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Luo S, Li Z, Wang M, Liu Z, Wang D, Bai Y, Ge H, Yu Y, Yu Y, Chen W, Wang Y, Zhang C, Yu J, Song C, Lv C, Zhen Q, Han Y, Sun L. Genome wide association study and meta-analysis identified multiple new risk loci for freckles in 4813 Chinese individuals. Pigment Cell Melanoma Res 2024. [PMID: 38970458 DOI: 10.1111/pcmr.13183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 06/11/2024] [Accepted: 06/18/2024] [Indexed: 07/08/2024]
Abstract
Freckle is a prevalent pigmentary dermatosis with an obvious hereditary component. Dozens of freckles risk loci have been discovered through research on multiple traits or other diseases, rather than as an independent trait. To discover novel variants associated with freckles, we performed GWAS and meta-analysis in 4813 Chinese individuals. We conducted GWAS and meta-analysis of two cohorts: 197 patients and 1603 controls (Cohort I), and 336 patients and 2677 controls (Cohort II), both from China. Then we performed linkage disequilibrium (LD) analysis, eQTL study, and enrichment analysis with association results for functional implications. Finally, we discovered 59 new SNPs and 13 novel susceptibility genes associated with freckles (Pmeta <5 × 10-8), which has enriched the genetic research on freckles.
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Affiliation(s)
- Sihan Luo
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Zhuo Li
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Minhao Wang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Zhili Liu
- Dalian Dermatosis Hospital, Dalian, China
| | - Daiyue Wang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Yuanming Bai
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Huiyao Ge
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Yafen Yu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Yanxia Yu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Weiwei Chen
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Yirui Wang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Chang Zhang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Jing Yu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | - Can Song
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
| | | | - Qi Zhen
- North China University of Science and Technology Affiliated Hospital Tangshan, Tangshan, China
| | - Yang Han
- North China University of Science and Technology Affiliated Hospital Tangshan, Tangshan, China
| | - Liangdan Sun
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
- North China University of Science and Technology Affiliated Hospital Tangshan, Tangshan, China
- School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
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Zhong M, Xu W, Tian P, Zhang Q, Wang Z, Liang L, Zhang Q, Yang Y, Lu Y, Wei GH. An Inherited Allele Confers Prostate Cancer Progression and Drug Resistance via RFX6/HOXA10-Orchestrated TGFβ Signaling. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2401492. [PMID: 38932472 DOI: 10.1002/advs.202401492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 05/01/2024] [Indexed: 06/28/2024]
Abstract
Genetic and epigenetic alterations are cancer hallmark characteristics. However, the role of inherited cancer predisposition alleles in co-opting lineage factor epigenetic reprogramming and tumor progression remains elusive. Here the FinnGen cohort phenome-wide analysis, along with multiple genome-wide association studies, has consistently identified the rs339331-RFX6/6q22 locus associated with prostate cancer (PCa) risk across diverse populations. It is uncovered that rs339331 resides in a reprogrammed androgen receptor (AR) binding site in PCa tumors, with the T risk allele enhancing AR chromatin occupancy. RFX6, an AR-regulated gene linked to rs339331, exhibits synergistic prognostic value for PCa recurrence and metastasis. This comprehensive in vitro and in vivo studies demonstrate the oncogenic functions of RFX6 in promoting PCa cell proliferation and metastasis. Mechanistically, RFX6 upregulates HOXA10 that profoundly correlates with adverse PCa outcomes and is pivotal in RFX6-mediated PCa progression, facilitating the epithelial-mesenchymal transition (EMT) and modulating the TGFβ/SMAD signaling axis. Clinically, HOXA10 elevation is associated with increased EMT scores, tumor advancement and PCa recurrence. Remarkably, reducing RFX6 expression restores enzalutamide sensitivity in resistant PCa cells and tumors. This findings reveal a complex interplay of genetic and epigenetic mechanisms in PCa pathogenesis and drug resistance, centered around disrupted prostate lineage AR signaling and abnormal RFX6 expression.
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Affiliation(s)
- Mengjie Zhong
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Wenjie Xu
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Pan Tian
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Qin Zhang
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, 90220, Finland
| | - Zixian Wang
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Limiao Liang
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Qixiang Zhang
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Yuehong Yang
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, 90220, Finland
| | - Ying Lu
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Gong-Hong Wei
- MOE Key Laboratory of Metabolism and Molecular Medicine & Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, and Fudan University Shanghai Cancer Center, Cancer Institutes, Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, 90220, Finland
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Zucker R, Kovalerchik M, Stern A, Kaufman H, Linial M. Revealing the genetic complexity of hypothyroidism: integrating complementary association methods. Front Genet 2024; 15:1409226. [PMID: 38919955 PMCID: PMC11196612 DOI: 10.3389/fgene.2024.1409226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 05/16/2024] [Indexed: 06/27/2024] Open
Abstract
Hypothyroidism is a common endocrine disorder whose prevalence increases with age. The disease manifests itself when the thyroid gland fails to produce sufficient thyroid hormones. The disorder includes cases of congenital hypothyroidism (CH), but most cases exhibit hormonal feedback dysregulation and destruction of the thyroid gland by autoantibodies. In this study, we sought to identify causal genes for hypothyroidism in large populations. The study used the UK-Biobank (UKB) database, reporting on 13,687 cases of European ancestry. We used GWAS compilation from Open Targets (OT) and tuned protocols focusing on genes and coding regions, along with complementary association methods of PWAS (proteome-based) and TWAS (transcriptome-based). Comparing summary statistics from numerous GWAS revealed a limited number of variants associated with thyroid development. The proteome-wide association study method identified 77 statistically significant genes, half of which are located within the Chr6-MHC locus and are enriched with autoimmunity-related genes. While coding GWAS and PWAS highlighted the centrality of immune-related genes, OT and transcriptome-wide association study mostly identified genes involved in thyroid developmental programs. We used independent populations from Finland (FinnGen) and the Taiwan cohort to validate the PWAS results. The higher prevalence in females relative to males is substantiated as the polygenic risk score prediction of hypothyroidism relied mostly from the female group genetics. Comparing results from OT, TWAS, and PWAS revealed the complementary facets of hypothyroidism's etiology. This study underscores the significance of synthesizing gene-phenotype association methods for this common, intricate disease. We propose that the integration of established association methods enhances interpretability and clinical utility.
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Affiliation(s)
- Roei Zucker
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michael Kovalerchik
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amos Stern
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hadasa Kaufman
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michal Linial
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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Gholami M. Common and novel haplotype structures between different types of cancer. Cancer Rep (Hoboken) 2024; 7:e2107. [PMID: 39031745 PMCID: PMC11190585 DOI: 10.1002/cnr2.2107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/03/2024] [Accepted: 05/07/2024] [Indexed: 07/22/2024] Open
Abstract
BACKGROUND Background: Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with cancer risk. GWAS data are important for cancer prevention and understanding the underlying mechanisms of cancer. AIMS This study aimed to investigate the genetic association between different types of cancer using GWAS data and a bioinformatics approach. METHODS AND RESULTS The significant GWAS variants associated with more than one cancer type were identified. Common linkage disequilibrium (LD) variants between different types of cancer were identified by 1000 genomes phase 3 LD data. Haplotype blocks were identified by analyzing 1000 Genomes phase 3 genotyping data in the GWAS populations. Subsequent analyses included functional SNP analyses and TCGA gene expression. The results associated with significant GWAS variants (P<5E-8) showed the following haplotype associations in European population: GT rs4808075-rs8170 haplotype on BABAM1 with breast and ovarian cancers, GC rs16857609-rs11693806 haplotype on DIRC3 with breast and thyroid cancers, GCG rs380286-rs401681-rs31487 haplotype on CLPTM1L with skin and lung cancers, GGG rs4430796-rs11651052-rs11263763 haplotype on HNF1B with prostate and endometrial cancers, and GT rs10505477-rs6983267 haplotype on CASC8 associated with colorectal and prostate cancers. All these genes had significantly different expressions in tumor tissues (P<1E-3). In addition, the rs11693806 variant is located in the hsa-miR-873-5p binding site and has an enhancing effect on the hsa-miR-873-5p:DIRC3 interaction. CONCLUSION These novel haplotype structures and miRNA:lncRNA interactions are important for understanding the common genetic link between cancers. These results can potentially be used in genetic panels.
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Affiliation(s)
- Morteza Gholami
- Department of Paramedicine, Amol School of Paramedical SciencesMazandaran University of Medical SciencesSariIran
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular‐Cellular Sciences InstituteTehran University of Medical SciencesTehranIran
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Gholami M. Novel genetic association between obesity, colorectal cancer, and inflammatory bowel disease. J Diabetes Metab Disord 2024; 23:739-744. [PMID: 38932827 PMCID: PMC11196566 DOI: 10.1007/s40200-023-01343-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 11/06/2023] [Indexed: 06/28/2024]
Abstract
Purpose Obesity/overweight is an important risk factor for CRC and IBD. The aim of this study was to investigate the role of common genetic factors and haplotypes associated with obesity, CRC and IBD. Methods Significant GWAS variants associated with CRC, IBD or obesity were extracted from the GWAS catalog. The common variants between CRC-IBD, CRC-obesity or IBD-obesity were identified. Finally, the haplotypic structure between these diseases was identified, and SNP function analysis, gene-gene expression, protein-protein interactions, gene survival analysis and pathway analysis were performed with the results. Results While the results showed several common variants between CRC and IBD, IBD and obesity, and CRC and obesity identified in previous GWAS, rs3184504 was the only common variant for CRC-IBD-obesity (P ≤ 5E-8). The result also identified a haplotypic block AGCAGT (r2 ≥ 0.8 and D'≥0.08) associated with the common variants of CRC-IBD-obesity. These variants are located on the SH2B3 gene, whose expression level decreases in both colon and rectal cancers (P ≤ 1E-3) and which has protein-protein interaction with inflammation- and cancer-associated genes. Conclusion The rs3184504 variant and the novel haplotype AGCAGT co-occurred in CRC, IBD, obesity, and inflammation. This novel haplotype could potentially be used in genetic panels to identify CRC/IBD susceptibility in obese patients.
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Affiliation(s)
- Morteza Gholami
- North Research Center, Pasteur Institute of Iran, Amol, Iran
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
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Zhang XX, Yu XY, Xu SJ, Shi XQ, Chen Y, Shi Q, Sun C. rs2736098, a synonymous polymorphism, is associated with carcinogenesis and cell count in multiple tissue types by regulating TERT expression. Heliyon 2024; 10:e27802. [PMID: 38496869 PMCID: PMC10944260 DOI: 10.1016/j.heliyon.2024.e27802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/19/2024] Open
Abstract
rs2736098 is a synonymous polymorphism in TERT (telomerase reverse transcriptase), an enzyme involved in tumor onset of multiple tissues, and should play no roles in carcinogenesis. However, a search in cancer somatic mutation database indicated that the mutation frequency at rs2736098 is much higher than the average one for TERT. Moreover, there are significant H3K4me1 and H3K27Ac signals, two universal histone modifications for active enhancers, surrounding rs2736098. Therefore, we hypothesized that rs2736098 might be within an enhancer region, regulate TERT expression and influence cancer risk. Through luciferase assay, it was verified that the enhancer activity of rs2736098C allele is significantly higher than that of T in multiple tissues. Transfection of plasmids containing TERT coding region with two different alleles indicated that rs2736098C allele can induce a significantly higher TERT expression than T. By chromatin immunoprecipitation, it was observed that the fragment spanning rs2736098 can interact with USF1 (upstream transcription factor 1). The two alleles of rs2736098 present evidently different binding affinity with nuclear proteins. Database and literature search indicated that rs2736098 is significantly associated with carcinogenesis in multiple tissues and count of multiple cell types. All these facts indicated that rs2736098 is also an oncogenic polymorphism and plays important role in cell proliferation.
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Affiliation(s)
- Xin-Xin Zhang
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Xin-Yi Yu
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Shuang-Jia Xu
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Xiao-Qian Shi
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Ying Chen
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Qiang Shi
- College of Biology Pharmacy and Food Engineering, Shangluo University, Shangluo, Shaanxi, 726000, PR China
| | - Chang Sun
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
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Camerota M, Lester BM, Castellanos FX, Carter BS, Check J, Helderman J, Hofheimer JA, McGowan EC, Neal CR, Pastyrnak SL, Smith LM, O'Shea TM, Marsit CJ, Everson TM. Epigenome-wide association study identifies neonatal DNA methylation associated with two-year attention problems in children born very preterm. Transl Psychiatry 2024; 14:126. [PMID: 38418845 PMCID: PMC10902402 DOI: 10.1038/s41398-024-02841-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 02/07/2024] [Accepted: 02/16/2024] [Indexed: 03/02/2024] Open
Abstract
Prior research has identified epigenetic predictors of attention problems in school-aged children but has not yet investigated these in young children, or children at elevated risk of attention problems due to preterm birth. The current study evaluated epigenome-wide associations between neonatal DNA methylation and attention problems at age 2 years in children born very preterm. Participants included 441 children from the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study, a multi-site study of infants born < 30 weeks gestational age. DNA methylation was measured from buccal swabs collected at NICU discharge using the Illumina MethylationEPIC Bead Array. Attention problems were assessed at 2 years of adjusted age using the attention problems subscale of the Child Behavior Checklist (CBCL). After adjustment for multiple testing, DNA methylation at 33 CpG sites was associated with child attention problems. Differentially methylated CpG sites were located in genes previously linked to physical and mental health, including several genes associated with ADHD in prior epigenome-wide and genome-wide association studies. Several CpG sites were located in genes previously linked to exposure to prenatal risk factors in the NOVI sample. Neonatal epigenetics measured at NICU discharge could be useful in identifying preterm children at risk for long-term attention problems and related psychiatric disorders, who could benefit from early prevention and intervention efforts.
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Affiliation(s)
- Marie Camerota
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA.
- Brown Center for the Study of Children at Risk, Alpert Medical School of Brown University and Women and Infants Hospital, Providence, RI, USA.
| | - Barry M Lester
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
- Brown Center for the Study of Children at Risk, Alpert Medical School of Brown University and Women and Infants Hospital, Providence, RI, USA
- Department of Pediatrics, Alpert Medical School of Brown University and Women and Infants Hospital, Providence, RI, USA
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Brian S Carter
- Department of Pediatrics-Neonatology, Children's Mercy Hospital, Kansas City, MO, USA
| | - Jennifer Check
- Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer Helderman
- Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Julie A Hofheimer
- Department of Pediatrics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Elisabeth C McGowan
- Department of Pediatrics, Alpert Medical School of Brown University and Women and Infants Hospital, Providence, RI, USA
| | - Charles R Neal
- Department of Pediatrics, University of Hawaii John A. Burns School of Medicine, Honolulu, HI, USA
| | - Steven L Pastyrnak
- Department of Pediatrics, Spectrum Health-Helen DeVos Hospital, Grand Rapids, MI, USA
| | - Lynne M Smith
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Thomas Michael O'Shea
- Department of Pediatrics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Todd M Everson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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Izquierdo-Villalba I, Mirra S, Manso Y, Parcerisas A, Rubio J, Del Valle J, Gil-Bea FJ, Ulloa F, Herrero-Lorenzo M, Verdaguer E, Benincá C, Castro-Torres RD, Rebollo E, Marfany G, Auladell C, Navarro X, Enríquez JA, López de Munain A, Soriano E, Aragay AM. A mammalian-specific Alex3/Gα q protein complex regulates mitochondrial trafficking, dendritic complexity, and neuronal survival. Sci Signal 2024; 17:eabq1007. [PMID: 38320000 DOI: 10.1126/scisignal.abq1007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 01/16/2024] [Indexed: 02/08/2024]
Abstract
Mitochondrial dynamics and trafficking are essential to provide the energy required for neurotransmission and neural activity. We investigated how G protein-coupled receptors (GPCRs) and G proteins control mitochondrial dynamics and trafficking. The activation of Gαq inhibited mitochondrial trafficking in neurons through a mechanism that was independent of the canonical downstream PLCβ pathway. Mitoproteome analysis revealed that Gαq interacted with the Eutherian-specific mitochondrial protein armadillo repeat-containing X-linked protein 3 (Alex3) and the Miro1/Trak2 complex, which acts as an adaptor for motor proteins involved in mitochondrial trafficking along dendrites and axons. By generating a CNS-specific Alex3 knockout mouse line, we demonstrated that Alex3 was required for the effects of Gαq on mitochondrial trafficking and dendritic growth in neurons. Alex3-deficient mice had altered amounts of ER stress response proteins, increased neuronal death, motor neuron loss, and severe motor deficits. These data revealed a mammalian-specific Alex3/Gαq mitochondrial complex, which enables control of mitochondrial trafficking and neuronal death by GPCRs.
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Affiliation(s)
| | - Serena Mirra
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Raras (CIBER-CIBERER), ISCIII, Madrid 28031, Spain
- Institut de Biomedicina- Institut de Recerca Sant Joan de Déu (IBUB-IRSJD), Universitat de Barcelona, Barcelona 08028, Spain
| | - Yasmina Manso
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
| | - Antoni Parcerisas
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Biosciences Department, Faculty of Sciences, Technology and Engineering, University of Vic, Central University of Catalonia (UVic-UCC); and Tissue Repair and Regeneration Laboratory (TR2Lab), Institut de Recerca i Innovació en Ciències de la Vida i de la Salut a la Catalunya Central (IRIS-CC), 08500 Vic, Spain
| | - Javier Rubio
- Institut de Biologia Molecular de Barcelona (IBMB-CSIC), Barcelona 08028, Spain
| | - Jaume Del Valle
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, Universitat Autonoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Francisco J Gil-Bea
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián 20014, Spain
| | - Fausto Ulloa
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
| | - Marina Herrero-Lorenzo
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
| | - Ester Verdaguer
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
| | - Cristiane Benincá
- Institut de Biologia Molecular de Barcelona (IBMB-CSIC), Barcelona 08028, Spain
| | - Rubén D Castro-Torres
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
| | - Elena Rebollo
- Institut de Biologia Molecular de Barcelona (IBMB-CSIC), Barcelona 08028, Spain
| | - Gemma Marfany
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Raras (CIBER-CIBERER), ISCIII, Madrid 28031, Spain
- Institut de Biomedicina- Institut de Recerca Sant Joan de Déu (IBUB-IRSJD), Universitat de Barcelona, Barcelona 08028, Spain
| | - Carme Auladell
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
| | - Xavier Navarro
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, Universitat Autonoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - José A Enríquez
- Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid 28029, Spain
- Centro de Investigación Biomédica en Red en Fragilidad y Envejecimiento Saludable (CIBER-CIBERFES), Madrid 28031, Spain
| | - Adolfo López de Munain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián 20014, Spain
- Neurology Department, Donostia University Hospital, San Sebastián 20014, Spain
| | - Eduardo Soriano
- Department of Cell Biology, Physiology and Immunology, and Institute of Neurosciences, University of Barcelona, Barcelona 08028, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBER-CIBERNED), ISCIII, Madrid 28031, Spain
| | - Anna M Aragay
- Institut de Biologia Molecular de Barcelona (IBMB-CSIC), Barcelona 08028, Spain
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9
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Lucotte EA, Asgari Y, Sugier PE, Karimi M, Domenighetti C, Lesueur F, Boland-Augé A, Ostroumova E, de Vathaire F, Zidane M, Guénel P, Deleuze JF, Boutron-Ruault MC, Severi G, Liquet B, Truong T. Investigation of common genetic risk factors between thyroid traits and breast cancer. Hum Mol Genet 2023; 33:38-47. [PMID: 37740403 PMCID: PMC10729861 DOI: 10.1093/hmg/ddad159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/12/2023] [Accepted: 09/19/2023] [Indexed: 09/24/2023] Open
Abstract
Breast cancer (BC) risk is suspected to be linked to thyroid disorders, however observational studies exploring the association between BC and thyroid disorders gave conflicting results. We proposed an alternative approach by investigating the shared genetic risk factors between BC and several thyroid traits. We report a positive genetic correlation between BC and thyroxine (FT4) levels (corr = 0.13, p-value = 2.0 × 10-4) and a negative genetic correlation between BC and thyroid-stimulating hormone (TSH) levels (corr = -0.09, p-value = 0.03). These associations are more striking when restricting the analysis to estrogen receptor-positive BC. Moreover, the polygenic risk scores (PRS) for FT4 and hyperthyroidism are positively associated to BC risk (OR = 1.07, 95%CI: 1.00-1.13, p-value = 2.8 × 10-2 and OR = 1.04, 95%CI: 1.00-1.08, p-value = 3.8 × 10-2, respectively), while the PRS for TSH is inversely associated to BC risk (OR = 0.93, 95%CI: 0.89-0.97, p-value = 2.0 × 10-3). Using the PLACO method, we detected 49 loci associated to both BC and thyroid traits (p-value < 5 × 10-8), in the vicinity of 130 genes. An additional colocalization and gene-set enrichment analyses showed a convincing causal role for a known pleiotropic locus at 2q35 and revealed an additional one at 8q22.1 associated to both BC and thyroid cancer. We also found two new pleiotropic loci at 14q32.33 and 17q21.31 that were associated to both TSH levels and BC risk. Enrichment analyses and evidence of regulatory signals also highlighted brain tissues and immune system as candidates for obtaining associations between BC and TSH levels. Overall, our study sheds light on the complex interplay between BC and thyroid traits and provides evidence of shared genetic risk between those conditions.
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Affiliation(s)
- Elise A Lucotte
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
| | - Yazdan Asgari
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
| | - Pierre-Emmanuel Sugier
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
- Laboratoire de Mathématiques et de leurs Applications de Pau, Université de Pau et des Pays de l’Adour, UMR CNRS 5142, E2S-UPPA, 64013 Pau, France
| | - Mojgan Karimi
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
| | - Cloé Domenighetti
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
| | - Fabienne Lesueur
- Inserm, U900, Institut Curie, PSL University, Mines ParisTech, 75006 Paris, France
| | - Anne Boland-Augé
- National Centre of Human Genomics Research, François Jacob Institute of Biology, Commissariat à l’Energie Atomique, Paris-Saclay University, 91000 Evry, France
| | | | - Florent de Vathaire
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team of Epidemiology of radiations, 94807 Villejuif, France
| | - Monia Zidane
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team of Epidemiology of radiations, 94807 Villejuif, France
| | - Pascal Guénel
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
| | - Jean-François Deleuze
- National Centre of Human Genomics Research, François Jacob Institute of Biology, Commissariat à l’Energie Atomique, Paris-Saclay University, 91000 Evry, France
| | | | - Gianluca Severi
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
- Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence, 50121 Florence, Italy
| | - Benoît Liquet
- Laboratoire de Mathématiques et de leurs Applications de Pau, Université de Pau et des Pays de l’Adour, UMR CNRS 5142, E2S-UPPA, 64013 Pau, France
- School of Mathematical and Physical Sciences, Macquarie University, 2109 Sydney, Australia
| | - Thérèse Truong
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team “Exposome and Heredity”, 94807 Villejuif, France
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10
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Brandes N, Goldman G, Wang CH, Ye CJ, Ntranos V. Genome-wide prediction of disease variant effects with a deep protein language model. Nat Genet 2023; 55:1512-1522. [PMID: 37563329 PMCID: PMC10484790 DOI: 10.1038/s41588-023-01465-0] [Citation(s) in RCA: 62] [Impact Index Per Article: 62.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 07/05/2023] [Indexed: 08/12/2023]
Abstract
Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.
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Affiliation(s)
- Nadav Brandes
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Grant Goldman
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Charlotte H Wang
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Chun Jimmie Ye
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Parker Institute for Cancer Immunotherapy, University of California, San Francisco, San Francisco, CA, USA.
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Vasilis Ntranos
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
- Diabetes Center, University of California, San Francisco, San Francisco, CA, USA.
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11
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Badré A, Pan C. Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis. PLoS Comput Biol 2023; 19:e1011211. [PMID: 37418352 DOI: 10.1371/journal.pcbi.1011211] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/23/2023] [Indexed: 07/09/2023] Open
Abstract
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygenic risk scores (PRS). This hypothesis was tested using a multi-task learning (MTL) approach based on an explainable neural network architecture. We found that parallel estimations of the PRS for 17 prevalent cancers in a pan-cancer MTL model were generally more accurate than independent estimations for individual cancers in comparable single-task learning (STL) models. Such performance improvement conferred by positive transfer learning was also observed consistently for 60 prevalent non-cancer diseases in a pan-disease MTL model. Interpretation of the MTL models revealed significant genetic correlations between the important sets of single nucleotide polymorphisms used by the neural network for PRS estimation. This suggested a well-connected network of diseases with shared genetic basis.
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Affiliation(s)
- Adrien Badré
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Chongle Pan
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, United States of America
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12
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Zucker R, Kovalerchik M, Linial M. Gene-based association study reveals a distinct female genetic signal in primary hypertension. Hum Genet 2023:10.1007/s00439-023-02567-9. [PMID: 37133573 DOI: 10.1007/s00439-023-02567-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/25/2023] [Indexed: 05/04/2023]
Abstract
Hypertension is a polygenic disease that affects over 1.2 billion adults aged 30-79 worldwide. It is a major risk factor for renal, cerebrovascular, and cardiovascular diseases. The heritability of hypertension is estimated to be high; nevertheless, our understanding of its underlying mechanisms remains scarce and incomplete. This study covered the entries from European ancestry from the UK-Biobank (UKB), with 74,090 cases diagnosed with essential (primary) hypertension and 200,734 controls. We compared the findings from large-scale genome-wide association studies (GWAS) to the gene-based method of proteome-wide association studies (PWAS). We focused on 70 statistically significant associated genes, most of which failed to reach significance in variant-based GWAS. A total of 30% of the PWAS-associated genes were validated against independent cohorts, including the Finnish Biobank. Furthermore, gene-based analyses that were performed on both sexes revealed sex-dependent genetics with a stronger genetic component associated with females. Analysis of systolic and diastolic blood pressure measurements confirms a strong genetic effect associated with females. We demonstrated that gene-based approaches provide insight into the underlying biology of hypertension. Specifically, the expression profiles of the identified genes exposed the enrichment of endothelial cells from multiple organs. Furthermore, females' top-ranked significant genes are involved in cellular immunity. We conclude that studying hypertension and blood pressure via gene-based association methods improves interpretability and exposes sex-dependent genetic effects, which enhances clinical utility.
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Affiliation(s)
- Roei Zucker
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel
| | - Michael Kovalerchik
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel
| | - Michal Linial
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel.
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13
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Nunziato M, Scaglione GL, Di Maggio F, Nardelli C, Capoluongo E, Salvatore F. The performance of multi-gene panels for breast/ovarian cancer predisposition. Clin Chim Acta 2023; 539:151-161. [PMID: 36521553 DOI: 10.1016/j.cca.2022.12.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/05/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022]
Abstract
BRCA1 and BRCA2 are the most mutated genes in breast cancer. We analyzed 48 breast cancer subjects using two methods that differ in terms of number of genes investigated and strategy used (primers: Panel A - 12 genes - vs probes: Panel B - 48 genes). Both the panels and procedures identified "pathogenic" or "likely pathogenic" variants in TP53, ATM, CHEK2 and BARD1 besides BRCA1 and BRCA2. Panel B identified two other putatively pathogenic variants in RNASEL and in RAD50. Identification of variants other than the BRCA genes can be useful in patient management. A total of 121 variants were distributed within the 12 genes and were correctly detected by both panels. However, the number of calls without divergence, namely ± 0.10 difference of allelic frequency, was 78.3%, while calls with a divergence below 0.10 was 16.7%, thus indicating that only 5% (n = 275) of 5,412 calls had a divergence above 0.10. Although these panels differ from each other, both are useful in different situations, particularly when patients should be tested for genes other than BRCA1/2 (as occurs in patients affected by a so called hereditary syndrome) or for therapeutic purposes.
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Affiliation(s)
- Marcella Nunziato
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Giovanni Luca Scaglione
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy; Istituto Dermopatico dell'Immacolata IDI-IRCCS, Via dei Monti di Creta, 104, 00167 Rome, Italy
| | - Federica Di Maggio
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Carmela Nardelli
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Ettore Capoluongo
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy; Department of Clinical Pathology and Genomics, Ospedale Cannizzaro, Via Messina, 829, 95126 Catania, Italy.
| | - Francesco Salvatore
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy.
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14
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Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells. Int J Mol Sci 2023; 24:ijms24021181. [PMID: 36674696 PMCID: PMC9864731 DOI: 10.3390/ijms24021181] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/21/2022] [Accepted: 01/03/2023] [Indexed: 01/11/2023] Open
Abstract
Microgravity changes the gene expression pattern in various cell types. This study focuses on the breast cancer cell lines MCF-7 (less invasive) and MDA-MB-231 (triple-negative, highly invasive). The cells were cultured for 14 days under simulated microgravity (s-µg) conditions using a random positioning machine (RPM). We investigated cytoskeletal and extracellular matrix (ECM) factors as well as focal adhesion (FA) and the transmembrane proteins involved in different cellular signaling pathways (MAPK, PAM and VEGF). The mRNA expressions of 24 genes of interest (TUBB, ACTB, COL1A1, COL4A5, LAMA3, ITGB1, CD44, VEGF, FLK1, EGFR, SRC, FAK1, RAF1, AKT1, ERK1, MAPK14, MAP2K1, MTOR, RICTOR, VCL, PXN, CDKN1, CTNNA1 and CTNNB1) were determined by quantitative real-time PCR (qPCR) and studied using STRING interaction analysis. Histochemical staining was carried out to investigate the morphology of the adherent cells (ADs) and the multicellular spheroids (MCSs) after RPM exposure. To better understand this experimental model in the context of breast cancer patients, a weighted gene co-expression network analysis (WGCNA) was conducted to obtain the expression profiles of 35 breast cell lines from the HMS LINCS Database. The qPCR-verified genes were searched in the mammalian phenotype database and the human genome-wide association studies (GWAS) Catalog. The results demonstrated the positive association between the real metastatic microtumor environment and MCSs with respect to the extracellular matrix, cytoskeleton, morphology, different cellular signaling pathway key proteins and several other components. In summary, the microgravity-engineered three-dimensional MCS model can be utilized to study breast cancer cell behavior and to assess the therapeutic efficacies of drugs against breast cancer in the future.
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15
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Hofmeister RJ, Rubinacci S, Ribeiro DM, Buil A, Kutalik Z, Delaneau O. Parent-of-Origin inference for biobanks. Nat Commun 2022; 13:6668. [PMID: 36335127 PMCID: PMC9637181 DOI: 10.1038/s41467-022-34383-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
Abstract
Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.
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Affiliation(s)
- Robin J Hofmeister
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Simone Rubinacci
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Diogo M Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.,University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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16
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Brandes N, Weissbrod O, Linial M. Open problems in human trait genetics. Genome Biol 2022; 23:131. [PMID: 35725481 PMCID: PMC9208223 DOI: 10.1186/s13059-022-02697-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 05/30/2022] [Indexed: 12/21/2022] Open
Abstract
Genetic studies of human traits have revolutionized our understanding of the variation between individuals, and yet, the genetics of most traits is still poorly understood. In this review, we highlight the major open problems that need to be solved, and by discussing these challenges provide a primer to the field. We cover general issues such as population structure, epistasis and gene-environment interactions, data-related issues such as ancestry diversity and rare genetic variants, and specific challenges related to heritability estimates, genetic association studies, and polygenic risk scores. We emphasize the interconnectedness of these problems and suggest promising avenues to address them.
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Affiliation(s)
- Nadav Brandes
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Omer Weissbrod
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Michal Linial
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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