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Canchi Sistla H, Talluri S, Rajagopal T, Venkatabalasubramanian S, Rao Dunna N. Genomic instability in ovarian cancer: Through the lens of single nucleotide polymorphisms. Clin Chim Acta 2024; 565:119992. [PMID: 39395774 DOI: 10.1016/j.cca.2024.119992] [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: 08/06/2024] [Revised: 10/04/2024] [Accepted: 10/04/2024] [Indexed: 10/14/2024]
Abstract
Ovarian cancer (OC) is the deadliest gynecological malignancy among all female reproductive cancers. It is characterized by high mortality rate and poor prognosis. Genomic instability caused by mutations, single nucleotide polymorphisms (SNPs), copy number variations (CNVs), microsatellite instability (MSI), and chromosomal instability (CIN) are associated with OC predisposition. SNPs, which are highly prevalent in the general population, show a greater relative risk contribution, particularly in sporadic cancers. Understanding OC etiology in terms of genetic basis can increase the use of molecular diagnostics and provide promising approaches for designing novel treatment modalities. This will help deliver personalized medicine to OC patients, which may soon be within reach. Given the pivotal impact of SNPs in cancers, the primary emphasis of this review is to shed light on their prevalence in key caretaker genes that closely monitor genomic integrity, viz., DNA damage response, repair, cell cycle checkpoints, telomerase maintenance, and apoptosis and their clinical implications in OC. We highlight the current challenges faced in different SNP-based studies. Various computational methods and bioinformatic tools employed to predict the functional impact of SNPs have also been comprehensively reviewed concerning OC research. Overall, this review identifies that variants in the DDR and HRR pathways are the most studied, implying their critical role in the disease. Conversely, variants in other pathways, such as NHEJ, MMR, cell cycle, apoptosis, telomere maintenance, and PARP genes, have been explored the least.
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Affiliation(s)
- Harshavardhani Canchi Sistla
- Cancer Genomics Laboratory, Department of Biotechnology, School of Chemical and Biotechnology, SASTRA- Deemed University, Thanjavur 613 401, India
| | - Srikanth Talluri
- Dana Farber Cancer Institute, Boston, MA 02215, USA; Veterans Administration Boston Healthcare System, West Roxbury, MA 02132, USA
| | | | - Sivaramakrishna Venkatabalasubramanian
- Department of Genetic Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur Campus, Chennai 603 203, India
| | - Nageswara Rao Dunna
- Cancer Genomics Laboratory, Department of Biotechnology, School of Chemical and Biotechnology, SASTRA- Deemed University, Thanjavur 613 401, India.
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Tseng YP, Chang YS, Mekala VR, Liu TY, Chang JG, Shieh GS. Whole-genome sequencing reveals rare variants associated with gout in Taiwanese males. Front Genet 2024; 15:1423714. [PMID: 39385933 PMCID: PMC11462091 DOI: 10.3389/fgene.2024.1423714] [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: 04/26/2024] [Accepted: 08/28/2024] [Indexed: 10/12/2024] Open
Abstract
To identify rare variants (RVs) of gout, we sequenced the whole genomes of 321 male gout patients and combined these with those of 64 male gout patients and 682 normal controls at Taiwan Biobank. We performed ACAT-O to identify 682 significant RVs (p < 3.8 × 10-8) clustered on chromosomes 1, 7, 10, 16, and 18. To prioritize causal variants effectively, we sifted them by Combined Annotation-Dependent Depletion score >10 or |effect size| ≥ 1.5 for those without CADD scores. In particular, to the best of our knowledge, we identified the rare variants rs559954634, rs186763678, and 13-85340782-G-A for the first time to be associated with gout in Taiwanese males. Importantly, the RV rs559954634 positively affects gout, and its neighboring gene NPHS2 is involved in serum urate and expressed in kidney tissues. The kidneys play a major role in regulating uric acid levels. This suggests that rs559954634 may be involved in gout. Furthermore, rs186763678 is in the intron of NFIA that interacts with SLC2A9, which has the most significant effect on serum urate. Note that gene-gene interaction NFIA-SLC2A9 is significantly associated with serum urate in the Italian MICROS population and a Croatian population. Moreover, 13-85340782-G-A significantly affects gout susceptibility (odds ratio 6.0; P = 0.038). The >1% carrier frequencies of these potentially pathogenic (protective) RVs in cases (controls) suggest the revealed associations may be true; these RVs deserve further studies for the mechanism. Finally, multivariate logistic regression analysis shows that the rare variants rs559954634 and 13-85340782-G-A jointly are significantly associated with gout susceptibility.
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Affiliation(s)
- Yu-Ping Tseng
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Ya-Sian Chang
- Department of Pathology, Chung Shan Medical University Hospital, Taichung, Taiwan
| | | | - Ting-Yuan Liu
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jan-Gowth Chang
- Department of Laboratory Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Grace S. Shieh
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
- Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan
- Data Science Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan
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Wu K, Wang W, Cheng Q, Xiao D, Li Y, Chen M, Zheng X. Rare MED12L Variants Are Associated with Susceptibility to Guttate Psoriasis in the Han Chinese Population. Dermatology 2024; 240:606-614. [PMID: 38735287 DOI: 10.1159/000538805] [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: 10/09/2022] [Accepted: 04/08/2024] [Indexed: 05/14/2024] Open
Abstract
INTRODUCTION According to the common disease/rare variant hypothesis, it is important to study the role of rare variants in complex diseases. The association of rare variants with psoriasis has been demonstrated, but the association between rare variants and specific clinical subtypes of psoriasis has not been investigated. METHODS Gene-based and gene-level meta-analyses were performed on data extracted from our previous study data sets (2,483 patients with guttate psoriasis and 8,292 patients with non-guttate psoriasis) for genotyping. Then, haplotype analysis was performed for rare loss-of-function variants located in MED12L, and protein function prediction was performed for MED12L. Gene-based analysis at each stage had a moderate significance threshold (p < 0.05). A χ2 test was then conducted on the three potential genes, and the merged gene-based analysis was used to confirm the results. We also conducted association analysis and meta-analysis for functional variants located on the identified gene. RESULTS Through these gene-level analyses, we determined that MED12L is a guttate psoriasis susceptibility gene (p = 9.99 × 10-5), and the single-nucleotide polymorphism with the strongest association was rs199780529 (p_combine = 1 × 10-3, p_meta = 2 × 10-3). CONCLUSIONS In our study, a guttate psoriasis-specific subtype-associated susceptibility gene was confirmed in a Chinese Han population. These findings contribute to a better genetic understanding of different subtypes of psoriasis.
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Affiliation(s)
- Kejia Wu
- 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- First Clinical Medical College, Anhui Medical University, Hefei, China
| | - Wanrong 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- First Clinical Medical College, Anhui Medical University, Hefei, China
| | - Qianhui Cheng
- 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- First Clinical Medical College, Anhui Medical University, Hefei, China
| | - Duncheng Xiao
- 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Second Clinical Medical College, Anhui Medical University, Hefei, China
| | - Yunxiao Li
- School of Life Science, Shandong University, Qingdao, China
| | - Mengyun 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
| | - Xiaodong Zheng
- 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
- Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
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Alfayyadh MM, Maksemous N, Sutherland HG, Lea RA, Griffiths LR. Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches. Genes (Basel) 2024; 15:443. [PMID: 38674378 PMCID: PMC11049430 DOI: 10.3390/genes15040443] [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: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.
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Affiliation(s)
| | | | | | | | - Lyn R. Griffiths
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia; (M.M.A.); (N.M.); (H.G.S.); (R.A.L.)
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Zambrano-Román M, Padilla-Gutiérrez JR, Valle Y, Muñoz-Valle JF, Guevara-Gutiérrez E, López-Olmos PA, Sepúlveda-Loza LC, Bautista-Herrera LA, Valdés-Alvarado E. PTCH1 Gene Variants, mRNA Expression, and Bioinformatics Insights in Mexican Cutaneous Squamous Cell Carcinoma Patients. BIOLOGY 2024; 13:191. [PMID: 38534460 DOI: 10.3390/biology13030191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 03/11/2024] [Accepted: 03/15/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND Skin cancer is one of the most frequent types of cancer, and cutaneous squamous cell carcinoma (cSCC) constitutes 20% of non-melanoma skin cancer (NMSC) cases. PTCH1, a tumor suppressor gene involved in the Sonic hedgehog signaling pathway, plays a crucial role in neoplastic processes. METHODS An analytical cross-sectional study, encompassing 211 cSCC patients and 290 individuals in a control group (CG), was performed. A subgroup of samples was considered for the relative expression analysis, and the results were obtained using quantitative real-time PCR (qPCR) with TaqMan® probes. The functional, splicing, and disease-causing effects of the proposed variants were explored via bioinformatics. RESULTS cSCC was predominant in men, especially in sun-exposed areas such as the head and neck. No statistically significant differences were found regarding the rs357564, rs2236405, rs2297086, and rs41313327 variants of PTCH1, or in the risk of cSCC, nor in the mRNA expression between the cSCC group and CG. A functional effect of rs357564 and a disease-causing relation to rs41313327 was identified. CONCLUSION The proposed variants were not associated with cSCC risk in this Mexican population, but we recognize the need for analyzing larger population groups to elucidate the disease-causing role of rare variants.
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Affiliation(s)
- Marianela Zambrano-Román
- Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico
- Doctorado en Genética Humana, Departamento de Biología Molecular y Genómica, Universidad de Guadalajara, Guadalajara 44340, Mexico
| | - Jorge R Padilla-Gutiérrez
- Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico
| | - Yeminia Valle
- Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico
| | - José Francisco Muñoz-Valle
- Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico
| | - Elizabeth Guevara-Gutiérrez
- Departamento de Dermatología, Instituto Dermatológico de Jalisco "Dr. José Barba Rubio", Secretaría de Salud Jalisco, Zapopan 45190, Mexico
| | - Patricia Aidé López-Olmos
- Departamento de Dermatología, Instituto Dermatológico de Jalisco "Dr. José Barba Rubio", Secretaría de Salud Jalisco, Zapopan 45190, Mexico
| | | | | | - Emmanuel Valdés-Alvarado
- Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico
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Wei SM, Gregory MD, Nash T, de Abreu e Gouvêa A, Mervis CB, Cole KM, Garvey MH, Kippenhan JS, Eisenberg DP, Kolachana B, Schmidt PJ, Berman KF. Altered pubertal timing in 7q11.23 copy number variations and associated genetic mechanisms. iScience 2024; 27:109113. [PMID: 38375233 PMCID: PMC10875153 DOI: 10.1016/j.isci.2024.109113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/20/2023] [Accepted: 01/31/2024] [Indexed: 02/21/2024] Open
Abstract
Pubertal timing, including age at menarche (AAM), is a heritable trait linked to lifetime health outcomes. Here, we investigate genetic mechanisms underlying AAM by combining genome-wide association study (GWAS) data with investigations of two rare genetic conditions clinically associated with altered AAM: Williams syndrome (WS), a 7q11.23 hemideletion characterized by early puberty; and duplication of the same genes (7q11.23 Duplication syndrome [Dup7]) characterized by delayed puberty. First, we confirm that AAM-derived polygenic scores in typically developing children (TD) explain a modest amount of variance in AAM (R2 = 0.09; p = 0.04). Next, we demonstrate that 7q11.23 copy number impacts AAM (WS < TD < Dup7; p = 1.2x10-8, η2 = 0.45) and pituitary volume (WS < TD < Dup7; p = 3x10-5, ηp2 = 0.2) with greater effect sizes. Finally, we relate an AAM-GWAS signal in 7q11.23 to altered expression in postmortem brains of STAG3L2 (p = 1.7x10-17), a gene we also find differentially expressed with 7q11.23 copy number (p = 0.03). Collectively, these data explicate the role of 7q11.23 in pubertal onset, with STAG3L2 and pituitary development as potential mediators.
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Affiliation(s)
- Shau-Ming Wei
- Behavioral Endocrinology Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Michael D. Gregory
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Tiffany Nash
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Andrea de Abreu e Gouvêa
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Carolyn B. Mervis
- Neurodevelopmental Sciences Laboratory, Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, USA
| | - Katherine M. Cole
- Behavioral Endocrinology Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Madeline H. Garvey
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - J. Shane Kippenhan
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Daniel P. Eisenberg
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Bhaskar Kolachana
- Human Brain Collection Core, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Peter J. Schmidt
- Behavioral Endocrinology Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Karen F. Berman
- Section on Integrative Neuroimaging, Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
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Pugsley K, Namipashaki A, Bellgrove MA, Hawi Z. Evaluating the regulatory function of non-coding autism-associated single nucleotide polymorphisms on gene expression in human brain tissue. Autism Res 2024; 17:467-481. [PMID: 38323502 DOI: 10.1002/aur.3101] [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: 09/11/2023] [Accepted: 01/18/2024] [Indexed: 02/08/2024]
Abstract
Common variants account for most of the estimated heritability associated with autism spectrum disorder (autism). Although several replicable single nucleotide polymorphisms (SNPs) for the condition have been detected using genome-wide association study (GWAS) methodologies, their pathophysiological relevance remains elusive. Examining this is complicated, however, as all detected loci are situated within non-coding regions of the genome. It is therefore likely that they possess roles of regulatory function as opposed to directly affecting gene coding sequences. To bridge the gap between SNP discovery and mechanistic insight, we applied a comprehensive bioinformatic pipeline to functionally annotate autism-associated polymorphisms and their non-coding linkage disequilibrium (i.e., non-randomly associated) partners. We identified 82 DNA variants of probable regulatory function that may contribute to autism pathogenesis. To validate these predictions, we measured the impact of 11 high-confidence candidates and their GWAS linkage disequilibrium partners on gene expression in human brain tissue from Autistic and non-Autistic donors. Although a small number of the surveyed variants exhibited measurable influence on gene expression as determined via quantitative polymerase chain reaction, these did not survive correction for multiple comparisons. Additionally, no significant genotype-by-diagnosis effects were observed for any of the SNP-gene associations. We contend that this may reflect an inability to effectively capture the modest, neurodevelopmental-specific impact of individual variants on biological dysregulation in available post-mortem tissue samples, as well as limitations in the existing autism GWAS data.
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Affiliation(s)
- Kealan Pugsley
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Atefeh Namipashaki
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ziarih Hawi
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
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Bale G, Kulkarni AV, Padaki NR, Menon PB, Sharma M, Iyengar S, Sekaran A, Pawar SC, Duvvur NR, Vishnubhotla R. Comparing rare variants versus common in the pathogenesis of nonalcoholic fatty liver disease: a whole exome sequencing approach. J Gastroenterol Hepatol 2024; 39:587-595. [PMID: 37939728 DOI: 10.1111/jgh.16394] [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: 08/28/2023] [Revised: 10/10/2023] [Accepted: 10/16/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND/PURPOSE Genome-wide association studies have reported the association of common variants with nonalcoholic fatty liver disease in genes, namely, PNPLA3/TM6SF2/MBOAT7/HSD17B13, across ethnicities. However, the approach does not identify rarer variants with a higher effect size. We therefore sequenced the complete exonic regions of patients with nonalcoholic steatohepatitis and controls to compare rare and common variants with a role in the pathogenesis. METHODS This is a prospective study that recruited 54 individuals with/without fatty infiltration. Patients with biopsy-proven nonalcoholic steatohepatitis and persistently elevated liver enzymes were included. Controls were with normal CT/MR fat fraction. DNA was isolated from whole blood, amplified (SureSelectXT Human All Exon V5 + UTR kit) and sequenced (Illumina). Data were filtered for quality, aligned (hg19), and annotated (OpenCRAVAT). Pathogenic (Polyphen-2/SIFT/ClinVar) variants and variants reported to be associated with NAFLD based on published literature were extracted from our data and compared between patients and controls. RESULTS The mean age of controls (N = 17) and patients (N = 37) was 46.88 ± 6.94 and 37.46 ± 13.34 years, respectively. A total of 251 missense variants out of 89 286 were classified as pathogenic. Of these, 106 (42.23%) were unique to the patients and remaining (n = 145; 57.77%) were found in both patients and controls. Majority (25/37; 67.57%) patients had a minimum of one or more rare pathogenic variant(s) related to liver pathology that was not seen in the controls. CONCLUSION Elucidating the contribution of rare pathogenic variants would enhance our understanding of the pathogenesis. Including the rarer genes in the polygenic risk scores would enhance prediction power.
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Affiliation(s)
- Govardhan Bale
- Asian Healthcare Foundation, Hyderabad, Telangana, India
| | | | | | | | | | | | | | - Smita C Pawar
- Department of Genetics, Osmania University, Hyderabad, Telangana, India
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Goyal S, Rani J, Bhat MA, Vanita V. Genetics of diabetes. World J Diabetes 2023; 14:656-679. [PMID: 37383588 PMCID: PMC10294065 DOI: 10.4239/wjd.v14.i6.656] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/13/2023] [Accepted: 04/17/2023] [Indexed: 06/14/2023] Open
Abstract
Diabetes mellitus is a complicated disease characterized by a complex interplay of genetic, epigenetic, and environmental variables. It is one of the world's fastest-growing diseases, with 783 million adults expected to be affected by 2045. Devastating macrovascular consequences (cerebrovascular disease, cardiovascular disease, and peripheral vascular disease) and microvascular complications (like retinopathy, nephropathy, and neuropathy) increase mortality, blindness, kidney failure, and overall quality of life in individuals with diabetes. Clinical risk factors and glycemic management alone cannot predict the development of vascular problems; multiple genetic investigations have revealed a clear hereditary component to both diabetes and its related complications. In the twenty-first century, technological advancements (genome-wide association studies, next-generation sequencing, and exome-sequencing) have led to the identification of genetic variants associated with diabetes, however, these variants can only explain a small proportion of the total heritability of the condition. In this review, we address some of the likely explanations for this "missing heritability", for diabetes such as the significance of uncommon variants, gene-environment interactions, and epigenetics. Current discoveries clinical value, management of diabetes, and future research directions are also discussed.
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Affiliation(s)
- Shiwali Goyal
- Department of Ophthalmic Genetics and Visual Function Branch, National Eye Institute, Rockville, MD 20852, United States
| | - Jyoti Rani
- Department of Human Genetics, Guru Nanak Dev University, Amritsar 143005, Punjab, India
| | - Mohd Akbar Bhat
- Department of Ophthalmology, Georgetown University Medical Center, Washington DC, DC 20057, United States
| | - Vanita Vanita
- Department of Human Genetics, Guru Nanak Dev University, Amritsar 143005, Punjab, India
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Fiziev PP, McRae J, Ulirsch JC, Dron JS, Hamp T, Yang Y, Wainschtein P, Ni Z, Schraiber JG, Gao H, Cable D, Field Y, Aguet F, Fasnacht M, Metwally A, Rogers J, Marques-Bonet T, Rehm HL, O'Donnell-Luria A, Khera AV, Farh KKH. Rare penetrant mutations confer severe risk of common diseases. Science 2023; 380:eabo1131. [PMID: 37262146 DOI: 10.1126/science.abo1131] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 03/16/2023] [Indexed: 06/03/2023]
Abstract
We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.
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Affiliation(s)
- Petko P Fiziev
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jacob C Ulirsch
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jacqueline S Dron
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tobias Hamp
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Yanshen Yang
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Pierrick Wainschtein
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zijian Ni
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Joshua G Schraiber
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Hong Gao
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Dylan Cable
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02142, USA
| | - Yair Field
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Francois Aguet
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Marc Fasnacht
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Ahmed Metwally
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Verve Therapeutics, Cambridge, MA 02215, USA
| | - Kyle Kai-How Farh
- Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA
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11
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Fiziev P, McRae J, Ulirsch JC, Dron JS, Hamp T, Yang Y, Wainschtein P, Ni Z, Schraiber JG, Gao H, Cable D, Field Y, Aguet F, Fasnacht M, Metwally A, Rogers J, Marques-Bonet T, Rehm HL, O’Donnell-Luria A, Khera AV, Kai-How Farh K. Rare penetrant mutations confer severe risk of common diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.01.23289356. [PMID: 37205493 PMCID: PMC10187340 DOI: 10.1101/2023.05.01.23289356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ∼10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared to common variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction. One sentence summary Rare variant polygenic risk scores identify individuals with outlier phenotypes in common human diseases and complex traits.
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Affiliation(s)
- Petko Fiziev
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jacob C. Ulirsch
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jacqueline S. Dron
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
| | - Tobias Hamp
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Yanshen Yang
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Pierrick Wainschtein
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Zijian Ni
- Department of Statistics, UW Madison; Madison, Wisconsin 53706, USA
| | - Joshua G. Schraiber
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Hong Gao
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Dylan Cable
- Department of Electrical Engineering and Computer Science, MIT; Cambridge, Massachusetts 02142, USA
| | - Yair Field
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Francois Aguet
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Marc Fasnacht
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Ahmed Metwally
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
- Wisconsin National Primate Research Center, University of Wisconsin; Madison 53715, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC); 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA); 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona; 08193 Barcelona, Spain
| | - Heidi L. Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital; Boston, Massachusetts 02114, USA
| | - Anne O’Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital; Boston, Massachusetts 02114, USA
- Division of Genetics and Genomics, Boston Children’s Hospital; Boston, Massachusetts 02115, USA
| | - Amit V. Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, USA
- Verve Therapeutics, Cambridge, Massachusetts 02215, USA
| | - Kyle Kai-How Farh
- Artificial Intelligence Laboratory, Illumina, Inc.; San Diego, California 92122, USA
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12
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Mollon J, Almasy L, Jacquemont S, Glahn DC. The contribution of copy number variants to psychiatric symptoms and cognitive ability. Mol Psychiatry 2023; 28:1480-1493. [PMID: 36737482 PMCID: PMC10213133 DOI: 10.1038/s41380-023-01978-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 02/05/2023]
Abstract
Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Laura Almasy
- Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, USA
| | - Sebastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, QC, Canada
- Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, QC, Canada
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
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13
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Innes H. Genetic data not yet a "game-changer" for predicting individualised hepatocellular carcinoma risk. J Hepatol 2023; 78:460-462. [PMID: 36592645 DOI: 10.1016/j.jhep.2022.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 12/31/2022]
Affiliation(s)
- Hamish Innes
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow UK; Public Health Scotland, Glasgow, UK; Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK.
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14
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Alyabyeva PV, Petrova MM, Dmitrenko DV, Garganeeva NP, Chumakova GA, Al-Zamil M, Trefilova VV, Nasyrova RF, Shnayder NA. Association of Single-Nucleotide Polymorphisms Rs2779249 (chr17:26128581 C>A) and Rs rs2297518 (chr17: chr17:27769571 G>A) of the NOS2 Gene with Tension-Type Headache and Arterial Hypertension Overlap Syndrome in Eastern Siberia. Genes (Basel) 2023; 14:513. [PMID: 36833440 PMCID: PMC9957272 DOI: 10.3390/genes14020513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/07/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
Inducible nitric oxide (NO) synthase (iNOS), encoded by the NOS2 gene, promotes the generation of high levels of NO to combat harmful environmental influences in a wide range of cells. iNOS can cause adverse effects, such as falling blood pressure, if overexpressed. Thus, according to some data, this enzyme is an important precursor of arterial hypertension (AH) and tension-type headache (TTH), which are the most common multifactorial diseases in adults. The purpose of this study was to investigate the association of rs2779249 (chr17:26128581 C>A) and rs2297518 (chr17: chr17:27769571 G>A) of the NOS2 gene with TTH and AH overlap syndrome (OS) in Caucasians in Eastern Siberia. The sample size was 91 participants: the first group-30 patients with OS; the second group-30 patients AH; and the third group-31 healthy volunteers. RT-PCR was used for the determination of alleles and genotypes of the SNPs rs2779249 and rs2297518 of the NOS2 gene in all groups of participants. We showed that the frequency of allele A was significantly higher among patients with AH compared with healthy volunteers (p-value < 0.05). The frequency of the heterozygous genotype CA of rs2779249 was higher in the first group vs. the control (p-value = 0.03), and in the second group vs. the control (p-value = 0.045). The frequency of the heterozygous genotype GA of rs2297518 was higher in the first group vs. the control (p-value = 0.035), and in the second group vs. the control (p-value = 0.001). The allele A of rs2779249 was associated with OS (OR = 3.17 [95% CI: 1.31-7.67], p-value = 0.009) and AH (OR = 2.94 [95% CI: 1.21-7.15], p-value = 0.015) risks compared with the control. The minor allele A of rs2297518 was associated with OS (OR = 4.0 [95% CI: 0.96-16.61], p-value = 0.035) and AH (OR = 8.17 [95% CI: 2.03-32.79], p-value = 0.001) risks compared with the control. Therefore, our pilot study demonstrated that the SNPs rs2779249 and rs229718 of the NOS2 gene could be promising genetic biomarkers for this OS risk in Caucasians from Eastern Siberia.
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Affiliation(s)
- Polina V. Alyabyeva
- Shared Core Facilities Molecular and Cell Technologies, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Marina M. Petrova
- Shared Core Facilities Molecular and Cell Technologies, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Diana V. Dmitrenko
- Shared Core Facilities Molecular and Cell Technologies, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Natalia P. Garganeeva
- Department of General Medical Practice and Outpatient Therapy, Siberian State Medical University, 634050 Tomsk, Russia
| | - Galina A. Chumakova
- Department of Therapy and General Medical Practice with a Course of Postgraduate Professional Education, Altai State Medical University, 656038 Barnaul, Russia
| | - Mustafa Al-Zamil
- Department of Physiotherapy, Faculty of Continuing Medical Education, Peoples’ Friendship University of Russia, 117198 Moscow, Russia
| | - Vera V. Trefilova
- Neurological Department No. 16, Hospital for War Veterans, 193079 St. Petersburg, Russia
| | - Regina F. Nasyrova
- Institute of Personalized Psychiatry and Neurology, V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, 192019 St. Petersburg, Russia
| | - Natalia A. Shnayder
- Shared Core Facilities Molecular and Cell Technologies, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
- Institute of Personalized Psychiatry and Neurology, V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, 192019 St. Petersburg, Russia
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15
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Identification of rare missense mutations in the glutamate ionotropic receptor AMPA type subunit genes in schizophrenia. Psychiatr Genet 2023; 33:20-25. [PMID: 36617743 DOI: 10.1097/ypg.0000000000000328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE The alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptors significantly regulate the synaptic transmission and functions of various synaptic receptors. This study aimed to identify single nucleotide mutations in the glutamate receptor, ionotropic, AMPA type (GRIA) gene family, which is associated with schizophrenia. METHODS The exon regions of four genes (GRIA1, GRIA2, GRIA3, and GRIA4) encoding glutamate ionotropic receptor AMPA type proteins were resequenced in 516 patients with schizophrenia. We analyzed the protein function of the identified rare mutants via immunoblotting. RESULTS A total of 24 coding variants were detected in the GRIA gene family, including six missense mutations, 17 synonymous mutations, and one frameshift insertion. Notably, three ultra-rare missense mutations (GRIA1p.V182A, GRIA2p.P123Q, and GRIA4p.Y491H) were not documented in the single nucleotide polymorphism database, gnomAD genomes, and 1517 healthy controls available from Taiwan BioBank. Immunoblotting revealed GRIA4p.Y491H mutant with altered protein expressions in cultured cells compared with the wild type. CONCLUSION Our findings suggest that, in some patients affected by schizophrenia, the GRIA gene family harbors rare functional mutations, which support rare coding variants that could contribute to the genetic architecture of this illness. The in-vitro impacts of these rare pathological mutations on the pathophysiology of schizophrenia are worthy of future investigation.
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16
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Wang F, Moon W, Letsou W, Sapkota Y, Wang Z, Im C, Baedke JL, Robison L, Yasui Y. Genome-Wide Analysis of Rare Haplotypes Associated with Breast Cancer Risk. Cancer Res 2023; 83:332-345. [PMID: 36354368 PMCID: PMC9852031 DOI: 10.1158/0008-5472.can-22-1888] [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: 06/13/2022] [Revised: 09/09/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022]
Abstract
Numerous common genetic variants have been linked to breast cancer risk, but they only partially explain the total breast cancer heritability. Inference from Nordic population-based twin data indicates rare high-risk loci as the chief determinant of breast cancer risk. Here, we use haplotypes, rather than single variants, to identify rare high-risk loci for breast cancer. With computationally phased genotypes from 181,034 white British women in the UK Biobank, a genome-wide haplotype-breast cancer association analysis was conducted using sliding windows of 5 to 500 consecutive array-genotyped variants. In the discovery stage, haplotype-breast cancer associations were evaluated retrospectively in the prestudy-enrollment data including 5,487 breast cancer cases. Breast cancer hazard ratios (HR) for additive haplotypic effects were estimated using Cox regression. The replication analysis included a prospective cohort of women free of breast cancer at enrollment, of whom 3,524 later developed breast cancer. This two-stage analysis detected 13 rare loci (frequency <1%), each associated with an appreciable breast cancer-risk increase (discovery: HRs = 2.84-6.10, P < 5 × 10-8; replication: HRs = 2.08-5.61, P < 0.01). In contrast, the variants that formed these rare haplotypes individually exhibited much smaller effects. Functional annotation revealed extensive cis-regulatory DNA elements in breast cancer-related cells underlying the replicated rare haplotypes. Using phased, imputed genotypes from 30,064 cases and 25,282 controls in the DRIVE OncoArray case-control study, 6 of the 13 rare-loci associations were found generalizable (odds ratio estimates: 1.48-7.67, P < 0.05). This study demonstrates the complementary advantage of utilizing rare haplotypes to capture novel risk loci and suggests the potential for the discovery of more genetic elements contributing to cancer heritability as large data sets of germline whole-genome sequencing become available. SIGNIFICANCE A genome-wide two-stage haplotype analysis identifies rare haplotypes associated with breast cancer risk and suggests that the rare risk haplotypes represent long-range interactions with regulatory consequences influencing cancer risk.
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Affiliation(s)
- Fan Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Wonjong Moon
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - William Letsou
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Yadav Sapkota
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Cindy Im
- School of Public Health, University of Alberta, Edmonton, Alberta T6G 1C9, Canada
| | - Jessica L. Baedke
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Leslie Robison
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
- School of Public Health, University of Alberta, Edmonton, Alberta T6G 1C9, Canada
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17
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Li N, Chen L, Zhou Y, Wei Q. A fast and efficient approach for gene-based association studies of ordinal phenotypes. Stat Appl Genet Mol Biol 2023; 22:sagmb-2021-0068. [PMID: 36724206 DOI: 10.1515/sagmb-2021-0068] [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: 09/09/2021] [Accepted: 01/16/2023] [Indexed: 02/02/2023]
Abstract
Many human disease conditions need to be measured by ordinal phenotypes, so analysis of ordinal phenotypes is valuable in genome-wide association studies (GWAS). However, existing association methods for dichotomous or quantitative phenotypes are not appropriate to ordinal phenotypes. Therefore, based on an aggregated Cauchy association test, we propose a fast and efficient association method to test the association between genetic variants and an ordinal phenotype. To enrich association signals of rare variants, we first use the burden method to aggregate rare variants. Then we respectively test the significance of the aggregated rare variants and other common variants. Finally, the combination of transformed variant-level P values is taken as test statistic, that approximately follows Cauchy distribution under the null hypothesis. Extensive simulation studies and analysis of GAW19 show that our proposed method is powerful and computationally fast as a gene-based method. Especially, in the presence of an extremely low proportion of causal variants in a gene, our method has better performance.
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Affiliation(s)
- Nanxing Li
- School of Mathematical Sciences, Heilongjiang University, Harbin 150080, P. R. China
| | - Lili Chen
- School of Mathematical Sciences, Heilongjiang University, Harbin 150080, P. R. China
| | - Yajing Zhou
- School of Mathematical Sciences, Heilongjiang University, Harbin 150080, P. R. China
| | - Qianran Wei
- School of Mathematical Sciences, Heilongjiang University, Harbin 150080, P. R. China
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18
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Wang Y, Chen H, Peloso GM, DeStefano AL, Dupuis J. Exploiting family history in aggregation unit-based genetic association tests. Eur J Hum Genet 2022; 30:1355-1362. [PMID: 34690355 PMCID: PMC9712547 DOI: 10.1038/s41431-021-00980-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 07/20/2021] [Accepted: 10/04/2021] [Indexed: 11/08/2022] Open
Abstract
The development of sequencing technology calls for new powerful methods to detect disease associations and lower the cost of sequencing studies. Family history (FH) contains information on disease status of relatives, adding valuable information about the probands' health problems and risk of diseases. Incorporating data from FH is a cost-effective way to improve statistical evidence in genetic studies, and moreover, overcomes limitations in study designs with insufficient cases or missing genotype information for association analysis. We proposed family history aggregation unit-based test (FHAT) and optimal FHAT (FHAT-O) to exploit available FH for rare variant association analysis. Moreover, we extended liability threshold model of case-control status and FH (LT-FH) method in aggregated unit-based methods and compared that with FHAT and FHAT-O. The computational efficiency and flexibility of the FHAT and FHAT-O were demonstrated through both simulations and applications. We showed that FHAT, FHAT-O, and LT-FH methods offer reasonable control of the type I error unless case/control ratio is unbalanced, in which case they result in smaller inflation than that observed with conventional methods excluding FH. We also demonstrated that FHAT and FHAT-O are more powerful than LT-FH and conventional methods in many scenarios. By applying FHAT and FHAT-O to the analysis of all cause dementia and hypertension using the exome sequencing data from the UK Biobank, we showed that our methods can improve significance for known regions. Furthermore, we replicated the previous associations in all cause dementia and hypertension and detected novel regions through the exome-wide analysis.
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Affiliation(s)
- Yanbing Wang
- Department of Biostatistics, School of Public Health, Boston University, Massachusetts, MA, 02215, USA.
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Gina M Peloso
- Department of Biostatistics, School of Public Health, Boston University, Massachusetts, MA, 02215, USA
| | - Anita L DeStefano
- Department of Biostatistics, School of Public Health, Boston University, Massachusetts, MA, 02215, USA
| | - Josée Dupuis
- Department of Biostatistics, School of Public Health, Boston University, Massachusetts, MA, 02215, USA.
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19
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Dapas M, Dunaif A. Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification. Endocr Rev 2022; 43:927-965. [PMID: 35026001 PMCID: PMC9695127 DOI: 10.1210/endrev/bnac001] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Indexed: 01/16/2023]
Abstract
Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.
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Affiliation(s)
- Matthew Dapas
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Andrea Dunaif
- Division of Endocrinology, Diabetes and Bone Disease, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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20
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Holborn MA, Ford G, Turner S, Mellet J, van Rensburg J, Joubert F, Pepper MS. The NESHIE and CP Genetics Resource (NCGR): A database of genes and variants reported in neonatal encephalopathy with suspected hypoxic ischemic encephalopathy (NESHIE) and consequential cerebral palsy (CP). Genomics 2022; 114:110508. [PMID: 36270382 PMCID: PMC9726645 DOI: 10.1016/j.ygeno.2022.110508] [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: 08/30/2022] [Revised: 10/12/2022] [Accepted: 10/17/2022] [Indexed: 01/15/2023]
Abstract
Neonatal encephalopathy (NE) with suspected hypoxic ischaemic encephalopathy (HIE) (NESHIE) is a complex syndrome occurring in newborns, characterised by altered neurological function. It has been suggested that genetic variants may influence NESHIE susceptibility and outcomes. Unlike NESHIE, for which a limited number of genetic studies have been performed, many studies have identified genetic variants associated with cerebral palsy (CP), which can develop from severe NESHIE. Identifying variants in patients with CP, as a consequence of NESHIE, may provide a starting point for the identification of genetic variants associated with NESHIE outcomes. We have constructed NCGR (NESHIE and CP Genetics Resource), a database of genes and variants reported in patients with NESHIE and CP (where relevant to NESHIE), for the purpose of collating and comparing genetic findings between the two conditions. In this paper we describe the construction and functionality of NCGR. Furthermore, we demonstrate how NCGR can be used to prioritise genes and variants of potential clinical relevance that may underlie a genetic predisposition to NESHIE and contribute to an understanding of its pathogenesis.
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Affiliation(s)
- Megan A. Holborn
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Graeme Ford
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa,Centre for Bioinformatics and Computational Biology, Genomics Research Institute, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Sarah Turner
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa,Centre for Bioinformatics and Computational Biology, Genomics Research Institute, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Juanita Mellet
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Jeanne van Rensburg
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Fourie Joubert
- Centre for Bioinformatics and Computational Biology, Genomics Research Institute, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Michael S. Pepper
- Institute for Cellular and Molecular Medicine, Department of Immunology; SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa,Corresponding author.
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Chen W, Coombes BJ, Larson NB. Recent advances and challenges of rare variant association analysis in the biobank sequencing era. Front Genet 2022; 13:1014947. [PMID: 36276986 PMCID: PMC9582646 DOI: 10.3389/fgene.2022.1014947] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 09/22/2022] [Indexed: 12/04/2022] Open
Abstract
Causal variants for rare genetic diseases are often rare in the general population. Rare variants may also contribute to common complex traits and can have much larger per-allele effect sizes than common variants, although power to detect these associations can be limited. Sequencing costs have steadily declined with technological advancements, making it feasible to adopt whole-exome and whole-genome profiling for large biobank-scale sample sizes. These large amounts of sequencing data provide both opportunities and challenges for rare-variant association analysis. Herein, we review the basic concepts of rare-variant analysis methods, the current state-of-the-art methods in utilizing variant annotations or external controls to improve the statistical power, and particular challenges facing rare variant analysis such as accounting for population structure, extremely unbalanced case-control design. We also review recent advances and challenges in rare variant analysis for familial sequencing data and for more complex phenotypes such as survival data. Finally, we discuss other potential directions for further methodology investigation.
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Affiliation(s)
- Wenan Chen
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN, United States
- *Correspondence: Wenan Chen, ; Brandon J. Coombes, ; Nicholas B. Larson,
| | - Brandon J. Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
- *Correspondence: Wenan Chen, ; Brandon J. Coombes, ; Nicholas B. Larson,
| | - Nicholas B. Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
- *Correspondence: Wenan Chen, ; Brandon J. Coombes, ; Nicholas B. Larson,
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22
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Aborageh M, Krawitz P, Fröhlich H. Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine. FRONTIERS IN MOLECULAR MEDICINE 2022; 2:933383. [PMID: 39086979 PMCID: PMC11285583 DOI: 10.3389/fmmed.2022.933383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 08/30/2022] [Indexed: 08/02/2024]
Abstract
Parkinson's Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated with disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods to detect associations between genetic variants and the disease phenotypes in existing PD GWAS. Secondly, we discuss the potential of machine learning approaches to better quantify disease phenotypes and to move beyond disease understanding towards a better-personalized treatment of the disease.
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Affiliation(s)
- Mohamed Aborageh
- Bonn-Aachen International Center for Information Technology (B-IT), Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Peter Krawitz
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany
| | - Holger Fröhlich
- Bonn-Aachen International Center for Information Technology (B-IT), Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
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23
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Pang H, Lin J, Luo S, Huang G, Li X, Xie Z, Zhou Z. The missing heritability in type 1 diabetes. Diabetes Obes Metab 2022; 24:1901-1911. [PMID: 35603907 PMCID: PMC9545639 DOI: 10.1111/dom.14777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/04/2022] [Accepted: 05/17/2022] [Indexed: 12/15/2022]
Abstract
Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.
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Affiliation(s)
- Haipeng Pang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Jian Lin
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Shuoming Luo
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Gan Huang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Zhiguo Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
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Huang J, Su M, Chen H, Wu S, Chen Z. The S267F variant of sodium-taurocholate-co-transporting polypeptide is strongly associated with resistance to chronic hepatitis B and high level of serum total bile acids. LIVER RESEARCH 2022. [DOI: 10.1016/j.livres.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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25
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Müller-Nedebock AC, Pfaff AL, Pienaar IS, Kõks S, van der Westhuizen FH, Elson JL, Bardien S. Mitochondrial DNA variation in Parkinson’s disease: Analysis of “out-of-place” population variants as a risk factor. Front Aging Neurosci 2022; 14:921412. [PMID: 35912088 PMCID: PMC9330142 DOI: 10.3389/fnagi.2022.921412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/30/2022] [Indexed: 12/17/2022] Open
Abstract
Mitochondrial DNA (mtDNA), a potential source of mitochondrial dysfunction, has been implicated in Parkinson’s disease (PD). However, many previous studies investigating associations between mtDNA population variation and PD reported inconsistent or contradictory findings. Here, we investigated an alternative hypothesis to determine whether mtDNA variation could play a significant role in PD risk. Emerging evidence suggests that haplogroup-defining mtDNA variants may have pathogenic potential if they occur “out-of-place” on a different maternal lineage. We hypothesized that the mtDNA of PD cases would be enriched for out-of-place variation in genes encoding components of the oxidative phosphorylation complexes. We tested this hypothesis with a unique dataset comprising whole mitochondrial genomes of 70 African ancestry PD cases, two African ancestry control groups (n = 78 and n = 53) and a replication group of 281 European ancestry PD cases and 140 controls from the Parkinson’s Progression Markers Initiative cohort. Significantly more African ancestry PD cases had out-of-place variants than controls from the second control group (P < 0.0125), although this association was not observed in the first control group nor the replication group. As the first mtDNA study to include African ancestry PD cases and to explore out-of-place variation in a PD context, we found evidence that such variation might be significant in this context, thereby warranting further replication in larger cohorts.
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Affiliation(s)
- Amica C. Müller-Nedebock
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council, Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Abigail L. Pfaff
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Murdoch, WA, Australia
| | - Ilse S. Pienaar
- Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Sulev Kõks
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Murdoch, WA, Australia
| | | | - Joanna L. Elson
- Human Metabolomics, North-West University, Potchefstroom, South Africa
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Soraya Bardien
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council, Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
- *Correspondence: Soraya Bardien,
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Rodrigue AL, Mathias SR, Knowles EEM, Mollon J, Almasy L, Schultz L, Turner J, Calhoun V, Glahn DC. Specificity of Psychiatric Polygenic Risk Scores and their Effects on Associated Risk Phenotypes. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022. [PMID: 37519455 PMCID: PMC10382704 DOI: 10.1016/j.bpsgos.2022.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Polygenic risk scores (PRSs) are indices of genetic liability for illness, but their clinical utility for predicting risk for a specific psychiatric disorder is limited. Genetic overlap among disorders and their effects on allied phenotypes may be a possible explanation, but this has been difficult to quantify given focus on singular disorders and/or allied phenotypes. Methods We constructed PRSs for 5 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder) and 3 nonpsychiatric control traits (height, type II diabetes, irritable bowel disease) in the UK Biobank (N = 31,616) and quantified associations between PRSs and phenotypes allied with mental illness: behavioral (symptoms, cognition, trauma) and brain measures from magnetic resonance imaging. We then evaluated the extent of specificity among PRSs and their effects on these allied phenotypes. Results Correlations among psychiatric PRSs replicated previous work, with overlap between schizophrenia and bipolar disorder, which was distinct from overlap between autism spectrum disorder and attention-deficit/hyperactivity disorder; overlap between psychiatric and control PRSs was minimal. There was, however, substantial overlap of PRS effects on allied phenotypes among psychiatric disorders and among psychiatric disorders and control traits, where the extent and pattern of overlap was phenotype specific. Conclusions Results show that genetic distinctions between psychiatric disorders and between psychiatric disorders and control traits exist, but this does not extend to their effects on allied phenotypes. Although overlap can be informative, work is needed to construct PRSs that will function at the level of specificity needed for clinical application.
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Fernández-Santiago R, Sharma M. What have we learned from genome-wide association studies (GWAS) in Parkinson's disease? Ageing Res Rev 2022; 79:101648. [PMID: 35595184 DOI: 10.1016/j.arr.2022.101648] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 04/11/2022] [Accepted: 05/11/2022] [Indexed: 11/01/2022]
Abstract
After fifteen years of genome-wide association studies (GWAS) in Parkinson's disease (PD), what have we learned? Addressing this question will help catalogue the progress made towards elucidating disease mechanisms, improving the clinical utility of the identified loci, and envisioning how we can harness the strides to develop translational GWAS strategies. Here we review the advances of PD GWAS made to date while critically addressing the challenges and opportunities for next-generation GWAS. Thus, deciphering the missing heritability in underrepresented populations is currently at the reach of hand for a truly comprehensive understanding of the genetics of PD across the different ethnicities. Moreover, state-of-the-art GWAS designs hold a true potential for enhancing the clinical applicability of genetic findings, for instance, by improving disease prediction (PD risk and progression). Lastly, advanced PD GWAS findings, alone or in combination with clinical and environmental parameters, are expected to have the capacity for defining patient enriched cohorts stratified by genetic risk profiles and readily available for neuroprotective clinical trials. Overall, envisioning future strategies for advanced GWAS is currently timely and can be instrumental in providing novel genetic readouts essential for a true clinical translatability of PD genetic findings.
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Li MK, Yuan YX, Zhu B, Wang KW, Fung WK, Zhou JY. Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation. Genes (Basel) 2022; 13:genes13050827. [PMID: 35627212 PMCID: PMC9140558 DOI: 10.3390/genes13050827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/01/2022] [Accepted: 05/02/2022] [Indexed: 11/16/2022] Open
Abstract
Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases, and currently several methods have been proposed to estimate the degree of the XCI-S (denoted as γ) for a single locus. However, no method has been available to estimate γ for genes. Therefore, in this paper, we first propose the point estimate and the penalized point estimate of γ for genes, and then derive its confidence intervals based on the Fieller’s and penalized Fieller’s methods, respectively. Further, we consider the constraint condition of γ∈[0, 2] and propose the Bayesian methods to obtain the point estimates and the credible intervals of γ, where a truncated normal prior and a uniform prior are respectively used (denoted as GBN and GBU). The simulation results show that the Bayesian methods can avoid the extreme point estimates (0 or 2), the empty sets, the noninformative intervals ([0, 2]) and the discontinuous intervals to occur. GBN performs best in both the point estimation and the interval estimation. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. In summary, in practical applications, we recommend using GBN to estimate γ of genes.
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Affiliation(s)
- Meng-Kai Li
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; (M.-K.L.); (Y.-X.Y.); (B.Z.); (K.-W.W.)
- Guangdong-Hong Hong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou 510006, China
| | - Yu-Xin Yuan
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; (M.-K.L.); (Y.-X.Y.); (B.Z.); (K.-W.W.)
- Guangdong-Hong Hong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou 510006, China
| | - Bin Zhu
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; (M.-K.L.); (Y.-X.Y.); (B.Z.); (K.-W.W.)
- Guangdong-Hong Hong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou 510006, China
| | - Kai-Wen Wang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; (M.-K.L.); (Y.-X.Y.); (B.Z.); (K.-W.W.)
- Guangdong-Hong Hong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou 510006, China
| | - Wing Kam Fung
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, China;
| | - Ji-Yuan Zhou
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; (M.-K.L.); (Y.-X.Y.); (B.Z.); (K.-W.W.)
- Guangdong-Hong Hong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou 510006, China
- Correspondence:
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Fan D, Zheng C, Wu W, Chen Y, Chen D, Hu X, Shen C, Chen M, Li R, Chen Y. MMP9 SNP and MMP SNP-SNP interactions increase the risk for ischemic stroke in the Han Hakka population. Brain Behav 2022; 12:e2473. [PMID: 34984852 PMCID: PMC8865147 DOI: 10.1002/brb3.2473] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/06/2021] [Accepted: 12/13/2021] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVES To investigate the association of eight variants of four matrix metalloproteinase (MMP) genes with ischemic stroke (IS) and whether interactions among these single nucleotide polymorphisms (SNPs) increases the risk of IS. METHODS Among 547 patients with ischemic stroke and 350 controls, matrix-assisted laser desorption/ionization time of flight mass spectrometry was used to examine eight variants arising from four different genes, including MMP-1 (rs1799750), MMP-2 (rs243865, rs2285053, rs2241145), MMP-9 (rs17576), and MMP-12 (rs660599, rs2276109, and rs652438). Gene-gene interactions were employed using generalized multifactor dimensionality reduction (GMDR) methods. RESULTS The frequency of rs17576 was significantly higher in IS patients than in controls (p = .033). Logistic regression analysis revealed the AG and GG genotypes of rs17576 to be associated with a higher risk for IS, with the odds ratio and 95% confidence interval being 2.490 (1.251-4.959) and 2.494 (1.274-4.886), respectively. GMDR analysis showed a significant SNP-SNP interaction between rs17576 and rs660599 (the testing balanced accuracy was 53.70% and cross-validation consistency was 8/10, p = .0107). Logistic regression analysis showed the interaction between rs17576 and rs660599 to be an independent risk factor for IS with an odds ratio of 1.568 and a 95% confidence interval of 1.152-2.135. CONCLUSION An MMP-9 rs17576 polymorphism is associated with increased IS risk in the Han Hakka population and interaction between MMP-9 rs17576 and MMP-12 rs660599 is associated with increased IS risk as well.
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Affiliation(s)
- Daofeng Fan
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Chong Zheng
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Wenbao Wu
- Department of Acupuncture and Moxibustion, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Yinjuan Chen
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Dongping Chen
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Xiaohong Hu
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Chaoxiong Shen
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Mingsheng Chen
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Rongtong Li
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
| | - Yangui Chen
- Department of Neurology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fijian, China
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Piras D, Lepori N, Cabiddu G, Pani A. How Genetics Can Improve Clinical Practice in Chronic Kidney Disease: From Bench to Bedside. J Pers Med 2022; 12:jpm12020193. [PMID: 35207681 PMCID: PMC8875178 DOI: 10.3390/jpm12020193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/17/2022] [Accepted: 01/24/2022] [Indexed: 01/27/2023] Open
Abstract
Chronic kidney disease (CKD) is considered a major global health problem with high socio-economic costs: the risk of CKD in individuals with an affected first degree relative has been found to be three times higher than in the general population. Genetic factors are known to be involved in CKD pathogenesis, both due to the possible presence of monogenic pathologies as causes of CKD, and to the role of numerous gene variants in determining susceptibility to the development of CKD. The genetic study of CKD patients can represent a useful tool in the hands of the clinician; not only in the diagnostic and prognostic field, but potentially also in guiding therapeutic choices and in designing clinical trials. In this review we discuss the various aspects of the role of genetic analysis on clinical management of patients with CKD with a focus on clinical applications. Several topics are discussed in an effort to provide useful information for daily clinical practice: definition of susceptibility to the development of CKD, identification of unrecognized monogenic diseases, reclassification of the etiological diagnosis, role of pharmacogenetics.
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Affiliation(s)
- Doloretta Piras
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Correspondence:
| | - Nicola Lepori
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
| | - Gianfranca Cabiddu
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
| | - Antonello Pani
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerce (CNR), 09042 Monserrato, Italy
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Khani M, Gibbons E, Bras J, Guerreiro R. Challenge accepted: uncovering the role of rare genetic variants in Alzheimer's disease. Mol Neurodegener 2022; 17:3. [PMID: 35000612 PMCID: PMC8744312 DOI: 10.1186/s13024-021-00505-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 12/06/2021] [Indexed: 12/11/2022] Open
Abstract
The search for rare variants in Alzheimer's disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful.Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs.Multiple independent studies have now shown associations of rare variants in NOTCH3, TREM2, SORL1, ABCA7, BIN1, CLU, NCK2, AKAP9, UNC5C, PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions.Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.
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Affiliation(s)
- Marzieh Khani
- School of Biology, College of Science, University of Tehran, Tehran, Iran
| | - Elizabeth Gibbons
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 USA
| | - Jose Bras
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI USA
| | - Rita Guerreiro
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI USA
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Schiabor Barrett KM, Masnick M, Hatchell KE, Savatt JM, Banet N, Buchanan A, Willard HF. Clinical validation of genomic functional screen data: analysis of observed BRCA1 variants in an unselected population cohort. HGG ADVANCES 2022; 3:100086. [PMID: 35128484 PMCID: PMC8804171 DOI: 10.1016/j.xhgg.2022.100086] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 01/06/2022] [Indexed: 12/02/2022] Open
Abstract
Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.
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Duong HTT, Suzuki H, Katagiri S, Shibata M, Arai M, Yura K. Computational study of the impact of nucleotide variations on highly conserved proteins: In the case of actin. Biophys Physicobiol 2022; 19:e190025. [PMID: 36160324 PMCID: PMC9465404 DOI: 10.2142/biophysico.bppb-v19.0025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 07/27/2022] [Indexed: 12/01/2022] Open
Abstract
Sequencing of individual human genomes enables studying relationship among nucleotide variations, amino acid substitutions, effect on protein structures and diseases. Many studies have found general tendencies, for instance, that pathogenic variations tend to be found in the buried regions of the protein structures, that benign variations tend to be found on the surface of the proteins, and that variations on evolutionary conserved residues tend to be pathogenic. These tendencies were deduced from globular proteins with standard evolutionary changes in amino acid sequences. In this study, we investigated the variation distribution on actin, one of the highly conserved proteins. Many nucleotide variations and three-dimensional structures of actin have been registered in databases. By combining those data, we found that variations buried inside the protein were rather benign and variations on the surface of the protein were pathogenic. This idiosyncratic distribution of the variation impact is likely ascribed to the extensive use of the surface of the protein for protein-protein interactions in actin.
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Affiliation(s)
- Ha T. T. Duong
- Graduate School of Humanities and Sciences, Ochanomizu University
| | - Hirofumi Suzuki
- Graduate School of Advanced Science and Engineering, Waseda University
| | - Saki Katagiri
- Graduate School of Humanities and Sciences, Ochanomizu University
| | - Mayu Shibata
- Graduate School of Humanities and Sciences, Ochanomizu University
| | - Misae Arai
- Graduate School of Humanities and Sciences, Ochanomizu University
| | - Kei Yura
- Graduate School of Humanities and Sciences, Ochanomizu University
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Cross B, Turner R, Pirmohamed M. Polygenic risk scores: An overview from bench to bedside for personalised medicine. Front Genet 2022; 13:1000667. [PMID: 36437929 PMCID: PMC9692112 DOI: 10.3389/fgene.2022.1000667] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.
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Affiliation(s)
- Benjamin Cross
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Richard Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
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DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment? Int J Mol Sci 2021; 22:ijms222111652. [PMID: 34769081 PMCID: PMC8584054 DOI: 10.3390/ijms222111652] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 12/15/2022] Open
Abstract
Diabetes is a severe threat to global health. Almost 500 million people live with diabetes worldwide. Most of them have type 2 diabetes (T2D). T2D patients are at risk of developing severe and life-threatening complications, leading to an increased need for medical care and reduced quality of life. Improved care for people with T2D is essential. Actions aiming at identifying undiagnosed diabetes and at preventing diabetes in those at high risk are needed as well. To this end, biomarker discovery and validation of risk assessment for T2D are critical. Alterations of DNA methylation have recently helped to better understand T2D pathophysiology by explaining differences among endophenotypes of diabetic patients in tissues. Recent evidence further suggests that variations of DNA methylation might contribute to the risk of T2D even more significantly than genetic variability and might represent a valuable tool to predict T2D risk. In this review, we focus on recent information on the contribution of DNA methylation to the risk and the pathogenesis of T2D. We discuss the limitations of these studies and provide evidence supporting the potential for clinical application of DNA methylation marks to predict the risk and progression of T2D.
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36
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Barizzone N, Cagliani R, Basagni C, Clarelli F, Mendozzi L, Agliardi C, Forni D, Tosi M, Mascia E, Favero F, Corà D, Corrado L, Sorosina M, Esposito F, Zuccalà M, Vecchio D, Liguori M, Comi C, Comi G, Martinelli V, Filippi M, Leone M, Martinelli-Boneschi F, Caputo D, Sironi M, Guerini FR, D’Alfonso S. An Investigation of the Role of Common and Rare Variants in a Large Italian Multiplex Family of Multiple Sclerosis Patients. Genes (Basel) 2021; 12:1607. [PMID: 34681001 PMCID: PMC8535321 DOI: 10.3390/genes12101607] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/26/2021] [Accepted: 10/01/2021] [Indexed: 12/30/2022] Open
Abstract
Known multiple sclerosis (MS) susceptibility variants can only explain half of the disease's estimated heritability, whereas low-frequency and rare variants may partly account for the missing heritability. Thus, here we sought to determine the occurrence of rare functional variants in a large Italian MS multiplex family with five affected members. For this purpose, we combined linkage analysis and next-generation sequencing (NGS)-based whole exome and whole genome sequencing (WES and WGS, respectively). The genetic burden attributable to known common MS variants was also assessed by weighted genetic risk score (wGRS). We found a significantly higher burden of common variants in the affected family members compared to that observed among sporadic MS patients and healthy controls (HCs). We also identified 34 genes containing at least one low-frequency functional variant shared among all affected family members, showing a significant enrichment in genes involved in specific biological processes-particularly mRNA transport-or neurodegenerative diseases. Altogether, our findings point to a possible pathogenic role of different low-frequency functional MS variants belonging to shared pathways. We propose that these rare variants, together with other known common MS variants, may account for the high number of affected family members within this MS multiplex family.
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Affiliation(s)
- Nadia Barizzone
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
| | - Rachele Cagliani
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (D.F.); (M.S.)
| | - Chiara Basagni
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
| | - Ferdinando Clarelli
- Laboratory of Genetics of Neurological Complex Disorders, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (F.C.); (E.M.); (M.S.); (F.E.)
| | - Laura Mendozzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (L.M.); (C.A.); (D.C.); (F.R.G.)
| | - Cristina Agliardi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (L.M.); (C.A.); (D.C.); (F.R.G.)
| | - Diego Forni
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (D.F.); (M.S.)
| | - Martina Tosi
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
| | - Elisabetta Mascia
- Laboratory of Genetics of Neurological Complex Disorders, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (F.C.); (E.M.); (M.S.); (F.E.)
| | - Francesco Favero
- Department of Translational Medicine, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (F.F.); (D.C.)
| | - Davide Corà
- Department of Translational Medicine, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (F.F.); (D.C.)
| | - Lucia Corrado
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
| | - Melissa Sorosina
- Laboratory of Genetics of Neurological Complex Disorders, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (F.C.); (E.M.); (M.S.); (F.E.)
| | - Federica Esposito
- Laboratory of Genetics of Neurological Complex Disorders, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy; (F.C.); (E.M.); (M.S.); (F.E.)
| | - Miriam Zuccalà
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
| | - Domizia Vecchio
- Department of Translational Medicine, IRCAD (Interdisciplinary Research Center of Autoimmune Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (D.V.); (C.C.)
| | - Maria Liguori
- Institute of Biomedical Technologies, Bari Unit, National Research Council, 70126 Bari, Italy;
| | - Cristoforo Comi
- Department of Translational Medicine, IRCAD (Interdisciplinary Research Center of Autoimmune Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (D.V.); (C.C.)
| | - Giancarlo Comi
- Vita-Salute San Raffaele University, 20132 Milan, Italy; (G.C.); (M.F.)
| | - Vittorio Martinelli
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy;
| | - Massimo Filippi
- Vita-Salute San Raffaele University, 20132 Milan, Italy; (G.C.); (M.F.)
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy;
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Maurizio Leone
- Dipartimento di Emergenza e Area Critica, UO Neurologia, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, 71013 Foggia, Italy;
| | - Filippo Martinelli-Boneschi
- Department of Pathophysiology and Transplantation (DEPT), Dino Ferrari Centre, Neuroscience Section, University of Milan, 20122 Milan, Italy;
- Neurology Unit and MS Centre, Foundation IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Domenico Caputo
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (L.M.); (C.A.); (D.C.); (F.R.G.)
| | - Manuela Sironi
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (D.F.); (M.S.)
| | - Franca Rosa Guerini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (L.M.); (C.A.); (D.C.); (F.R.G.)
| | - Sandra D’Alfonso
- Department of Health Sciences, CAAD (Center for Translational Research on Autoimmune and Allergic Diseases), University of Eastern Piedmont, 28100 Novara, Italy; (C.B.); (M.T.); (L.C.); (M.Z.)
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Goodin DS, Khankhanian P, Gourraud PA, Vince N. Genetic susceptibility to multiple sclerosis: interactions between conserved extended haplotypes of the MHC and other susceptibility regions. BMC Med Genomics 2021; 14:183. [PMID: 34246256 PMCID: PMC8272333 DOI: 10.1186/s12920-021-01018-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 06/11/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND To study the accumulation of MS-risk resulting from different combinations of MS-associated conserved-extended-haplotypes (CEHs) of the MHC and three non-MHC "risk-haplotypes" nearby genes EOMES, ZFP36L1, and CLEC16A. Many haplotypes are MS-associated despite having population-frequencies exceeding the percentage of genetically-susceptible individuals. The basis of this frequency-disparity requires explanation. METHODS The SNP-data from the WTCCC was phased at the MHC and three non-MHC susceptibility-regions. CEHs at the MHC were classified into five haplotype-groups: (HLA-DRB1*15:01 ~ DQB1*06:02 ~ a1)-containing (H +); extended-risk (ER); all-protective (AP); neutral (0); and the single-CEH (c1). MS-associations for different "risk-combinations" at the MHC and other non-MHC "risk-loci" and the appropriateness of additive and multiplicative risk-accumulation models were assessed. RESULTS Different combinations of "risk-haplotypes" produce a final MS-risk closer to additive rather than multiplicative risk-models but neither model was consistent. Thus, (H +)-haplotypes had greater impact when combined with (0)-haplotypes than with (H +)-haplotypes, whereas, (H +)-haplotypes had greater impact when combined with a (c1)-haplotypes than with (0)-haplotypes. Similarly, risk-genotypes (0,H +), (c1,H +), (H + ,H +) and (0,c1) were additive with risks from non-MHC risk-loci, whereas risk-genotypes (ER,H +) and (AP,c1) were unaffected. CONCLUSIONS Genetic-susceptibility to MS is essential for MS to develop but actually developing MS depends heavily upon both an individual's particular combination of "risk-haplotypes" and how these loci interact.
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Affiliation(s)
- D S Goodin
- Department of Neurology, University of California, UCSF MS Center, San Francisco 675 Nelson Rising Lane, Suite #221D, CA, 94158, San Francisco, USA.
| | - P Khankhanian
- Center for Neuro-Engineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - P A Gourraud
- Department of Neurology, University of California, UCSF MS Center, San Francisco 675 Nelson Rising Lane, Suite #221D, CA, 94158, San Francisco, USA
- Centre de Recherche en Transplantation Et Immunologie, UMR 1064, INSERM, Université de Nantes, Nantes, France
- Institut de Transplantation Urologie Néphrologie (ITUN), CHU Nantes, Nantes, France
| | - N Vince
- Centre de Recherche en Transplantation Et Immunologie, UMR 1064, INSERM, Université de Nantes, Nantes, France
- Institut de Transplantation Urologie Néphrologie (ITUN), CHU Nantes, Nantes, France
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Shivakumar M, Miller JE, Dasari VR, Zhang Y, Lee MTM, Carey DJ, Gogoi R, Kim D. Genetic Analysis of Functional Rare Germline Variants across Nine Cancer Types from an Electronic Health Record Linked Biobank. Cancer Epidemiol Biomarkers Prev 2021; 30:1681-1688. [PMID: 34244158 DOI: 10.1158/1055-9965.epi-21-0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/15/2021] [Accepted: 06/17/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Rare variants play an essential role in the etiology of cancer. In this study, we aim to characterize rare germline variants that impact the risk of cancer. METHODS We performed a genome-wide rare variant analysis using germline whole exome sequencing (WES) data derived from the Geisinger MyCode initiative to discover cancer predisposition variants. The case-control association analysis was conducted by binning variants in 5,538 patients with cancer and 7,286 matched controls in a discovery set and 1,991 patients with cancer and 2,504 matched controls in a validation set across nine cancer types. Further, The Cancer Genome Atlas (TCGA) germline data were used to replicate the findings. RESULTS We identified 133 significant pathway-cancer pairs (85 replicated) and 90 significant gene-cancer pairs (12 replicated). In addition, we identified 18 genes and 3 pathways that were associated with survival outcome across cancers (Bonferroni P < 0.05). CONCLUSIONS In this study, we identified potential predisposition genes and pathways based on rare variants in nine cancers. IMPACT This work adds to the knowledge base and progress being made in precision medicine.
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Affiliation(s)
- Manu Shivakumar
- Biomedical & Translational Informatics Institute, Geisinger, Danville, Pennsylvania
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jason E Miller
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - David J Carey
- Department of Molecular and Functional Genomics, Geisinger, Danville, Pennsylvania
| | - Radhika Gogoi
- Weis Center for Research, Geisinger Clinic, Danville, Pennsylvania.
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39
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Tang H, He Z. Advances and challenges in quantitative delineation of the genetic architecture of complex traits. QUANTITATIVE BIOLOGY 2021; 9:168-184. [PMID: 35492964 PMCID: PMC9053444 DOI: 10.15302/j-qb-021-0249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Genome-wide association studies (GWAS) have been widely adopted in studies of human complex traits and diseases. Results This review surveys areas of active research: quantifying and partitioning trait heritability, fine mapping functional variants and integrative analysis, genetic risk prediction of phenotypes, and the analysis of sequencing studies that have identified millions of rare variants. Current challenges and opportunities are highlighted. Conclusion GWAS have fundamentally transformed the field of human complex trait genetics. Novel statistical and computational methods have expanded the scope of GWAS and have provided valuable insights on the genetic architecture underlying complex phenotypes.
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Affiliation(s)
- Hua Tang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA 94305, USA
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40
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Koganebuchi K, Sato K, Fujii K, Kumabe T, Haneji K, Toma T, Ishida H, Joh K, Soejima H, Mano S, Ogawa M, Oota H. An analysis of the demographic history of the risk allele R4810K in RNF213 of moyamoya disease. Ann Hum Genet 2021; 85:166-177. [PMID: 34013582 PMCID: PMC8453937 DOI: 10.1111/ahg.12424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/07/2021] [Accepted: 04/08/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Ring finger protein 213 (RNF213) is a susceptibility gene of moyamoya disease (MMD). A previous case-control study and a family analysis demonstrated a strong association of the East Asian-specific variant, R4810K (rs112735431), with MMD. Our aim is to uncover evolutionary history of R4810K in East Asian populations. METHODS The RNF213 locus of 24 MMD patients in Japan were sequenced using targeted-capture sequencing. Based on the sequence data, we conducted population genetic analysis and estimated the age of R4810K using coalescent simulation. RESULTS The diversity of the RNF213 gene was higher in Africans than non-Africans, which can be explained by bottleneck effect of the out-of-Africa migration. Coalescent simulation showed that the risk variant was born in East Asia 14,500-5100 years ago and came to the Japanese archipelago afterward, probably in the period when the known migration based on archaeological evidences occurred. CONCLUSIONS Although clinical data show that the symptoms varies, all sequences harboring the risk allele are almost identical with a small number of exceptions, suggesting the MMD phenotypes are unaffected by the variants of this gene and rather would be more affected by environmental factors.
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Affiliation(s)
- Kae Koganebuchi
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Faculty of Medicine, Advanced Medical Research Center, University of the Ryukyus, Nishihara, Okinawa, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo, Japan
| | - Kimitoshi Sato
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Kiyotaka Fujii
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Toshihiro Kumabe
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Kuniaki Haneji
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Takashi Toma
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Hajime Ishida
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Keiichiro Joh
- Division of Molecular Genetics and Epigenetics, Faculty of Medicine, Department of Biomolecular Sciences, Saga University, Saga, Saga, Japan
| | - Hidenobu Soejima
- Division of Molecular Genetics and Epigenetics, Faculty of Medicine, Department of Biomolecular Sciences, Saga University, Saga, Saga, Japan
| | - Shuhei Mano
- Department of Mathematical Analysis and Statistical Inference, The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan
| | - Motoyuki Ogawa
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Department of Anatomy, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Hiroki Oota
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Department of Anatomy, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo, Japan
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Darbeheshti F, Abolhassani H, Bashashati M, Ghavami S, Shahkarami S, Zoghi S, Gupta S, Orange JS, Ochs HD, Rezaei N. Coronavirus: Pure Infectious Disease or Genetic Predisposition. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1318:91-107. [PMID: 33973174 DOI: 10.1007/978-3-030-63761-3_6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes novel coronavirus disease (COVID-19), is the seventh pathogenic coronavirus recently discovered in December 2019 in Wuhan, China. To date, our knowledge about its effect on the human host remains limited. It is well known that host genetic factors account for the individual differences in the susceptibility to infectious diseases. The genetic susceptibility factors to COVID-19 and its severity are associated with several unanswered questions. However, the experience gained from an earlier strain of coronavirus, SARS-CoV-1, which shows 78% genetic similarity to SARS-CoV-2 and uses the same receptor to bind to host cells, could provide some clues. It, therefore, seems possible to assemble new evidence in order to solve a potential genetic predisposition puzzle for COVID-19. In this chapter, the puzzle pieces, including virus entry receptors, immune response, and inflammation-related genes, as well as the probable genetic predisposition models to COVID-19, are discussed.
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Affiliation(s)
- Farzaneh Darbeheshti
- Department of Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Medical Genetics Network (MeGeNe), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Hassan Abolhassani
- Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institute at Karolinska University Hospital Huddinge, Stockholm, Sweden
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
- Primary Immunodeficiency Diseases Network (PIDNet), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden
| | - Mohammad Bashashati
- Division of Gastroenterology, Department of Internal Medicine, Texas Tech University Health Sciences Center, El Paso, TX, USA
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), El Paso, TX, USA
| | - Saeid Ghavami
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Faculty of Medicine, Katowice School of Technology, Katowice, Poland
| | - Sepideh Shahkarami
- Medical Genetics Network (MeGeNe), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Gene center, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Samaneh Zoghi
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
- Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Vienna, Austria
| | - Sudhir Gupta
- Department of Medicine, Division of Basic and Clinical Immunology, University of California, Irvine, CA, USA
| | - Jordan S Orange
- Immunology, Allergy, and Rheumatology, Baylor College of Medicine and the Texas Children's Hospital, Houston, TX, USA
| | - Hans D Ochs
- School of Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Universal Scientific Education and Research Network (USERN), Seattle, WA, USA
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
- Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
- Children's Medical Center Hospital, Tehran, Iran.
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42
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The impact of rare and low-frequency genetic variants in common variable immunodeficiency (CVID). Sci Rep 2021; 11:8308. [PMID: 33859323 PMCID: PMC8050305 DOI: 10.1038/s41598-021-87898-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 04/01/2021] [Indexed: 02/07/2023] Open
Abstract
Next Generation Sequencing (NGS) has uncovered hundreds of common and rare genetic variants involved in complex and rare diseases including immune deficiencies in both an autosomal recessive and autosomal dominant pattern. These rare variants however, cannot be classified clinically, and common variants only marginally contribute to disease susceptibility. In this study, we evaluated the multi-gene panel results of Common Variable Immunodeficiency (CVID) patients and argue that rare variants located in different genes play a more prominent role in disease susceptibility and/or etiology. We performed NGS on DNA extracted from the peripheral blood leukocytes from 103 patients using a panel of 19 CVID-related genes: CARD11, CD19, CD81, ICOS, CTLA4, CXCR4, GATA2, CR2, IRF2BP2, MOGS, MS4A1, NFKB1, NFKB2, PLCG2, TNFRSF13B, TNFRSF13C, TNFSF12, TRNT1 and TTC37. Detected variants were evaluated and classified based on their impact, pathogenicity classification and population frequency as well as the frequency within our study group. NGS revealed 112 different (a total of 227) variants with under 10% population frequency in 103 patients of which 22(19.6%) were classified as benign, 29(25.9%) were classified as likely benign, 4(3.6%) were classified as likely pathogenic and 2(1.8%) were classified as pathogenic. Moreover, 55(49.1%) of the variants were classified as variants of uncertain significance. We also observed different variant frequencies when compared to population frequency databases. Case-control data is not sufficient to unravel the genetic etiology of immune deficiencies. Thus, it is important to understand the incidence of co-occurrence of two or more rare variants to aid in illuminating their potential roles in the pathogenesis of immune deficiencies.
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43
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Genetic Analysis Reveals Rare Variants in T-Cell Response Gene MR1 Associated with Poor Overall Survival after Urothelial Cancer Diagnosis. Cancers (Basel) 2021; 13:cancers13081864. [PMID: 33919687 PMCID: PMC8069815 DOI: 10.3390/cancers13081864] [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: 01/22/2021] [Revised: 04/06/2021] [Accepted: 04/08/2021] [Indexed: 11/16/2022] Open
Abstract
Urothelial carcinoma of the bladder (UC) is the fifth most common cancer in the United States. Germline variants, especially rare germline variants, may account for a portion of the disparity seen among patients in terms of UC incidence, presentation, and outcomes. The objectives of this study were to identify rare germline variant associations in UC incidence and to determine its association with clinical outcomes. Using exome sequencing data from the DiscovEHR UC cohort (n = 446), a European-ancestry, North American population, the complex influence of germline variants on known clinical phenotypes were analyzed using dispersion and burden metrics with regression tests. Outcomes measured were derived from the electronic health record (EHR) and included UC incidence, age at diagnosis, and overall survival (OS). Consequently, key rare variant association genes were implicated in MR1 and ADGRL2. The Kaplan-Meier survival analysis reveals that individuals with MR1 germline variants had significantly worse OS than those without any (log-rank p-value = 3.46 × 10-7). Those with ADGRL2 variants were found to be slightly more likely to have UC compared to a matched control cohort (FDR q-value = 0.116). These associations highlight several candidate genes that have the potential to explain clinical disparities in UC and predict UC outcomes.
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44
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Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits. Sci Rep 2021; 11:7431. [PMID: 33795796 PMCID: PMC8016937 DOI: 10.1038/s41598-021-86871-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 03/22/2021] [Indexed: 11/30/2022] Open
Abstract
After the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.
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45
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Pang H, Xia Y, Luo S, Huang G, Li X, Xie Z, Zhou Z. Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus. J Med Genet 2021; 58:289-296. [PMID: 33753534 PMCID: PMC8086251 DOI: 10.1136/jmedgenet-2020-107350] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 01/06/2021] [Accepted: 01/10/2021] [Indexed: 12/12/2022]
Abstract
Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%–85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.
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Affiliation(s)
- Haipeng Pang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Ying Xia
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Shuoming Luo
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Gan Huang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhiguo Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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46
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Long X, Xue H. Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability. Hum Genomics 2021; 15:19. [PMID: 33741065 PMCID: PMC7976700 DOI: 10.1186/s40246-021-00318-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 03/04/2021] [Indexed: 12/25/2022] Open
Abstract
Background Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. Methods Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. Results The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10−10), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. Conclusions In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00318-3.
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Affiliation(s)
- Xi Long
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China
| | - Hong Xue
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. .,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China. .,Centre for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
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47
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Pavard S, Coste CFD. Evolutionary demographic models reveal the strength of purifying selection on susceptibility alleles to late-onset diseases. Nat Ecol Evol 2021; 5:392-400. [PMID: 33398109 DOI: 10.1038/s41559-020-01355-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 10/22/2020] [Indexed: 01/28/2023]
Abstract
Assessing the role played by purifying selection on a susceptibility allele to late-onset disease (SALOD) is crucial to understanding the puzzling allelic spectrum of a disease, because most alleles are recent and rare. This fact is surprising because it suggests that alleles are under purifying selection while those that are involved in post-menopause mortality are often considered neutral in the genetic literature. The aim of this article is to use an evolutionary demography model to assess the magnitude of selection on SALODs while accounting for epidemiological and sociocultural factors. We develop an age-structured population model allowing for the calculation of SALOD selection coefficients (1) for a large and realistic parameter space for disease onset, (2) in a two-sex model in which men can reproduce in old age and (3) for situations in which child survival depends on maternal, paternal and grandmaternal care. The results show that SALODs are under purifying selection for most known age-at-onset distributions of late-onset genetic diseases. Estimates regarding various genes involved in susceptibility to cancer or Huntington's disease demonstrate that negative selection largely overcomes the effects of drift in most human populations. This is also probably true for neurodegenerative or polycystic kidney diseases, although sociocultural factors modulate the effect of selection in these cases. We conclude that neutrality is probably the exception among alleles that have a deleterious effect in old age and that accounting for sociocultural factors is required to understand the full extent of the force of selection shaping senescence in humans.
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Affiliation(s)
- Samuel Pavard
- Unité 7206 Eco-anthropologie, Muséum National d'Histoire Naturelle, CNRS, Université de Paris, Paris, France.
| | - Christophe F D Coste
- Unité 7206 Eco-anthropologie, Muséum National d'Histoire Naturelle, CNRS, Université de Paris, Paris, France.,Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway
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48
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Abstract
Alzheimer’s disease (AD) is the leading cause of neurodegeneration in the elderly and is clinically characterized by slowly progressing cognitive decline, which most commonly affects episodic memory function. This eventually leads to difficulties in activities of daily living. Biomarker studies show that the underlying pathology of AD begins 20 years before clinical symptoms. This results in the need to define specific targets and preclinical stages in order to address the problems of this disease at an earlier point in time. Genetic studies are indispensable for gaining insight into the etiology of neurodegenerative diseases and can play a major role in the early definition of the individual disease risk. This review provides an overview of the currently known genetic features of AD.
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Affiliation(s)
- Theresa König
- Department of Neurology, Medical University of Vienna, Vienna, Austria
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49
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Gualtieri CT. Genomic Variation, Evolvability, and the Paradox of Mental Illness. Front Psychiatry 2021; 11:593233. [PMID: 33551865 PMCID: PMC7859268 DOI: 10.3389/fpsyt.2020.593233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 11/27/2020] [Indexed: 12/30/2022] Open
Abstract
Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.
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50
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Laaksonen J, Mishra PP, Seppälä I, Lyytikäinen LP, Raitoharju E, Mononen N, Lepistö M, Almusa H, Ellonen P, Hutri-Kähönen N, Juonala M, Raitakari O, Kähönen M, Salonen JT, Lehtimäki T. Examining the effect of mitochondrial DNA variants on blood pressure in two Finnish cohorts. Sci Rep 2021; 11:611. [PMID: 33436758 PMCID: PMC7804469 DOI: 10.1038/s41598-020-79931-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 12/10/2020] [Indexed: 12/12/2022] Open
Abstract
High blood pressure (BP) is a major risk factor for many noncommunicable diseases. The effect of mitochondrial DNA single-nucleotide polymorphisms (mtSNPs) on BP is less known than that of nuclear SNPs. We investigated the mitochondrial genetic determinants of systolic, diastolic, and mean arterial BP. MtSNPs were determined from peripheral blood by sequencing or with genome-wide association study SNP arrays in two independent Finnish cohorts, the Young Finns Study and the Finnish Cardiovascular Study, respectively. In total, over 4200 individuals were included. The effects of individual common mtSNPs, with an additional focus on sex-specificity, and aggregates of rare mtSNPs grouped by mitochondrial genes were evaluated by meta-analysis of linear regression and a sequence kernel association test, respectively. We accounted for the predicted pathogenicity of the rare variants within protein-encoding and the tRNA regions. In the meta-analysis of 87 common mtSNPs, we did not observe significant associations with any of the BP traits. Sex-specific and rare-variant analyses did not pinpoint any significant associations either. Our results are in agreement with several previous studies suggesting that mtDNA variation does not have a significant role in the regulation of BP. Future studies might need to reconsider the mechanisms thought to link mtDNA with hypertension.
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Affiliation(s)
- Jaakko Laaksonen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland.
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
| | - Maija Lepistö
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Henrikki Almusa
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Nina Hutri-Kähönen
- Department of Paediatrics, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland.,Division of Medicine, Turku University Hospital, Turku, Finland.,Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,Research Centre for Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jukka T Salonen
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,MAS-Metabolic Analytical Services Oy, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, 33014, Tampere, Finland
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