inhibited proliferation, induced G0/G1 cell cycle arrest, promoted apoptosis, and reduced migration and invasion capabilities. These effects were rescued by CALU overexpression, confirming CALU as a functional target of miR-30a. Analysis of 50 paired clinical specimens supported these findings, with CALU upregulation and miR-30a downregulation correlating with poor differentiation and lymph node metastasis. Our findings introduce the miR-30a/CALU axis as a potential therapeutic target in CRC.
{"title":"Comprehensive in silico and in vitro studies reveal the miR-30a/CALU axis as a potential therapeutic target in colorectal cancer","authors":"Parinaz Nasri Nasrabadi , Forouzandeh Mahjoubi , Gilles A. Robichaud , Fatemeh Masoumi , Alireza Zomorodipour","doi":"10.1016/j.humgen.2025.201518","DOIUrl":"10.1016/j.humgen.2025.201518","url":null,"abstract":"<div><div>Colorectal cancer (CRC) progression involves complex molecular mechanisms that remain incompletely understood. This study investigated the expression and functional significance of calumenin (CALU) in CRC pathogenesis. Bioinformatic analyses revealed significant CALU upregulation in CRC compared to normal tissues, with expression increasing progressively from primary to metastatic tumors. Protein-protein interaction networks positioned CALU as a hub gene interacting with multiple cancer-associated proteins. Single-cell RNA sequencing revealed cell-type-specific CALU expression patterns, with the highest levels observed in tumor-derived colonic goblet cells, colonocytes, and fibroblasts. MicroRNA target prediction algorithms identified miR-30a as a potential CALU regulator, which we confirmed through luciferase reporter assays. In CRC tissues and cell lines, miR-30a expression was significantly downregulated and inversely correlated with CALU levels. Functionally, restoration of miR-30a expression in CRC cells suppressed CALU expression, inhibited proliferation, induced G0/G1 cell cycle arrest, promoted apoptosis, and reduced migration and invasion capabilities. These effects were rescued by CALU overexpression, confirming CALU as a functional target of miR-30a. Analysis of 50 paired clinical specimens supported these findings, with CALU upregulation and miR-30a downregulation correlating with poor differentiation and lymph node metastasis. Our findings introduce the miR-30a/CALU axis as a potential therapeutic target in CRC.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201518"},"PeriodicalIF":0.7,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several investigations have noted to the potential link between Vitamin D Receptor (VDR) gene polymorphisms and autism spectrum disorder (ASD); however, the findings have been controversial. To find a convincing answer, we performed this meta-analysis to identify a reliable understanding for plausible association of VDR gene SNPs and risk of ASD susceptibility. A systematic search was performed to search for relevant studies assessing the association between the Cdx (rs11568820), TaqI (rs731236), FokI (rs2228570), ApaI (rs7975232), and BsmI (rs1544410) SNPs of the VDR gene and susceptibility to ASD released before January 2024. Odd Ratio (OR) and 95 % CI were used to show statistical relationship between the VDR gene SNPs and ASD. In the final analysis 14 studies containing 2023 ASD patients and 2008 healthy individuals were included. The comprehensive analysis revealed that the TaqI variant across all genotypes, and the FokI variant in recessive, allelic, and homozygote genetic models, were associated with an increased risk of ASD. According to the findings of this meta-analysis, TaqI and FokI SNPs play a role in predisposition to ASD; however, because of limitation in sample size and geographical distribution of included studies, findings should be interpreted cautiously.
{"title":"Vitamin D receptor gene polymorphisms and the risk of autism spectrum disorder (ASD): A meta-analysis","authors":"Ghasem Fakourizad , Alireza Hatami , Saeed Aslani , Mohammad Masoud Eslami , Danyal Imani , Bahman Razi , Tannaz Jamialahmadi , Prashant Kesharwani , Amirhossein Sahebkar","doi":"10.1016/j.humgen.2025.201517","DOIUrl":"10.1016/j.humgen.2025.201517","url":null,"abstract":"<div><div>Several investigations have noted to the potential link between <em>Vitamin D Receptor</em> (<em>VDR</em>) gene polymorphisms and autism spectrum disorder (ASD); however, the findings have been controversial. To find a convincing answer, we performed this meta-analysis to identify a reliable understanding for plausible association of <em>VDR</em> gene SNPs and risk of ASD susceptibility. A systematic search was performed to search for relevant studies assessing the association between the Cdx (rs11568820), TaqI (rs731236), <em>Fok</em>I (rs2228570), <em>Apa</em>I (rs7975232), and <em>Bsm</em>I (rs1544410) SNPs of the <em>VDR</em> gene and susceptibility to ASD released before January 2024. Odd Ratio (OR) and 95 % CI were used to show statistical relationship between the <em>VDR</em> gene SNPs and ASD. In the final analysis 14 studies containing 2023 ASD patients and 2008 healthy individuals were included. The comprehensive analysis revealed that the TaqI variant across all genotypes, and the <em>Fok</em>I variant in recessive, allelic, and homozygote genetic models, were associated with an increased risk of ASD. According to the findings of this meta-analysis, TaqI and FokI SNPs play a role in predisposition to ASD; however, because of limitation in sample size and geographical distribution of included studies, findings should be interpreted cautiously.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201517"},"PeriodicalIF":0.7,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-24DOI: 10.1016/j.humgen.2025.201516
Taisir A. Kadhim , Randa R. Ghamyes , Dhay A. Azeez , Mustafa A. Bashi , Ali A. Alsodani , Mohammed K. Al-Qayyim , Noor T. Kadhim , Rawan A. Nijeeb , Dhuha F.N. Bani-Wais , Ali H. Ad'hiah
Acute myeloid leukemia (AML) is a genetically heterogeneous malignant hematopoietic disorder, and research continues to update its genetic drivers. Golgi-associated PDZ and coiled-coil motif-containing (GOPC) is a signaling protein implicated in regulating cellular trafficking of transmembrane proteins. Recent research has shown that the gene encoding GOPC exhibits dysregulated expression in colorectal cancer. In AML, the significance of GOPC expression in disease risk and pathogenesis has not been explored. Therefore, a case-control study was conducted to evaluate GOPC mRNA expression in a cohort of 100 AML patients and 100 controls. GOPC expression was quantified using a reverse transcription-quantitative PCR-based fold change method (2–ΔCt). Statistical data management included receiver-operating characteristic (ROC) curve analysis, disease-risk assessment, and assessment of correlation with AML characteristics. Results revealed that GOPC expression levels (median [interquartile range: 25–75 %]) were significantly decreased in patients compared to controls (0.04 [0.02–0.14] vs. 0.73 [0.18–1.16]; probability <0.001). ROC curve analysis demonstrated the reliability of GOPC expression in distinguishing between AML patients and controls (area under the curve = 0.91; probability <0.001). Disease-risk assessment indicated that low GOPC expression was linked to a 16.15-fold increased risk of AML. GOPC expression was not affected by clinical and genetic characteristics of AML or chemotherapy and was not correlated with diagnostic laboratory criteria. In conclusion, GOPC mRNA expression was down-regulated in AML and was not affected by the patient's clinical, genetic, or laboratory characteristics. Low GOPC expression may be considered a potential risk factor for AML.
{"title":"Low GOPC mRNA expression is a novel candidate associated with increased risk of acute myeloid leukemia","authors":"Taisir A. Kadhim , Randa R. Ghamyes , Dhay A. Azeez , Mustafa A. Bashi , Ali A. Alsodani , Mohammed K. Al-Qayyim , Noor T. Kadhim , Rawan A. Nijeeb , Dhuha F.N. Bani-Wais , Ali H. Ad'hiah","doi":"10.1016/j.humgen.2025.201516","DOIUrl":"10.1016/j.humgen.2025.201516","url":null,"abstract":"<div><div>Acute myeloid leukemia (AML) is a genetically heterogeneous malignant hematopoietic disorder, and research continues to update its genetic drivers. Golgi-associated PDZ and coiled-coil motif-containing (GOPC) is a signaling protein implicated in regulating cellular trafficking of transmembrane proteins. Recent research has shown that the gene encoding GOPC exhibits dysregulated expression in colorectal cancer. In AML, the significance of <em>GOPC</em> expression in disease risk and pathogenesis has not been explored. Therefore, a case-control study was conducted to evaluate <em>GOPC</em> mRNA expression in a cohort of 100 AML patients and 100 controls. <em>GOPC</em> expression was quantified using a reverse transcription-quantitative PCR-based fold change method (2<sup>–ΔCt</sup>). Statistical data management included receiver-operating characteristic (ROC) curve analysis, disease-risk assessment, and assessment of correlation with AML characteristics. Results revealed that <em>GOPC</em> expression levels (median [interquartile range: 25–75 %]) were significantly decreased in patients compared to controls (0.04 [0.02–0.14] vs. 0.73 [0.18–1.16]; probability <0.001). ROC curve analysis demonstrated the reliability of <em>GOPC</em> expression in distinguishing between AML patients and controls (area under the curve = 0.91; probability <0.001). Disease-risk assessment indicated that low <em>GOPC</em> expression was linked to a 16.15-fold increased risk of AML. <em>GOPC</em> expression was not affected by clinical and genetic characteristics of AML or chemotherapy and was not correlated with diagnostic laboratory criteria<em>.</em> In conclusion, <em>GOPC</em> mRNA expression was down-regulated in AML and was not affected by the patient's clinical, genetic, or laboratory characteristics. Low <em>GOPC</em> expression may be considered a potential risk factor for AML.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201516"},"PeriodicalIF":0.7,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation, progressive joint destruction, and systemic complications. Despite significant advancements in RA research, the molecular mechanisms driving disease progression remain incompletely understood. This study employed an integrated bioinformatics approach to uncover differentially expressed genes (DEGs), key signaling pathways, and potential therapeutic targets in RA. Four publicly available microarray datasets (GSE56649, GSE93272, GSE110169, and GSE45291) from the NCBI Gene Expression Omnibus (GEO) were analyzed using the limma package in R with thresholds of |log2 fold change| > 0.1 and adjusted p-value <0.05. Common DEGs across datasets were identified by Venn diagram analysis and subjected to functional enrichment. Protein–protein interaction (PPI) networks were constructed using STRING and analyzed in Cytoscape with CytoHubba to extract hub genes. Clustering was performed with Gephi, and drug–gene interactions were explored using DGIdb. A total of 394 common DEGs were identified, significantly enriched in proteasome function, chromatin remodeling, oxidative phosphorylation, JAK-STAT signaling, and Th17 cell differentiation—pathways central to RA pathogenesis. Network analysis revealed ten hub genes (PSMA4, HSP90AA1, PSMD2, TRIM28, RBBP4, SIRT1, RPL35, HNRNPK, MAPK8, and PSMD10) as potential regulators in RA, implicated in inflammation, immune signaling, oxidative stress, and cartilage degradation. Among them, HSP90AA1, SIRT1, and MAPK8 showed particular relevance to RA through modulation of NF-κB, STAT3, and MAPK pathways. Drug–gene interaction analysis identified 21 small molecules targeting these hub genes, highlighting opportunities for drug repurposing. Collectively, these findings provide new insights into RA pathogenesis and highlight candidate biomarkers and therapeutic targets that may support earlier diagnosis and the development of novel targeted therapies.
{"title":"Multi-dataset transcriptomic study reveals key regulatory pathways and drug targets in rheumatoid arthritis","authors":"Ali Babaei-Ghaghelestany , Somayeh Pashaei , Reza Khodarahmi , Maryam Mehrabi , Masomeh Mehrabi","doi":"10.1016/j.humgen.2025.201515","DOIUrl":"10.1016/j.humgen.2025.201515","url":null,"abstract":"<div><div>Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation, progressive joint destruction, and systemic complications. Despite significant advancements in RA research, the molecular mechanisms driving disease progression remain incompletely understood. This study employed an integrated bioinformatics approach to uncover differentially expressed genes (DEGs), key signaling pathways, and potential therapeutic targets in RA. Four publicly available microarray datasets (GSE56649, GSE93272, GSE110169, and GSE45291) from the NCBI Gene Expression Omnibus (GEO) were analyzed using the <em>limma</em> package in R with thresholds of |log2 fold change| > 0.1 and adjusted <em>p</em>-value <0.05. Common DEGs across datasets were identified by Venn diagram analysis and subjected to functional enrichment. Protein–protein interaction (PPI) networks were constructed using STRING and analyzed in Cytoscape with CytoHubba to extract hub genes. Clustering was performed with Gephi, and drug–gene interactions were explored using DGIdb. A total of 394 common DEGs were identified, significantly enriched in proteasome function, chromatin remodeling, oxidative phosphorylation, JAK-STAT signaling, and Th17 cell differentiation—pathways central to RA pathogenesis. Network analysis revealed ten hub genes (<em>PSMA4</em>, <em>HSP90AA1</em>, <em>PSMD2</em>, <em>TRIM28</em>, <em>RBBP4</em>, <em>SIRT1</em>, <em>RPL35</em>, <em>HNRNPK</em>, <em>MAPK8</em>, and <em>PSMD10</em>) as potential regulators in RA, implicated in inflammation, immune signaling, oxidative stress, and cartilage degradation. Among them, <em>HSP90AA1</em>, <em>SIRT1</em>, and <em>MAPK8</em> showed particular relevance to RA through modulation of NF-κB, STAT3, and MAPK pathways. Drug–gene interaction analysis identified 21 small molecules targeting these hub genes, highlighting opportunities for drug repurposing. Collectively, these findings provide new insights into RA pathogenesis and highlight candidate biomarkers and therapeutic targets that may support earlier diagnosis and the development of novel targeted therapies.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201515"},"PeriodicalIF":0.7,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-22DOI: 10.1016/j.humgen.2025.201514
Joseph Livni , Karl Skorecki
This document is a response to Joseph Fiaith, Commentary on Livni & Skorecki, “Distinguishing between Founder and Host Population mtDNA Lineages in the Ashkenazi Population”. Human Gene 46. doi: 10.1016.
{"title":"Response to commentary on Livni & Skorecki, “Distinguishing between founder and host population mtDNA lineages in the Ashkenazi population”","authors":"Joseph Livni , Karl Skorecki","doi":"10.1016/j.humgen.2025.201514","DOIUrl":"10.1016/j.humgen.2025.201514","url":null,"abstract":"<div><div>This document is a response to Joseph Fiaith, Commentary on Livni & Skorecki, “Distinguishing between Founder and Host Population mtDNA Lineages in the Ashkenazi Population”. Human Gene 46. doi: 10.1016.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201514"},"PeriodicalIF":0.7,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-19DOI: 10.1016/j.humgen.2025.201501
Mohammad Reza Forouzesh Kia , Hajar Yaghoobi , Nooshafarin Shirani , Reza Eshraghi Samani
Epigenetic factors, such as regulatory RNAs, are among the most important drivers of breast cancer. Many of these non-coding RNAs are long non-coding RNAs (lncRNAs). Research has shown that numerous lncRNAs play a significant role in the development of breast cancer and can be categorized as either oncogenic or tumor suppressor. This study aims to identify the candidate lncRNAs relevant to breast cancer through bioinformatics studies and then investigate changes in their expression levels, specifically focusing on LINC01614 lncRNAs, in cancerous tissues in comparison to adjacent noncancerous tissues.
Method
In this study, gene expression data for 12,727 long non-coding RNAs (lncRNAs) were analyzed, consisting of 837 breast cancer samples and 105 normal samples, using the TANRIC database. To explore the potential biological functions of selective lncRNA, we identified its top 50 co-expressed genes using the lncHUB platform. This list of genes was subsequently subjected to comprehensive enrichment analysis, using the Enrichment Analysis Visualizer Appyter. Post-surgery patient samples were collected, and RNA was isolated and converted to cDNA for real-time quantitative PCR (RT-qPCR) to evaluate gene expression levels. Graph Pad Prism was employed for statistical evaluation of the data.
Result and discussion
Differential expression analysis revealed 64 lncRNAs, with LINC01614 showing the highest up-regulation (logFC of 2.34). Functional enrichment analysis of co-expressed genes revealed strong associations with key oncogenic pathways, including extracellular matrix organization, PI3K-AKT-mTOR signaling, and immune response processes. The analysis of long non-coding RNA LINC01614 indicated a significant 6.5-fold increase in cancer samples compared to normal tissues, suggesting its role in breast cancer development. Expression levels varied by tumor grade, with higher levels observed in grades 1 and 2 compared to grade 3, indicating its potential significance in tumor development. The study also explored the relationship between LINC01614 expression and PR-receptor status.
Conclusion
This study reveals the multifunctional role of LINC01614 in breast cancer pathogenesis. Its significant overexpression and involvement in diverse oncogenic processes highlight its potential as both a novel diagnostic biomarker and a promising therapeutic target. Further investigations are warranted to elucidate its precise mechanisms and clinical applicability.
表观遗传因素，如调控rna，是乳腺癌最重要的驱动因素之一。这些非编码rna中有许多是长链非编码rna （lncrna）。研究表明，许多lncrna在乳腺癌的发展中起着重要作用，可分为致癌和抑癌两类。本研究旨在通过生物信息学研究，确定与乳腺癌相关的候选lncrna，并研究其在癌组织中与邻近非癌组织相比表达水平的变化，重点关注LINC01614 lncrna。方法利用TANRIC数据库，分析837例乳腺癌样本和105例正常样本中12727种长链非编码rna （lncRNAs）的基因表达数据。为了探索选择性lncRNA的潜在生物学功能，我们使用lncHUB平台鉴定了其前50个共表达基因。随后使用富集分析可视化工具对该基因列表进行全面富集分析。收集术后患者标本，分离RNA转化为cDNA，进行实时定量PCR （RT-qPCR）检测基因表达水平。采用Graph Pad Prism对数据进行统计评价。差异表达分析共发现64个lncrna，其中LINC01614上调幅度最大（logFC为2.34）。共表达基因的功能富集分析显示，它们与细胞外基质组织、PI3K-AKT-mTOR信号传导和免疫反应过程等关键致癌途径密切相关。长链非编码RNA LINC01614的分析表明，与正常组织相比，癌症样本中的长链非编码RNA增加了6.5倍，表明其在乳腺癌发展中的作用。表达水平因肿瘤分级而异，1级和2级的表达水平高于3级，表明其在肿瘤发展中的潜在意义。本研究还探讨了LINC01614表达与pr受体状态的关系。结论揭示了LINC01614在乳腺癌发病中的多功能作用。其显著的过表达和参与多种致癌过程，突出了其作为一种新的诊断生物标志物和有希望的治疗靶点的潜力。需要进一步的研究来阐明其确切的机制和临床适用性。
{"title":"Upregulation of long non-coding RNA LINC01614 in breast cancer and its association with clinicopathological features","authors":"Mohammad Reza Forouzesh Kia , Hajar Yaghoobi , Nooshafarin Shirani , Reza Eshraghi Samani","doi":"10.1016/j.humgen.2025.201501","DOIUrl":"10.1016/j.humgen.2025.201501","url":null,"abstract":"<div><div>Epigenetic factors, such as regulatory RNAs, are among the most important drivers of breast cancer. Many of these non-coding RNAs are long non-coding RNAs (lncRNAs). Research has shown that numerous lncRNAs play a significant role in the development of breast cancer and can be categorized as either oncogenic or tumor suppressor. This study aims to identify the candidate lncRNAs relevant to breast cancer through bioinformatics studies and then investigate changes in their expression levels, specifically focusing on LINC01614 lncRNAs, in cancerous tissues in comparison to adjacent noncancerous tissues.</div></div><div><h3>Method</h3><div>In this study, gene expression data for 12,727 long non-coding RNAs (lncRNAs) were analyzed, consisting of 837 breast cancer samples and 105 normal samples, using the TANRIC database. To explore the potential biological functions of selective lncRNA, we identified its top 50 co-expressed genes using the lncHUB platform. This list of genes was subsequently subjected to comprehensive enrichment analysis, using the Enrichment Analysis Visualizer Appyter. Post-surgery patient samples were collected, and RNA was isolated and converted to cDNA for real-time quantitative PCR (RT-qPCR) to evaluate gene expression levels. Graph Pad Prism was employed for statistical evaluation of the data.</div></div><div><h3>Result and discussion</h3><div>Differential expression analysis revealed 64 lncRNAs, with LINC01614 showing the highest up-regulation (logFC of 2.34). Functional enrichment analysis of co-expressed genes revealed strong associations with key oncogenic pathways, including extracellular matrix organization, PI3K-AKT-mTOR signaling, and immune response processes. The analysis of long non-coding RNA LINC01614 indicated a significant 6.5-fold increase in cancer samples compared to normal tissues, suggesting its role in breast cancer development. Expression levels varied by tumor grade, with higher levels observed in grades 1 and 2 compared to grade 3, indicating its potential significance in tumor development. The study also explored the relationship between LINC01614 expression and PR-receptor status.</div></div><div><h3>Conclusion</h3><div>This study reveals the multifunctional role of LINC01614 in breast cancer pathogenesis. Its significant overexpression and involvement in diverse oncogenic processes highlight its potential as both a novel diagnostic biomarker and a promising therapeutic target. Further investigations are warranted to elucidate its precise mechanisms and clinical applicability.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"47 ","pages":"Article 201501"},"PeriodicalIF":0.7,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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