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Rege NK, Liu M, Yang Y, Dhayalan B, Wickramasinghe NP, Chen YS, Rahimi L, Guo H, Haataja L, Sun J, Ismail-Beigi F, Phillips NB, Arvan P, Weiss MA. Evolution of insulin at the edge of foldability and its medical implications. Proc Natl Acad Sci U S A 2020; 117:29618-29628. [PMID: 33154160 PMCID: PMC7703552 DOI: 10.1073/pnas.2010908117] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Proteins have evolved to be foldable, and yet determinants of foldability may be inapparent once the native state is reached. Insight has emerged from studies of diseases of protein misfolding, exemplified by monogenic diabetes mellitus due to mutations in proinsulin leading to endoplasmic reticulum stress and β-cell death. Cellular foldability of human proinsulin requires an invariant Phe within a conserved crevice at the receptor-binding surface (position B24). Any substitution, even related aromatic residue TyrB24, impairs insulin biosynthesis and secretion. As a seeming paradox, a monomeric TyrB24 insulin analog exhibits a native-like structure in solution with only a modest decrement in stability. Packing of TyrB24 is similar to that of PheB24, adjoining core cystine B19-A20 to seal the core; the analog also exhibits native self-assembly. Although affinity for the insulin receptor is decreased ∼20-fold, biological activities in cells and rats were within the range of natural variation. Together, our findings suggest that the invariance of PheB24 among vertebrate insulins and insulin-like growth factors reflects an essential role in enabling efficient protein folding, trafficking, and secretion, a function that is inapparent in native structures. In particular, we envision that the para-hydroxyl group of TyrB24 hinders pairing of cystine B19-A20 in an obligatory on-pathway folding intermediate. The absence of genetic variation at B24 and other conserved sites near this disulfide bridge-excluded due to β-cell dysfunction-suggests that insulin has evolved to the edge of foldability. Nonrobustness of a protein's fitness landscape underlies both a rare monogenic syndrome and "diabesity" as a pandemic disease of civilization.
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Affiliation(s)
- Nischay K Rege
- Department of Biochemistry, Case Western Reserve University, Cleveland, OH 44106
| | - Ming Liu
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, 300052 Tianjin, China
- Division of Metabolism, Endocrinology & Diabetes, University of Michigan Medical School, Ann Arbor, MI 48105
| | - Yanwu Yang
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
| | - Balamurugan Dhayalan
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
| | | | - Yen-Shan Chen
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
| | - Leili Rahimi
- Department of Biochemistry, Case Western Reserve University, Cleveland, OH 44106
- Department of Medicine, Case Western Reserve University, Cleveland, OH 44106
| | - Huan Guo
- Division of Metabolism, Endocrinology & Diabetes, University of Michigan Medical School, Ann Arbor, MI 48105
| | - Leena Haataja
- Division of Metabolism, Endocrinology & Diabetes, University of Michigan Medical School, Ann Arbor, MI 48105
| | - Jinhong Sun
- Division of Metabolism, Endocrinology & Diabetes, University of Michigan Medical School, Ann Arbor, MI 48105
| | - Faramarz Ismail-Beigi
- Department of Biochemistry, Case Western Reserve University, Cleveland, OH 44106
- Department of Medicine, Case Western Reserve University, Cleveland, OH 44106
- Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, OH 44106
| | - Nelson B Phillips
- Department of Biochemistry, Case Western Reserve University, Cleveland, OH 44106
| | - Peter Arvan
- Division of Metabolism, Endocrinology & Diabetes, University of Michigan Medical School, Ann Arbor, MI 48105
| | - Michael A Weiss
- Department of Biochemistry, Case Western Reserve University, Cleveland, OH 44106;
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
- Department of Medicine, Case Western Reserve University, Cleveland, OH 44106
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Kulminski AM, Loika Y, Nazarian A, Culminskaya I. Quantitative and Qualitative Role of Antagonistic Heterogeneity in Genetics of Blood Lipids. J Gerontol A Biol Sci Med Sci 2020; 75:1811-1819. [PMID: 31566214 DOI: 10.1093/gerona/glz225] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Indexed: 12/18/2022] Open
Abstract
Prevailing strategies in genome-wide association studies (GWAS) mostly rely on principles of medical genetics emphasizing one gene, one function, one phenotype concept. Here, we performed GWAS of blood lipids leveraging a new systemic concept emphasizing complexity of genetic predisposition to such phenotypes. We focused on total cholesterol, low- and high-density lipoprotein cholesterols, and triglycerides available for 29,902 individuals of European ancestry from seven independent studies, men and women combined. To implement the new concept, we leveraged the inherent heterogeneity in genetic predisposition to such complex phenotypes and emphasized a new counter intuitive phenomenon of antagonistic genetic heterogeneity, which is characterized by misalignment of the directions of genetic effects and the phenotype correlation. This analysis identified 37 loci associated with blood lipids but only one locus, FBXO33, was not reported in previous top GWAS. We, however, found strong effect of antagonistic heterogeneity that leaded to profound (quantitative and qualitative) changes in the associations with blood lipids in most, 25 of 37 or 68%, loci. These changes suggested new roles for some genes, which functions were considered as well established such as GCKR, SIK3 (APOA1 locus), LIPC, LIPG, among the others. The antagonistic heterogeneity highlighted a new class of genetic associations emphasizing beneficial and adverse trade-offs in predisposition to lipids. Our results argue that rigorous analyses dissecting heterogeneity in genetic predisposition to complex traits such as lipids beyond those implemented in current GWAS are required to facilitate translation of genetic discoveries into health care.
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Affiliation(s)
- Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Alireza Nazarian
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina
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Evolutionary framework of the human interactome: Unicellular and multicellular giant clusters. Biosystems 2019; 181:82-87. [PMID: 31077747 DOI: 10.1016/j.biosystems.2019.05.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 04/06/2019] [Accepted: 05/07/2019] [Indexed: 02/06/2023]
Abstract
The main contradiction of multicellularity (MCM) is between the unicellular (UC) and multicellular (MC) levels. In human interactome we revealed two giant clusters with MC and UC medians (and several smaller ones with MC medians). The enrichment of these clusters by phylostrata and by functions support the MC versus UC division. The total interactome and the giant clusters show a core-periphery evolutionary growth. From viewpoint of the MCM, the most important is the placement of genes, appearing at UC evolutionary stage, in the MC clusters. Thus, genes involved in vesicle-mediated transport, cell cycle, cellular responses to stress, post-translational modifications and many diseases appeared at UC evolutionary stage but are placed mostly in MC clusters. Genes downregulated with age are enriched in UC cluster, whereas the upregulated genes are preferentially placed in MC giant cluster. The tumor suppressor and pluripotency regulating pathways are also enriched in MC giant cluster. Therefore, this cluster probably operates as 'internal manager' constraining runaway unicellularity. The clusters have denser interactions within than between them, therefore they can serve as attractors (stable states of dynamic systems) of cellular programs. Importantly, the UC cluster have a higher inside/outside connection ratio compared with MC clusters, which suggests a stronger attractor effect and may explain why cells of MC organisms are prone to oncogenesis. The evolutionary clustering of human interactome elucidates the MC control over functions appearing at UC evolutionary stage and can build a framework for biosystems studies focusing on the interplay between UC and MC levels.
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A systematic review of the Trypanosoma cruzi genetic heterogeneity, host immune response and genetic factors as plausible drivers of chronic chagasic cardiomyopathy. Parasitology 2018; 146:269-283. [PMID: 30210012 DOI: 10.1017/s0031182018001506] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Chagas disease is a complex tropical pathology caused by the kinetoplastid Trypanosoma cruzi. This parasite displays massive genetic diversity and has been classified by international consensus in at least six Discrete Typing Units (DTUs) that are broadly distributed in the American continent. The main clinical manifestation of the disease is the chronic chagasic cardiomyopathy (CCC) that is lethal in the infected individuals. However, one intriguing feature is that only 30-40% of the infected individuals will develop CCC. Some authors have suggested that the immune response, host genetic factors, virulence factors and even the massive genetic heterogeneity of T. cruzi are responsible of this clinical pattern. To date, no conclusive data support the reason why a few percentages of the infected individuals will develop CCC. Therefore, we decided to conduct a systematic review analysing the host genetic factors, immune response, cytokine production, virulence factors and the plausible association of the parasite DTUs and CCC. The epidemiological and clinical implications are herein discussed.
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Marigorta UM, Rodríguez JA, Gibson G, Navarro A. Replicability and Prediction: Lessons and Challenges from GWAS. Trends Genet 2018; 34:504-517. [PMID: 29716745 PMCID: PMC6003860 DOI: 10.1016/j.tig.2018.03.005] [Citation(s) in RCA: 99] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 03/12/2018] [Accepted: 03/26/2018] [Indexed: 12/29/2022]
Abstract
Since the publication of the Wellcome Trust Case Control Consortium (WTCCC) landmark study a decade ago, genome-wide association studies (GWAS) have led to the discovery of thousands of risk variants involved in disease etiology. This success story has two angles that are often overlooked. First, GWAS findings are highly replicable. This is an unprecedented phenomenon in complex trait genetics, and indeed in many areas of science, which in past decades have been plagued by false positives. At a time of increasing concerns about the lack of reproducibility, we examine the biological and methodological reasons that account for the replicability of GWAS and identify the challenges ahead. In contrast to the exemplary success of disease gene discovery, at present GWAS findings are not useful for predicting phenotypes. We close with an overview of the prospects for individualized prediction of disease risk and its foreseeable impact in clinical practice.
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Affiliation(s)
- Urko M Marigorta
- Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, USA; These authors contributed equally
| | - Juan Antonio Rodríguez
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Catalonia, Spain; Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; These authors contributed equally. https://twitter.com/jrotwitguez
| | - Greg Gibson
- Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Arcadi Navarro
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Catalonia, Spain; Institute of Evolutionary Biology (UPF-CSIC), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain; National Institute for Bioinformatics (INB), Barcelona, Catalonia, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), PRBB, Barcelona, Catalonia, Spain.
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Szpak M, Mezzavilla M, Ayub Q, Chen Y, Xue Y, Tyler-Smith C. FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations. Genome Biol 2018; 19:5. [PMID: 29343290 PMCID: PMC5771147 DOI: 10.1186/s13059-017-1380-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 12/12/2017] [Indexed: 12/30/2022] Open
Abstract
We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.
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Affiliation(s)
- Michał Szpak
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Massimo Mezzavilla
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
- Division of Experimental Genetics, Sidra Medical and Research Center, Doha, Qatar
| | - Qasim Ayub
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
- Present Address: Genomics Facility, School of Science, Monash University Malaysia, Bandar Sunway, Selangor, Darul Ehsan Malaysia
| | - Yuan Chen
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Yali Xue
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Chris Tyler-Smith
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
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Spataro N, Rodríguez JA, Navarro A, Bosch E. Properties of human disease genes and the role of genes linked to Mendelian disorders in complex disease aetiology. Hum Mol Genet 2017; 26:489-500. [PMID: 28053046 PMCID: PMC5409085 DOI: 10.1093/hmg/ddw405] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 11/10/2016] [Accepted: 11/23/2016] [Indexed: 01/19/2023] Open
Abstract
Do genes presenting variation that has been linked to human disease have different biological properties than genes that have never been related to disease? What is the relationship between disease and fitness? Are the evolutionary pressures that affect genes linked to Mendelian diseases the same to those acting on genes whose variation contributes to complex disorders? The answers to these questions could shed light on the architecture of human genetic disorders and may have relevant implications when designing mapping strategies in future genetic studies. Here we show that, relative to non-disease genes, human disease (HD) genes have specific evolutionary profiles and protein network properties. Additionally, our results indicate that the mutation-selection balance renders an insufficient account of the evolutionary history of some HD genes and that adaptive selection could also contribute to shape their genetic architecture. Notably, several biological features of HD genes depend on the type of pathology (complex or Mendelian) with which they are related. For example, genes harbouring both causal variants for Mendelian disorders and risk factors for complex disease traits (Complex-Mendelian genes), tend to present higher functional relevance in the protein network and higher expression levels than genes associated only with complex disorders. Moreover, risk variants in Complex-Mendelian genes tend to present higher odds ratios than those on genes associated with the same complex disorders but with no link to Mendelian diseases. Taken together, our results suggest that genetic variation at genes linked to Mendelian disorders plays an important role in driving susceptibility to complex disease.
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Affiliation(s)
- Nino Spataro
- Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Antonio Rodríguez
- Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Arcadi Navarro
- Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- National Institute for Bioinformatics (INB), Barcelona Biomedical Research Park (PRBB), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona Biomedical Research Park (PRBB), Barcelona, Spain
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona Biomedical Research Park (PRBB), Barcelona, Spain
| | - Elena Bosch
- Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
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Simonti CN, Capra JA. The evolution of the human genome. Curr Opin Genet Dev 2015; 35:9-15. [PMID: 26338498 DOI: 10.1016/j.gde.2015.08.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/08/2015] [Accepted: 08/12/2015] [Indexed: 02/05/2023]
Abstract
Human genomes hold a record of the evolutionary forces that have shaped our species. Advances in DNA sequencing, functional genomics, and population genetic modeling have deepened our understanding of human demographic history, natural selection, and many other long-studied topics. These advances have also revealed many previously underappreciated factors that influence the evolution of the human genome, including functional modifications to DNA and histones, conserved 3D topological chromatin domains, structural variation, and heterogeneous mutation patterns along the genome. Using evolutionary theory as a lens to study these phenomena will lead to significant breakthroughs in understanding what makes us human and why we get sick.
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Affiliation(s)
- Corinne N Simonti
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - John A Capra
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235, USA.
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