Literature DB >> 33170170

Genetic analysis of intellectual disability and autism.

Pietro Chiurazzi1, Aysha Karim Kiani2, Jan Miertus3, Stefano Paolacci4, Shila Barati5, Elena Manara6, Liborio Stuppia7, Fiorella Gurrieri8, Matteo Bertelli9.   

Abstract

BACKGROUND AND AIM: Intellectual disability (ID) and autism spectrum disorders (ASD) are neurodevelopmental conditions that often co-exist and affect children from birth, impacting on their cognition and adaptive behaviour. Social interaction and communication ability are also severely impaired in ASD. Almost 1-3% of the population is affected and it has been estimated that approximately 30% of intellectual disability and autism is caused by genetic factors. The aim of this review is to summarize monogenic conditions characterized by intellectual disability and/or autism for which the causative genes have been identified. METHODS AND
RESULTS: We identified monogenic ID/ASD conditions through PubMed and other NCBI databases. Many such genes are located on the X chromosome (>150 out of 900 X-linked protein-coding genes), but at least 2000 human genes are estimated to be involved in ID/ASD. We selected 174 genes (64 X-linked and 110 autosomal) for an NGS panel in order to screen patients with ID and/or ASD, after fragile X syndrome and significant Copy Number Variants have been excluded.
CONCLUSIONS: Accurate clinical and genetic diagnosis is required for precise treatment of these disorders, but due to their genetic heterogeneity, most cases remain undiagnosed. Next generation sequencing technologies have greatly enhanced the identification of new genes associated with intellectual disability and autism, ultimately leading to the development of better treatment options.

Entities:  

Year:  2020        PMID: 33170170      PMCID: PMC8023126          DOI: 10.23750/abm.v91i13-S.10684

Source DB:  PubMed          Journal:  Acta Biomed        ISSN: 0392-4203


Intellectual Disability (ID) and Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that derive from an altered function of our brain (1). Their clinical manifestations overlap just as much as their etiology. In fact, the development of a functional brain depends on a complex sequence of events that include neuronal and glial cell proliferation and migration, neuronal maturation and survival, efficient connectivity at both the axonal as well as the synaptic level. Thousands of genes encode the many proteins that are needed for an efficient brain function, therefore next-generation sequencing greatly facilitates the identification of genetic determinants of ID and ASD (2).

Intellectual Disability

Intellectual disability (ID), previously known as “mental retardation” (3), represents a major public health concern. It is characterized by a congenital deficit in intellectual function and adaptive behaviour, impacting on social interactions as well as on mental and practical abilities of affected individuals. ID may be “isolated” or “syndromic” when patients have a peculiar facies, specific physical signs and/or an abnormal growth pattern. Many genetic and environmental factors, may cause intellectual disability (1). Common (but potentially preventable) causes of ID are iodine deficiency and malnutrition, affecting millions of people worldwide. Prenatal infections or maternal exposure to toxic substances (including alcohol, nicotine and several teratogenic drugs) as well as premature birth and perinatal asphyxia, may result in mild to severe ID in the child. The frequency of these “external” factors varies greatly among different countries and depends on (maternal) lifestyle and quality of health care, both indirectly influenced by socio-economic conditions. Genetic factors causing and/or contributing to ID (from chromosomal imbalances to monogenic syndromes) are less variable in frequency and increase with parental age (chromosomal non-disjunctions increase with maternal age while dominant de novo point mutations increase with paternal age). The reported prevalence of ID in children in the United States was 1.1-1.2% between 2014 and 2016 (4). In 2016, Chiurazzi and Pirozzi (1) listed 818 human genes associated with ID by searching the OMIM database (Table S1 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip); now we retrieved 1356 human genes from the OMIM database whose entries contain one of the following keywords: “intellectual disability”, “mental retardation”, “cognitive impairment” or “developmental delay” (Table S2 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip). Another valuable source of ID genes is provided by the SysID database (5), which also provides a useful distinction of the clinical phenotypes, based on disease severity and complexity (“sindromicity”): SysID presently lists 2588 human genes that can be easily accessed at https://sysid.cmbi.umcn.nl/ (Table S3 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip). Many of these genes have been found mutated in just one family and therefore their causative role should still be proven either by finding new unrelated patients with pathogenic variants or by functional studies (6). A note on the clinical phenotype should be made: broadly speaking ID is “isolated” or “pure” when the causative gene is expressed only in the brain while “ID syndromes” are either due to variants in a ubiquitously expressed gene that affect several tissues or to microdeletions/duplications (Copy Number Variants) involving contiguous genes (1). For instance the FMR1 gene is widely expressed in all tissues whereas the expression of SYNGAP1 is restricted to the brain: in fact absence of the FMR1 protein cause fragile X syndrome (7) while variants in SYNGAP1 and SHANK3, encoding synaptic proteins, are associated with non-syndromic intellectual disability (8).

Autism Spectrum Disorders

Children with intellectual disability have a significantly higher risk of autistic behaviour, stereotyped movements, neuromuscular deficits and epilepsy that affect their daily life and well-being. Autism Spectrum Disorder (ASD), just as ID, is a broad clinical definition including neurodevelopmental conditions characterized by deficient social interactions, poor or absent communication, repetitive behaviours and apparently limited interests (9). ASD generally becomes apparent after the first year of life and it has been reported in an increasing number (2.2-2.7%) of children between 2014 and 2016 in the United States (4). ASD, but not ID, in a child has also an important effect on parental emotional and mental health (10). The Simons Foundation Autism Research Initiative aims at identifying the genetic determinants of ASD and its database (https://gene.sfari.org/database/human-gene/) now lists 960 different genes ((Table S4 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip)), many of which are also responsible for ID. In fact, autism often coexists with intellectual disability, with 70% of ASD patients suffering also from ID whereas 40% of ID patients have ASD. The extended phenotypic overlap between ID and ASD is not surprising since they both derive from a more or less subtle alteration of brain functions and pathogenic variants in hundreds of genes expressed in neurons and/or glia cells underlie their pathogenesis, as proven in animal models (11).

Genetic determinants and molecular pathways of ID and ASD

For the accurate development as well as functioning of the brain, the coordinated and timely work of hundreds of genes is essential; 2000 to 3500 genes critical for brain function and involved in neurodevelopmental disorders has been made (1). Given the large number of proteins that must be produced at the right time and right amount, it is not surprising that both ID and ASD are characterized by a great genetic heterogeneity (12). However, the first-tier genetic test that should be recommended is array-CGH (13), in order to exclude copy number variants (CNV), possibly integrated by karyotyping when a chromosome translocation is suspected. Another cheap and useful first-tier assay looks for the possible CGG expansion in the FMR1 gene, since fragile X syndrome should be excluded before further testing, although recent reports argue that it should not be performed in the absence of family history and/or clinical features (14). Fragile X syndrome was the first monogenic ID condition whose gene was identified (in 1991), partly because of its frequency (relatively high, thanks to dynamic nature of its mutational mechanism) and partly because X-linked transmission is more easily recognized (7). In fact, X-linked conditions were identified first because of their typical inheritance pattern (affected males connected by carrier females) and, while 82 genes on the X chromosome had been associated with intellectual disability in 2008 (15), presently OMIM lists 167 X-linked ID genes (Table S2 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip). Then, the improvement of sequencing technology facilitated the analysis of (even small) autosomal recessive families (16) and of sporadic patients with autosomal dominant de novo mutations (17): as indicated in Table S2, there are now 1170 genes in OMIM whose mutations result in ID. The corresponding proteins play very different roles in the various cells, as gene ontology analysis revealed (1), however their functions ultimately converge on key biological pathways (18). Also in ASD most genes work in converging networks that are enriched in neuronal signaling, synaptic function, chromatin remodeling and channel activity (19,20).

Next-generation sequencing technologies in ID/ASD diagnostics

An accurate molecular diagnosis of neurodevelopmental disorders is important for their eventual treatment. However, differentiating between these clinically overlapping conditions with huge genetic heterogeneity is very difficult and up to 50% patients suffering from ID and/or ASD remain molecularly undiagnosed. Next-generation sequencing (NGS) technologies have greatly improved the chance of identifying known as well as novel responsible genes, hence allowing clinicians to establish a molecular diagnosis in a time- as well as cost-effective manner (21-23). The most powerful techniques involve NGS sequencing of known coding exons (“whole exome” sequencing i.e. WES) or possibly the “whole genome” (WGS) but these approaches require large investment on data storage and bioinformatic analysis as well as the availability of DNA from at least the patient’s parents (trio analysis) in order to sift through the huge amount of genetic variants that will be identified. Harripaul et al. (21) provide and excellent review of the evolution of NGS technologies with their potentials and pitfalls, while Han and Lee (22) describe the possible strategies and stepwise approach to diagnosing children with ID and/or developmental delay. Although WES and WGS may seem the best option to tackle the problem, increasing the amount of data comes with its limitations (e.g. insufficient coverage of part of some genes) and risks (e.g. incidental findings), even if increased costs were not a problem. Therefore, the choice of targeted gene panels as second-tier approach after chromosome studies, FMR1 screening and array-CGH (22) is probably wise, given their higher coverage of the selected genes and the possibility of analyzing only the proband without his parents.

Gene panel sequencing

Targeted gene panels are indeed useful tools for parallel analysis of clinically relevant genes that should be “deep” sequenced with very high coverage in order to reliably exclude not only the presence of variants in phenotype-related genes, but also intragenic deletions/duplications (24). Hundreds of genes linked with intellectual disability are presently included in several academic as well as commercial panels that also allow some extent of customization related to targeted genes number and identity. Multiple factors regulate gene panel size, like the incidence of mutations in a specific gene among patients, clinical heterogeneity of the tested population, available infrastructure for sequencing and bioinformatic analysis as well as the clinical and analytical capabilities of the involved institute or center (see the Genetic Testing Registry at https://www.ncbi.nlm.nih.gov/gtr/). Redin et al. (25) reached a diagnostic yield of 25% when 106 selected patients with ID (but without congenital malformations, fragile X syndrome or CNV detectable by array-CGH), using a targeted gene panel with 99 X-linked and 118 autosomal genes. One year later, in 2015, Grozeva et al. (26) reported on their less selected population of 986 patients with moderate to severe ID screened with a larger panel of 565 genes and found likely pathogenic variants in 11% of them. More recently Yan et al. (27) used a panel with 454 genes to screen 112 Chinese patients, reaching a definite diagnosis in 9 of them (8% yield). Finally, Aspromonte et al. (28) designed a smaller panel including just 74 genes belonging to molecular pathways involved in the pathogenesis of both ID and ASD: given their careful selection of both genes and patients (negative for CNV, FMR1 expansion, deletions/imprinting defects in 15q11q13, as well as variants in MECP2, CDKL5 and UBE3A), they reached a 27% total diagnostic yield (41/150 patients). Considering all these previous experiences, we designed a new NGS panel targeting 174 genes (Table S5 - not present in the article, please see at https://mattiolihealth.com/wp-content/uploads/2020/11/Supplementary-Tables-10684.zip) that is being used to screen patients with ID and/or ASD preselected with array-CGH and FMR1 CGG testing. We expect this approach to deliver a rapid, cost-efficient and sensitive analysis. Although gene panels are mostly useful for rare diseases that have well defined molecular origins, such an approach may serve well as second-tier screening test for individual patients. In case of a negative result, if DNA from relevant relatives is available, genome-wide techniques such as WES or WGS will be considered. However, given the rapid pace at which genetic knowledge accumulates, we anticipate that the panel structure will require a regular update to include newly identified genes and exclude those that are much less frequently mutated.

Conclusion

Intellectual disability and autism spectrum disorders are neurodevelopmental conditions characterized by cognitive impairment, defective adaptive behaviour and limited social interactions. ID and ASD have several environmental and genetic causes and 1400 human genes are described in OMIM associated either of the two or both. An accurate clinical as well as molecular diagnosis is essential for a deeper understanding of the pathogenesis of these conditions and for devising effective treatments. In fact, though some preclinical trials are ongoing, current therapeutic strategies are mostly symptomatic and aimed at controlling hyperactivity, anxiety, depression or epilepsy; sometimes patients develop undesired side effects especially when too many medications are co-administered. Therefore, NGS technology will hopefully facilitate an accurate diagnosis of the molecular basis of each individual condition so that every patient may receive a tailored treatment, fulfilling the promise of Precision Medicine (29).
  29 in total

1.  A de novo paradigm for mental retardation.

Authors:  Lisenka E L M Vissers; Joep de Ligt; Christian Gilissen; Irene Janssen; Marloes Steehouwer; Petra de Vries; Bart van Lier; Peer Arts; Nienke Wieskamp; Marisol del Rosario; Bregje W M van Bon; Alexander Hoischen; Bert B A de Vries; Han G Brunner; Joris A Veltman
Journal:  Nat Genet       Date:  2010-11-14       Impact factor: 38.330

Review 2.  Genetics of intellectual disability.

Authors:  H Hilger Ropers
Journal:  Curr Opin Genet Dev       Date:  2008-08-28       Impact factor: 5.578

3.  Excess of de novo deleterious mutations in genes associated with glutamatergic systems in nonsyndromic intellectual disability.

Authors:  Fadi F Hamdan; Julie Gauthier; Yoichi Araki; Da-Ting Lin; Yuhki Yoshizawa; Kyohei Higashi; A-Reum Park; Dan Spiegelman; Sylvia Dobrzeniecka; Amélie Piton; Hideyuki Tomitori; Hussein Daoud; Christine Massicotte; Edouard Henrion; Ousmane Diallo; Masoud Shekarabi; Claude Marineau; Michael Shevell; Bruno Maranda; Grant Mitchell; Amélie Nadeau; Guy D'Anjou; Michel Vanasse; Myriam Srour; Ronald G Lafrenière; Pierre Drapeau; Jean Claude Lacaille; Eunjoon Kim; Jae-Ran Lee; Kazuei Igarashi; Richard L Huganir; Guy A Rouleau; Jacques L Michaud
Journal:  Am J Hum Genet       Date:  2011-03-03       Impact factor: 11.025

Review 4.  The Use of Next-Generation Sequencing for Research and Diagnostics for Intellectual Disability.

Authors:  Ricardo Harripaul; Abdul Noor; Muhammad Ayub; John B Vincent
Journal:  Cold Spring Harb Perspect Med       Date:  2017-03-01       Impact factor: 6.915

5.  Genetics of intellectual disability in consanguineous families.

Authors:  Hao Hu; Kimia Kahrizi; Hans-Hilger Ropers; Hossein Najmabadi; Luciana Musante; Zohreh Fattahi; Ralf Herwig; Masoumeh Hosseini; Cornelia Oppitz; Seyedeh Sedigheh Abedini; Vanessa Suckow; Farzaneh Larti; Maryam Beheshtian; Bettina Lipkowitz; Tara Akhtarkhavari; Sepideh Mehvari; Sabine Otto; Marzieh Mohseni; Sanaz Arzhangi; Payman Jamali; Faezeh Mojahedi; Maryam Taghdiri; Elaheh Papari; Mohammad Javad Soltani Banavandi; Saeide Akbari; Seyed Hassan Tonekaboni; Hossein Dehghani; Mohammad Reza Ebrahimpour; Ingrid Bader; Behzad Davarnia; Monika Cohen; Hossein Khodaei; Beate Albrecht; Sarah Azimi; Birgit Zirn; Milad Bastami; Dagmar Wieczorek; Gholamreza Bahrami; Krystyna Keleman; Leila Nouri Vahid; Andreas Tzschach; Jutta Gärtner; Gabriele Gillessen-Kaesbach; Jamileh Rezazadeh Varaghchi; Bernd Timmermann; Fatemeh Pourfatemi; Aria Jankhah; Wei Chen; Pooneh Nikuei; Vera M Kalscheuer; Morteza Oladnabi; Thomas F Wienker
Journal:  Mol Psychiatry       Date:  2018-01-04       Impact factor: 15.992

6.  Which genes to assess in the NGS diagnostics of intellectual disability? The case for a consensus database-driven and expert-curated approach.

Authors:  Florian Erger; Christian P Schaaf; Christian Netzer
Journal:  Mol Cell Probes       Date:  2019-03-23       Impact factor: 2.365

7.  Convergence of genes and cellular pathways dysregulated in autism spectrum disorders.

Authors:  Dalila Pinto; Elsa Delaby; Daniele Merico; Mafalda Barbosa; Alison Merikangas; Lambertus Klei; Bhooma Thiruvahindrapuram; Xiao Xu; Robert Ziman; Zhuozhi Wang; Jacob A S Vorstman; Ann Thompson; Regina Regan; Marion Pilorge; Giovanna Pellecchia; Alistair T Pagnamenta; Bárbara Oliveira; Christian R Marshall; Tiago R Magalhaes; Jennifer K Lowe; Jennifer L Howe; Anthony J Griswold; John Gilbert; Eftichia Duketis; Beth A Dombroski; Maretha V De Jonge; Michael Cuccaro; Emily L Crawford; Catarina T Correia; Judith Conroy; Inês C Conceição; Andreas G Chiocchetti; Jillian P Casey; Guiqing Cai; Christelle Cabrol; Nadia Bolshakova; Elena Bacchelli; Richard Anney; Steven Gallinger; Michelle Cotterchio; Graham Casey; Lonnie Zwaigenbaum; Kerstin Wittemeyer; Kirsty Wing; Simon Wallace; Herman van Engeland; Ana Tryfon; Susanne Thomson; Latha Soorya; Bernadette Rogé; Wendy Roberts; Fritz Poustka; Susana Mouga; Nancy Minshew; L Alison McInnes; Susan G McGrew; Catherine Lord; Marion Leboyer; Ann S Le Couteur; Alexander Kolevzon; Patricia Jiménez González; Suma Jacob; Richard Holt; Stephen Guter; Jonathan Green; Andrew Green; Christopher Gillberg; Bridget A Fernandez; Frederico Duque; Richard Delorme; Geraldine Dawson; Pauline Chaste; Cátia Café; Sean Brennan; Thomas Bourgeron; Patrick F Bolton; Sven Bölte; Raphael Bernier; Gillian Baird; Anthony J Bailey; Evdokia Anagnostou; Joana Almeida; Ellen M Wijsman; Veronica J Vieland; Astrid M Vicente; Gerard D Schellenberg; Margaret Pericak-Vance; Andrew D Paterson; Jeremy R Parr; Guiomar Oliveira; John I Nurnberger; Anthony P Monaco; Elena Maestrini; Sabine M Klauck; Hakon Hakonarson; Jonathan L Haines; Daniel H Geschwind; Christine M Freitag; Susan E Folstein; Sean Ennis; Hilary Coon; Agatino Battaglia; Peter Szatmari; James S Sutcliffe; Joachim Hallmayer; Michael Gill; Edwin H Cook; Joseph D Buxbaum; Bernie Devlin; Louise Gallagher; Catalina Betancur; Stephen W Scherer
Journal:  Am J Hum Genet       Date:  2014-04-24       Impact factor: 11.025

8.  Targeted next generation sequencing in 112 Chinese patients with intellectual disability/developmental delay: novel mutations and candidate gene.

Authors:  Huifang Yan; Zhen Shi; Ye Wu; Jiangxi Xiao; Qiang Gu; Yanling Yang; Ming Li; Kai Gao; Yinyin Chen; Xiaoping Yang; Haoran Ji; Binbin Cao; Ruoyu Duan; Yuwu Jiang; Jingmin Wang
Journal:  BMC Med Genet       Date:  2019-05-14       Impact factor: 2.103

9.  Systematic Phenomics Analysis Deconvolutes Genes Mutated in Intellectual Disability into Biologically Coherent Modules.

Authors:  Korinna Kochinke; Christiane Zweier; Bonnie Nijhof; Michaela Fenckova; Pavel Cizek; Frank Honti; Shivakumar Keerthikumar; Merel A W Oortveld; Tjitske Kleefstra; Jamie M Kramer; Caleb Webber; Martijn A Huynen; Annette Schenck
Journal:  Am J Hum Genet       Date:  2016-01-07       Impact factor: 11.025

10.  Efficient strategy for the molecular diagnosis of intellectual disability using targeted high-throughput sequencing.

Authors:  Claire Redin; Bénédicte Gérard; Julia Lauer; Yvan Herenger; Jean Muller; Angélique Quartier; Alice Masurel-Paulet; Marjolaine Willems; Gaétan Lesca; Salima El-Chehadeh; Stéphanie Le Gras; Serge Vicaire; Muriel Philipps; Michaël Dumas; Véronique Geoffroy; Claire Feger; Nicolas Haumesser; Yves Alembik; Magalie Barth; Dominique Bonneau; Estelle Colin; Hélène Dollfus; Bérénice Doray; Marie-Ange Delrue; Valérie Drouin-Garraud; Elisabeth Flori; Mélanie Fradin; Christine Francannet; Alice Goldenberg; Serge Lumbroso; Michèle Mathieu-Dramard; Dominique Martin-Coignard; Didier Lacombe; Gilles Morin; Anne Polge; Sylvie Sukno; Christel Thauvin-Robinet; Julien Thevenon; Martine Doco-Fenzy; David Genevieve; Pierre Sarda; Patrick Edery; Bertrand Isidor; Bernard Jost; Laurence Olivier-Faivre; Jean-Louis Mandel; Amélie Piton
Journal:  J Med Genet       Date:  2014-08-28       Impact factor: 6.318

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  5 in total

Review 1.  Molecular Mechanisms of Aberrant Neuroplasticity in Autism Spectrum Disorders (Review).

Authors:  A A Anashkina; E I Erlykina
Journal:  Sovrem Tekhnologii Med       Date:  2021-02-28

2.  Missense variants in DPYSL5 cause a neurodevelopmental disorder with corpus callosum agenesis and cerebellar abnormalities.

Authors:  Médéric Jeanne; Hélène Demory; Aubin Moutal; Marie-Laure Vuillaume; Sophie Blesson; Rose-Anne Thépault; Sylviane Marouillat; Judith Halewa; Saskia M Maas; M Mahdi Motazacker; Grazia M S Mancini; Marjon A van Slegtenhorst; Avgi Andreou; Helene Cox; Julie Vogt; Jason Laufman; Natella Kostandyan; Davit Babikyan; Miroslava Hancarova; Sarka Bendova; Zdenek Sedlacek; Kimberly A Aldinger; Elliott H Sherr; Emanuela Argilli; Eleina M England; Séverine Audebert-Bellanger; Dominique Bonneau; Estelle Colin; Anne-Sophie Denommé-Pichon; Brigitte Gilbert-Dussardier; Bertrand Isidor; Sébastien Küry; Sylvie Odent; Richard Redon; Rajesh Khanna; William B Dobyns; Stéphane Bézieau; Jérôme Honnorat; Bernhard Lohkamp; Annick Toutain; Frédéric Laumonnier
Journal:  Am J Hum Genet       Date:  2021-04-23       Impact factor: 11.043

3.  Diagnostic yield of patients with undiagnosed intellectual disability, global developmental delay and multiples congenital anomalies using karyotype, microarray analysis, whole exome sequencing from Central Brazil.

Authors:  Ana Julia da Cunha Leite; Irene Plaza Pinto; Nico Leijsten; Martina Ruiterkamp-Versteeg; Rolph Pfundt; Nicole de Leeuw; Aparecido Divino da Cruz; Lysa Bernardes Minasi
Journal:  PLoS One       Date:  2022-04-07       Impact factor: 3.240

Review 4.  Cerebral Folate Deficiency Syndrome: Early Diagnosis, Intervention and Treatment Strategies.

Authors:  Vincent Th Ramaekers; Edward V Quadros
Journal:  Nutrients       Date:  2022-07-28       Impact factor: 6.706

5.  New Candidates for Autism/Intellectual Disability Identified by Whole-Exome Sequencing.

Authors:  Lucia Pia Bruno; Gabriella Doddato; Floriana Valentino; Margherita Baldassarri; Rossella Tita; Chiara Fallerini; Mirella Bruttini; Caterina Lo Rizzo; Maria Antonietta Mencarelli; Francesca Mari; Anna Maria Pinto; Francesca Fava; Alessandra Fabbiani; Vittoria Lamacchia; Anna Carrer; Valentina Caputo; Stefania Granata; Elisa Benetti; Kristina Zguro; Simone Furini; Alessandra Renieri; Francesca Ariani
Journal:  Int J Mol Sci       Date:  2021-12-14       Impact factor: 5.923

  5 in total

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