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Integration between Genomic and Computational Statistical Surveys for the Screening of SNP Genetic Variants in Inflammatory Bowel Disease (IBD) Pediatric Patients*

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Computational Molecular Bioscience 2024年第3期14卷 146-191页

作者： Dago Dougba Noel Koffi N’Guessan Bénédicte Sonia Dagnogo Olefongo Daramcoum Wentoin Alimata Marie-Pierre Mauro Giacomelli Dagnogo Dramane Eboulé Ago Eliane Rebecca Yao Saraka Didier Martial Diarrassouba Nafan Giovanni Malerba Raffaele Badolato Department of Clinical and Experimental Sciences University of Brescia Brescia Italy Angelo Nocivelli Institute of Molecular Medicine Childrens Hospital ASST Spedali Civili Brescia Italy Unit of Biostatistics and Biomathematics & Unit of Bioinformatics Department of Molecular and Translational Medicine University of Brescia Brescia Italy Biological Sciences Training and Research Unit Department of Genetic and Biochemistry Peleforo Gon Coulibaly University Korhogo Cte dIvoire Department of Neurosciences Biomedicine and Movement Sciences Section of Biology and Genetics University of Verona Verona Italy Biosciences Training and Research Unit Biology and Health Laboratory Felix Houphouet-Boigny University Abidjan Cte dIvoire

Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the distribution dynamism of IBD pathogenic genetic variants (single nucleotide polymorphisms;SNPs) and risk factors in four (4) IBD pediatric patients, by integrating both clinical exome sequencing and computational statistical approaches, aiming to categorize IBD patients in CD and UC phenotype. To this end, we first aligned genomic read sequences of these IBD patients to hg19 human genome by using bowtie 2 package. Next, we performed genetic variant calling analysis in terms of single nucleotide polymorphism (SNP) for genes covered by at least 20 read genomic sequences. Finally, we checked for biological and genomic functions of genes exhibiting statistically significant genetic variant (SNPs) by introducing Fitcon genomic parameter. Findings showed Fitcon parameter as normalizing IBD patient’s population variability, as well as inducing a relative good clustering between IBD patients in terms of CD and UC phenotypes. Genomic analysis revealed a random distribution of risk factors and as well pathogenic SNPs genetic variants in the four IBD patient’s genome, claiming to be involved in: i) Metabolic disorders, ii) Autoimmune deficiencies;iii) Crohn’s disease pathways. Integration of genomic and computational statistical analysis supported a relative genetic variability regarding IBD patient population by processing IBD pathogenic SNP genetic variants as opposite to IBD risk factor variants. Interestingly, findings clearly allowed categorizing IBD patients in CD and UC phenotypes by applying Fitcon parameter in selecting IBD pathogenic genetic variants. Considering as a whole, the study suggested the efficiency of integrating clinical exome sequencing and computational statistical tools as a right approach in discriminating IBD phenotypes as well as improvi

关键词： Inflammatory Bowel Disease (IBD) Crohn Disease (CD) Ulcerative Colitis (UC) Clinical Exome Analysis Computational Statistic SNP Genetic Variants

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PROMIS-29 in rheumatoid arthritis patients who screen positive or negative for fibromyalgia on MDHAQ FAST4 (fibromyalgia assessment screening tool) or 2011 fibromyalgia criteria

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Seminars in Arthritis and Rheumatism 2024年 66卷 152361-152361页

作者： Gibson, Kathryn A. Kaplan, Robert M. Pincus, Theodore Li, Tengfei Luta, George Department of Rheumatology Liverpool Hospital Ingham Research Institute University of New South Wales Sydney 2170 NSW Australia Clinical Excellence Research Center Department of Medicine Stanford University School of Medicine Stanford 94305 CA United States Division of Rheumatology Department of Internal Medicine Rush University School of Medicine Chicago 60612 Ill United States Department of Biostatistics Bioinformatics & Biomathematics Georgetown University Washington 20057 DC United States Clinical Research Unit The Parker Institute Copenhagen University Hospital Frederiksberg DK-2000 Denmark

Background: PROMIS-29 T-scores query health-related quality of life (HRQL) in 7 domains, physical function, pain, fatigue, anxiety, depression, sleep quality, and social participation, to establish population norms. An MDHAQ (multidimensional health assessment questionnaire) scores these 7 domains and includes medical information such as a FAST4 (fibromyalgia assessment screening tool) index. We analyzed PROMIS-29 T-scores in rheumatoid arthritis (RA) patients vs population norms and for positive vs negative fibromyalgia (FM) screens and compared PROMIS-29 T-scores to MDHAQ scores to assess HRQL. Methods: A cross-sectional study was performed at one routine visit of 213 RA patients, who completed MDHAQ, PROMIS-29, and reference 2011 FM Criteria. PROMIS-29 T-scores were compared in RA vs population norms and in FM+ vs FM- RA patients, based on MDHAQ/FAST4 and reference criteria. Possible associations between PROMIS-29 T-scores and corresponding MDHAQ scores were analyzed using Spearman correlations and multiple regressions. Results: Median PROMIS-29 T-scores indicated clinically and statistically significantly poorer status in 26-29% FM+ vs FM- RA patients, with larger differences than in RA patients vs population norms for 6/7 domains. MDHAQ scores were correlated significantly with each of 7 corresponding PROMIS-29 domains (|rho|≥0.62, p<0.001). Linear regressions explained 55-73% of PROMIS-29 T-score variation by MDHAQ scores and 56%-70% of MDHAQ score variation by PROMIS-29 T-scores. Conclusions: Scores for 7 PROMIS-29 domains and MDHAQ were highly correlated. The MDHAQ is effective to assess HRQL and offers incremental medical information, including FAST4 screening. The results indicate the importance of assessing comorbidities such as fibromyalgia screening in interpreting PROMIS-29 T-scores. © 2024

关键词： clinical measurement FAST4 fibromyalgia MDHAQ patient questionnaires PROMIS-29 rheumatoid arthritis

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Microbial diversity investigation using 16S metagenomics in Tunisian patients with systemic lupus erythematosus

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Revista Argentina de Microbiologia 2025年

作者： Messadi, Amira Sayhi, Sameh Ghedira, Kais Zaouaoui, Chadia Arfaoui, Bilel Khouikhi, Soumaya Rebai, Maha Guediche, Nour El Houda Abdelhafidh, Nadia Louzir, Bassem Faida, Ajili Research Unit of Autoimmune Disease UR17DN02 Military Hospital of Tunis Tunis Tunisia Internal Medicine Department Military Hospital of Tunis Tunisia University Tunis EL Manar Tunis Tunisia Laboratory of Bioinformatics Biomathematics and Biostatistics LR20IPT09 Pasteur Institute of Tunis University of Tunis El Manar Tunis Tunisia Endocrinology Department Military Hospital of Tunis Tunis Tunisia LR Biotechnology and Bio-Geo Resources Valorization (LR11ES31) University of Manouba Tunisia

Systemic lupus erythematosus (SLE) is a multisystemic autoimmune disease associated with significant morbidity and mortality. It is characterized by a loss of self-immune tolerance and autoantibody production, leading to multiple organ damage. Emerging investigations have confirmed the role of gut microbiota dysbiosis in patients with SLE, although the underlying mechanisms remain unclear to date. In this study, we aim to investigate the bacterial profile of SLE including phylum/class/genus relative abundance and diversity, to compare them with healthy controls and to study the correlation of relative abundance of different patterns with clinical/biological parameters. In this case–control study, the bacterial profile was investigated in 7 SLE patients and 7 healthy controls using 16S metagenomics clustering. The present study reported a low abundance of the class Bacilli (0.58% in SLE vs 1.26% in the controls), the genus Lactobacillus (0.43% vs 0.74%), as well as a higher abundance of the genera Gammaproteobacteria (2.37% vs 0.77%) and Escherichia–Shigella (2.04% vs 0.51%) in SLE samples compared to the controls (p < 0.05). We also found an association between the class Betaproteobacteria (4.42% vs 1.57%) and the genus Faecalibacterium (11.34% vs 3.35%) and renal manifestations (p < 0.05). The phylum Actinobacteria (0.21% vs 3.8%, p = 0.036) and the genus Bifidobacterium levels were lower in active SLE compared to the healthy controls. This study is the first report on the gut microbiota of SLE and the first case–control study in Tunisia and North Africa. We obtained a particular profile of bacterial gut microbiota for the SLE group. We found a specific clustering when compared to the healthy controls. © 2025 The Author(s)

关键词： 16S metagenomics bioinformatics Case–control studies Microbiome diversity Systemic lupus erythematous

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FRI0361 Pregnancy outcomes and therapy in systemic lupus erythematosus: results from our 30 years' experience pregnancy clinic

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Annals of the Rheumatic Diseases 2018年 77卷 715-716页

作者： F. Crisafulli M.G. Lazzaroni L. Andreoli M.C. Gerardi L. Antolini G. Parma C. Benigno A. Lojacono S. Zatti V. Cappa S. Calza F. Franceschini A. Tincani U.O. Rheumatology and Clinical Immunology Spedali Civili and University of Brescia Brescia U.O. Rheumatology and Clinical Immunology Federico II University Hospital and University of Napoli Napoli Obstetrics and Gynecology Unit Biostatistics and Biomathematics Unit and Bioinformatics Unit Spedali Civili and University of Brescia Brescia Italy

Background The outcome of Systemic Lupus Erythematosus(SLE) pregnancies has dramatically improved thanks to pregnancy planning, multidisciplinary management and close monitoring during pregnancy. In our experience, programmed pregnancies in SLE patients had similar rates of pregnancy losses as compared to general obstetric population, but there are still open issues on some pregnancy complications that more frequently affect SLE patients. Objectives To analyse the obstetric outcome of SLE patients, according to specific therapy received during pregnancy. Methods A monocentric, retrospective study of 98 SLE patients with a total of 134 pregnancies followed prospectively by multidisciplinary team(1987–2015). Adverse Pregnancy Outcomes(APOs) were defined as one of the followings:premature miscarriage(<10 th week), intrauterine fetal death(>10 th week), perinatal death(<30 th day of life), severe preterm birth(<34 th week) and preterm birth(between 34th-36th weeks). We also evaluated the frequency of other pregnancy complications such as preterm premature rupture of membranes(pPROM) and pre-eclampsia(PE). Results Among the 134 pregnancies(including 3 twin pregnancies), flares occurred in 10 (7.5%) and APOs in 39 (29.1%) cases (table 1). pPROM complicated 9 pregnancies, all resulted in preterm deliveries, including 3 severe preterm birth; PE complicated 6 pregnancies resulting in 2 preterm birth, 1 intrauterine fetal death, 1 perinatal death and 2 term birth. The rates of APOs, pPROM and PE were compared according to receiving or not a specific therapy: hydroxychloroquine(HCQ), low dose aspirin(LDA), immunosuppressant(IS) during the overall pregnancy and corticosteroids>35 mg/week(CS) during the 1 st, the 2nd and the 3rd trimester. No statistical significant association was found between a specific therapy and the rate of PE. HCQ and LDA did not significantly affected the rate of APOs or pPROM while pregnancies exposed to IS showed a higher frequency of APOs(47% vs 20%,

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Correction: Impact of nutritional status on heart failure mortality: a retrospective cohort study

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Nutrition journal 2022年第1期21卷 61页

作者： Nafz Abdoul Carime Jonathan Cottenet Guillaume Clerfond Romain Eschalier Didier Quilliot JeanChristophe Eicher Bertrand Joly Catherine Quantin Biostatistics and Bioinformatics department (DIM) Dijon University Hospital Dijon France University of Bourgogne Franche-Comté Dijon France. Cardiology Department CHU Clermont-Ferrand Clermont-Ferrand France and Université Clermont Auvergne CHU Clermont-Ferrand CNRS SIGMA Clermont Institut Pascal F-63000 Clermont-Ferrand France and F-CRIN INI-CRCT Nancy France. Department of Gastroenterology and Inserm NGERE U1256 University Hospital of Nancy University of Lorraine 1 Allée du Morvan 54511 Vandoeuvre-lès-Nancy France Nutritional Assistance Department University Hospital of Nancy University of Lorraine Vandoeuvre‑lès‑Nancy France. Cardiology Department University Hospital of Dijon Dijon France. CHPCB Paray-le-Monial General Hospital Paray‑le‑Monial France. University of Bourgogne Franche-Comté Dijon France. catherine.quantin@chu-dijon.f. Inserm CIC 1432 Dijon France Dijon University Hospital Clinical Investigation Center clinical epidemiology/ clinical trials unit Dijon France. catherine.quantin@chu-dijon.f. Biostatistics Biomathematics Pharmacoepidemiology and Infectious Diseases (B2PHI) INSERM UVSQ Institut Pasteur Université Paris-Saclay Paris France. catherine.quantin@chu-dijon.f.

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Author Correction: Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics

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Scientific reports 2020年第1期10卷 1827页

作者： Audrey Duval Thomas Obadia Lucie Martinet Pierre-Yves Boëlle Eric Fleury Didier Guillemot Lulla Opatowski Laura Temime Biostatistics Biomathematics Pharmacoepidemiology and Infectious Diseases (B2PHI) Inserm UVSQ Institut Pasteur Université Paris-Saclay Paris France. Institut Pasteur - Bioinformatics and Biostatistics Hub - C3BI USR 3756 IP CNRS Paris France. Malaria Parasites & Hosts Unit Department of Parasites & Insect Vectors Institut Pasteur Paris France. ENS de Lyon DANTE/INRIA LIP UMR CNRS 5668 Université de Lyon Lyon France. Sorbonne Universités UPMC Univ Paris 06 UMR_S 1136 Institut Pierre Louis d'Epidémiologie et de Santé Publique Paris France. ENS de Lyon Université de Lyon Laboratoire de l'Informatique du Parallélisme (UMR CNRS 5668- ENS de Lyon-UCB Lyon 1) IXXI Rhône Alpes Complex Systems Institute Lyon France. INSERM 1181 Biostatistics Biomathematics Pharmacoepidemiology and Infectious Diseases (B2PHI) Institut Pasteur B2PHI Paris France. Université de Versailles Saint-Quentin UMR 1181 B2PHI Montigny-Le-Bretonneux France. AP-HP Raymond-Poincaré Hospital Garche France. Biostatistics Biomathematics Pharmacoepidemiology and Infectious Diseases (B2PHI) Inserm UVSQ Institut Pasteur Université Paris-Saclay Paris France. lulla.opatowski@pasteur.fr. Laboratoire MESuRS Conservatoire national des Arts et Métiers Paris France. Unité PACRI Institut Pasteur Conservatoire national des Arts et Métiers Paris France.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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High-depth African genomes inform human migration and health (vol 586, pg 741, 2020)

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NATURE 2021年第7856期592卷 E26-E26页

作者： Choudhury, Ananyo Aron, Shaun Botigue, Laura R. Sengupta, Dhriti Botha, Gerrit Bensellak, Taoufik Wells, Gordon Kumuthini, Judit Shriner, Daniel Fakim, Yasmina J. Ghoorah, Anisah W. Dareng, Eileen Odia, Trust Falola, Oluwadamilare Adebiyi, Ezekiel Hazelhurst, Scott Mazandu, Gaston Nyangiri, Oscar A. Mbiyavanga, Mamana Benkahla, Alia Kassim, Samar K. Mulder, Nicola Adebamowo, Sally N. Chimusa, Emile R. Muzny, Donna Metcalf, Ginger Gibbs, Richard A. Matovu, Enock Bucheton, Bruno Hertz-Fowler, Christiane Koffi, Mathurin Macleod, Annette Mumba-Ngoyi, Dieudonne Noyes, Harry Nyangiri, Oscar A. Simo, Gustave Simuunza, Martin Rotimi, Charles Ramsay, Michele Choudhury, Ananyo Choudhury, Ananyo Aron, Shaun Botigue, Laura Sengupta, Dhriti Botha, Gerrit Bensellak, Taoufik Wells, Gordon Kumuthini, Judit Shriner, Daniel Fakim, Yasmina J. Ghoorah, Anisah W. Dareng, Eileen Odia, Trust Falola, Oluwadamilare Adebiyi, Ezekiel Hazelhurst, Scott Mazandu, Gaston Nyangiri, Oscar A. Mbiyavanga, Mamana Benkahla, Alia Kassim, Samar K. Mulder, Nicola Adebamowo, Sally N. Chimusa, Emile R. Rotimi, Charles Ramsay, Michele Adeyemo, Adebowale A. Lombard, Zane Hanchard, Neil A. Adebamowo, Clement Agongo, Godfred Boua, Romuald P. Oduro, Abraham Sorgho, Hermann Landoure, Guida Cisse, Lassana Diarra, Salimata Samassekou, Oumar Anabwani, Gabriel Matshaba, Mogomotsi Joloba, Moses Kekitiinwa, Adeodata Mardon, Graeme Mpoloka, Sununguko W. Kyobe, Samuel Mlotshwa, Busisiwe Mwesigwa, Savannah Retshabile, Gaone Williams, Lesedi Wonkam, Ambroise Moussa, Ahmed Adu, Dwomoa Ojo, Akinlolu Burke, David Salako, Babatunde O. Matovu, Enock Bucheton, Bruno Hertz-Fowler, Christiane Koffi, Mathurin Macleod, Annette Mumba-Ngoyi, Dieudonne Noyes, Harry Nyangiri, Oscar A. Simo, Gustave Simuunza, Martin Awadalla, Philip Bruat, Vanessa Gbeha, Elias Adeyemo, Adebowale A. Lombard, Zane Hanchard, Neil A. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa School of Electrical and Information Engineering University of the Witwatersrand Johannesburg South Africa Division of Human Genetics National Health Laboratory Service and School of Pathology Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa Navrongo Health Research Centre Navrongo Ghana Clinical Research Unit of Nanoro Institut de Recherche en Sciences de la Sante Bobo-Dioulasso Burkina Faso Center for Research in Agricultural Genomics (CRAG) Plant and Animal Genomics Program CSIC-IRTA-UAB-UB Barcelona Spain Computational Biology Division and H3ABioNet Department of Integrative Biomedical Sciences IDM University of Cape Town Cape Town South Africa System and Data Engineering Team Abdelmalek Essaadi University ENSA Tangier Morocco Centre for Proteomic and Genomic Research (CPGR) Cape Town South Africa South African National Bioinformatics Institute University of the Western Cape Bellville South Africa Africa Health Research Institute Durban South Africa Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA Department of Agriculture and Food Science Faculty of Agriculture University of Mauritius Reduit Mauritius Department of Digital Technologies Faculty of Information Communication & Digital Technologies University of Mauritius Reduit Mauritius Department of Public Health and Primary Care University of Cambridge Cambridge UK Institute of Human Virology Nigeria Abuja Nigeria Department of Epidemiology and Public Health University of Maryland School of Medicine University of Maryland Baltimore Baltimore MD USA University of Maryland Greenebaum Comprehensive Cancer Center University of Maryland School of Medicine University of Maryland Baltimore Baltimore MD USA Institute of Human Virology and Greeneba

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Genomic research data generation, analysis and sharing – challenges in the African setting

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Data Science Journal 2017年 16卷

作者： Mulder, Nicola Adebamowo, Clement A. Adebamowo, Sally N. Adebayo, Oladimeji Adeleye, Osimhiarherhuo Alibi, Mohamed Baichoo, Shakuntala Benkahla, Alia Fadlelmola, Faisal M. Ghazal, Hassan Ghedira, Kais Matimba, Alice Moussa, Ahmed Mungloo-Dilmohamud, Zahra Owolabi, Mayowa O. Radouani, Fouzia Rotimi, Charles N. Stein, Dan J. Souiai, Oussama Computational Biology Division Department of Integrative Biomedical Sciences Institute for Infectious Disease and Molecular Medicine University of Cape Town South Africa Department of Epidemiology and Public Health University of Maryland Greenebaum Comprehensive Cancer Center University of Maryland School of Medicine BaltimoreMD21201 United States Department of Medicine University College Hospital Ibadan Nigeria Federal Medical Centre Abeokuta Nigeria Université Tunis El Manar Institut Pasteur de Tunis Laboratory of BioInformatics BioMathematics and BioStatistics Tunisia University of Mauritius Mauritius Centre for Bioinformatics and Systems Biology Faculty of Science University of Khartoum Sudan Future University of Sudan Sudan Laboratory of Physiology and Genetics University Mohamed Premier Morocco Department of Clinical Pharmacology University of Zimbabwe Harare Zimbabwe SDET ENSAT Abdelmalek Essaadi University Morocco Institut Pasteur du Maroc Casablanca Morocco Morocco Center for Research on Genomics and Global Health National Human Genome Research Institute NIH BethesdaMD20892 United States Department of Psychiatry University of Cape Town MRC Unit on Risk and Resilience in Mental Disorders South Africa

Genomics is the study of the genetic material that constitutes the genomes of organisms. This genetic material can be sequenced and it provides a powerful tool for the study of human, plant and animal evolutionary history and diseases. Genomics research is becoming increasingly commonplace due to significant advances in and reducing costs of technologies such as sequencing. This has led to new challenges including increasing cost and complexity of data. There is, therefore, an increasing need for computing infrastructure and skills to manage, store, analyze and interpret the data. In addition, there is a significant cost associated with recruitment of participants and collection and processing of biological samples, particularly for large human genetics studies on specific diseases. As a result, researchers are often reluctant to share the data due to the effort and associated cost. In Africa, where researchers are most commonly at the study recruitment, determination of phenotypes and collection of biological samples end of the genomic research spectrum, rather than the generation of genomic data, data sharing without adequate safeguards for the interests of the primary data generators is a concern. There are substantial ethical considerations in the sharing of human genomics data. The broad consent for data sharing preferred by genomics researchers and funders does not necessarily align with the expectations of researchers, research participants, legal authorities and bioethicists. In Africa, this is complicated by concerns about comprehension of genomics research studies, quality of research ethics reviews and understanding of the implications of broad consent, secondary analyses of shared data, return of results and incidental findings. Additional challenges with genomics research in Africa include the inability to transfer, store, process and analyze large-scale genomics data on the continent, because this requires highly specialized skills and expensive comput

关键词： Genome

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1^st Conference Clinical Trials on Alzheimer's Disease September 17-18-19, 2008 School of Medecine Montpellier, France Abstracts

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JOURNAL OF NUTRITION HEALTH & AGING 2008年第8期12卷 531-543页

作者： [Anonymous] CNRS Institut de Génétique Humaine UPR 1142 Montpellier France Service de Neurologie CHU Gui de Chauliac Montpellier France Innogenetics NV Gent Belgium Laboratoire de Biochimie CHU Saint Eloi Montpellier France Faculté de Médecine Montpellier France Department of Neurology and Memory Clinic Middelheim General Hospital And Institute Born-Bunge University of Antwerp Belgium Department of Pathology and Laboratory Medicine Institute on Aging Alzheimer’s Disease Center Center For Neurodegenerative Disease Research University of Pennsylvania School of Medicine Philadelphia USA Centre for Functional and Metabolic Mapping Robarts Research Institute London Canada The Department Medicine Canada The Department Diagnostic Radiology and Nuclear Medicine Canada The Department Psychiatry University of Western Ontario London Canada Neuropsychiatric Clinic Malmö University Hospital Sweden Division of Aging Rehabilitation and Geriatric Care Lawson Health Research Institute London Canada Innogenetics Gent Belgium University of Erlangen-Nuremberg Erlangen Germany Memory Clinic Department of Psychiatry University Clinic Leipzig Department of Psychiatry Universitätsklinikum Erlangen Sweden Kliniken/Institut der Universität Duisburg-Essen Essen Germany Sahlgrenska University Hospital Göteborg University Sweden New York State Institute for Basic Research in Developmental Disabilities Staten Island USA James J. Peters VA Medical Center Bronx USA Brookdale Department of Geriatrics Mount Sinai School of Medicine New York USA Elan Pharmaceuticals Inc. South San Francisco USA Cognitive Neuroscience Division of the Taub Institute for Research in Alzheimer’s Disease and the Aging Brain USA Gertrude H. Sergievsky Center and the Department of Neurology Columbia University Medical Center New York USA Department of Psychiatry and Behavioral Sciences Johns Hopkins University Baltimore USA Department of Psychiatry Massachusetts General Hospital Harvard Medical School Boston USA D

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