Search Advanced

AIMS Allergy and Immunology

2022, Volume 6, Issue 3: 126-152. doi: 10.3934/Allergy.2022011
Previous Article Next Article
Review Special Issues

Multiple sclerosis and allergic diseases: is there a relationship?

  • 1.
    Department of Innovative Technologies in Medicine and Dentistry, University “G. d'Annunzio” of Chieti-Pescara, Italy
  • 2.
    Department of Pharmacy, University “G. d'Annunzio” of Chieti-Pescara, Italy
  • 3.
    Department of Medicine and Science of Aging, University “G. d'Annunzio” of Chieti-Pescara, Italy

  • Immune system disorders characterize various diseases such as multiple sclerosis (MS) and allergic diseases (AD). In MS, T-helper (Th)1 cell phenotype is responsible for the disease onset and long-term evolution. On the other hand, excessive Th2 cell activity has been demonstrated in AD. The simultaneous increase of MS and AD in the same geographical areas, observed in recent years, has questioned the mutually exclusive correlation between MS and AD immunopathogenesis supported by the Th1/Th2 paradigm and has moved the interest in understanding possible overlaps. This manuscript aims to discuss the literature, collected over the past two decades, about the association between MS and AD, and both experimental and epidemiological studies have been reviewed. The results do not provide a solid correlation between AD and MS, although experimental studies support the involvement of the same cells and molecules in the immunopathogenesis of both diseases. Further studies, increasing knowledge on the cellular and molecular mechanisms involved in these two disorders, could help to clarify if a positive or negative association links them and provide the possibility for the development of new therapies.

    Citation: Lisa Aielli, Federica Serra, Erica Costantini. Multiple sclerosis and allergic diseases: is there a relationship?[J]. AIMS Allergy and Immunology, 2022, 6(3): 126-152. doi: 10.3934/Allergy.2022011

    Related Papers:

    [1] Marcos André dos Santos, Alfredo Jarma-Orozco, Flavio Lozano-Isla, José Nailson S. Barros, Jesús Rivera, Carlos Espitia-Romero, Ángela Castillejo-Morales, Betty Jarma-Arroyo, Marcelo Francisco Pompelli . Leaf area estimation in Jatropha curcas (L.): an update. AIMS Environmental Science, 2018, 5(5): 353-371. doi: 10.3934/environsci.2018.5.353
    [2] Marcelo F. Pompelli, José N. B. Santos, Marcos A. Santos . Estimating leaf area of Jatropha nana through non-destructive allometric models. AIMS Environmental Science, 2019, 6(2): 59-76. doi: 10.3934/environsci.2019.2.59
    [3] Santosh Kumar Karn, Xiangliang Pan . Biotransformation of As (III) to As (V) and their stabilization in soil with Bacillus sp. XS2 isolated from gold mine tailing of Xinjiang, China. AIMS Environmental Science, 2016, 3(4): 592-603. doi: 10.3934/environsci.2016.4.592
    [4] Bruce S Dien, Patricia J. Slininger, Cletus P. Kurtzman, Bryan R. Moser, Patricia J. O’Bryan . Identification of superior lipid producing Lipomyces and Myxozyma yeasts. AIMS Environmental Science, 2016, 3(1): 1-20. doi: 10.3934/environsci.2016.1.1
    [5] Marcelo F. Pompelli, Gilmara M. Pompelli, Antônio F. M. de Oliveira, Werner C. Antunes . The effect of light and nitrogen availability on the caffeine, theophylline and allantoin contents in the leaves of Coffea arabica L.. AIMS Environmental Science, 2014, 1(1): 1-11. doi: 10.3934/environsci.2013.1.1
    [6] Parthiban Rajasekaran, Harikishan Kannan, Smruti Das, Mikaeel Young, Swadeshmukul Santra . Comparative analysis of copper and zinc based agrichemical biocide products: materials characteristics, phytotoxicity and in vitro antimicrobial efficacy. AIMS Environmental Science, 2016, 3(3): 439-455. doi: 10.3934/environsci.2016.3.439
    [7] James Bland, Gabriel da Silva . A detailed chemical kinetic model for pyrolysis of the lignin model compound chroman. AIMS Environmental Science, 2014, 1(1): 12-25. doi: 10.3934/environsci.2013.1.12
    [8] Geraldo Ceni Coelho, Glaci Benvenuti-Ferreira, Jorge Schirmer, Osório A. Lucchese . Survival, growth and seed mass in a mixed tree species planting for Atlantic Forest restoration. AIMS Environmental Science, 2016, 3(3): 382-394. doi: 10.3934/environsci.2016.3.382
    [9] Yang Wang, Chenhui Liang, Shijie Liu . Ethanol production from hot-water sugar maple wood extract hydrolyzate: fermentation media optimization for Escherichia coli FBWHR. AIMS Environmental Science, 2015, 2(2): 269-281. doi: 10.3934/environsci.2015.2.269
    [10] Natalia Ros, Laura Lomba, Ma Pilar Ribate, Estefania Zuriaga, Cristina B. García, Beatriz Giner . Acute lethal and sublethal effects of diltiazem and doxepin for four aquatic environmental bioindicators covering the trophic chain. AIMS Environmental Science, 2018, 5(4): 229-243. doi: 10.3934/environsci.2018.4.229

  • Immune system disorders characterize various diseases such as multiple sclerosis (MS) and allergic diseases (AD). In MS, T-helper (Th)1 cell phenotype is responsible for the disease onset and long-term evolution. On the other hand, excessive Th2 cell activity has been demonstrated in AD. The simultaneous increase of MS and AD in the same geographical areas, observed in recent years, has questioned the mutually exclusive correlation between MS and AD immunopathogenesis supported by the Th1/Th2 paradigm and has moved the interest in understanding possible overlaps. This manuscript aims to discuss the literature, collected over the past two decades, about the association between MS and AD, and both experimental and epidemiological studies have been reviewed. The results do not provide a solid correlation between AD and MS, although experimental studies support the involvement of the same cells and molecules in the immunopathogenesis of both diseases. Further studies, increasing knowledge on the cellular and molecular mechanisms involved in these two disorders, could help to clarify if a positive or negative association links them and provide the possibility for the development of new therapies.


    1. Introduction

    Jatropha, commonly called as physic nut, belongs to family Euphorbiaceae and comprises of 172 species of which the most primitive species is Jatropha curcas L. (2n = 22) [1]. Jatropha curcas has been recognized as an important crop for biodiesel production. The Jatropha species is perennial shrub and serves as an important wasteland crop facilitating soil conservation by protecting soil against erosion via wind and animals interference. It is widely distributed in Central and South America, Africa, India and South East Asia. The J. curcas originated in Central and South America, and distributed to other tropical countries [2]. It is mainly evolved for dryland and adapt well in limited water source. Several characteristics of J. curcas such as drought resistance, speedy growth, easy propagation and wide adaptation to soil conditions have led to the wide spread of J. curcas [3,4,5]. It has acclimatized in different agro-climatic regions because of its strong adaptation at morphological and physiological level. J. curcas is considered as the best source for restoration of ruined lands and rural development. The J. curcas seeds have semi-drying oil (32–35%) and yield biodiesel of European (EN 14214) and American (ASTM D6751) standards [3,6] via trans-esterification. J. curcas seed oil used in the production of biodiesel is eco-friendly, biodegradable, non-toxic and renewable to petroleum diesel [7,8]. It can be used as a traditional vegetable oil or trans-esterified to produce biodiesel for use in standard diesel engines. These properties of J. curcas have fascinated globally to develop a sustainable alternative feedstock for biodiesel production [9,10]. After oil extraction, the remaining seed cake can be used as organic fertilizer. Seed cake can be also used for direct combustion or charcoal conversion [11]. J. curcas has been used for the isolation and production of pharmaceutical and pesticides in China [12]. Anti-viral (against herpesvirus Ⅰ and Ⅱ) and antibacterial (Staphylococcus aureus and Monilia albicans) skin disinfectors are commercialized [13]. Additional products from J. curcas are A2-Jetfuel kerosene and polyol biodegradable foam for use in packaging and insulation industry, paint from the bark [14].

    DNA (or molecular) markers are used predominantly due to their abundance, plentiful in number and are unaltered by environmental factors and/or the plant developmental stage. Molecular markers develop from different classes of DNA mutations such as rearrangements (insertions or deletions), substitution (point mutations), or errors in replication of tandemly repeated DNA. Molecular markers have several applications in plant breeding such as (ⅰ) evaluation and selection of breeding materials for genetic diversity, parental selection, cultivar identity and assessment of cultivar purity, (ⅱ) trait pyramiding, and (ⅲ) backcrossing.

    Molecular markers have played an important role in the detection of unique alleles between two or more species which can be applied in the species characterization and improvement. Molecular markers have been abundantly used to evaluate biodiversity, phylogenetic relationships, construction of genetic linkage maps and in tagging and mapping of useful traits. Currently, genetic diversity studies in the genus Jatropha are focused on J. curcas and few wild species that are commonly distributed in India. Different types of single and multi-locus molecular markers such as random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), sequence-characterized amplified region (SCAR), inter simple sequence repeats (ISSRs), simple sequence repeats (SSRs) and single-nucleotide polymorphism (SNPs), etc. were used for assessment of genetic diversity in the available germplasm. This review mainly focus on the different studies carried out on genetic variability present in the Jatropha species other than Central and South-American and African regions.

    2. Genetic diversity studies in J. curcas using Molecular Markers

    2.1. Amplified fragment length polymorphism (AFLP)

    The AFLP is trustworthy, high throughput and less expansive. Many researchers from India, China, Brazil and Mexico used AFLP markers for genetic diversity analysis in J. curcas accessions and reported the presence of low to high genetic variability. Some researchers reported that germplasms from Mexico and Central America have high genetic diversity by using AFLP markers (Table 1). The different accessions from Mexico and Central America regions with high oil content and other characters are shown link with its productivity. These genetically contrary germplasm may provide critical resources for future genetic improvement of J. curcas. Zhang et al. [15] studied the genetic diversity within 240 samples by AFLP from three Asian countries, two African countries and different geographical regions in China. The germplasm of J. curcas showed a narrow genetic diversity in China and Southeast Asia with molecular polymorphism of 14.8%. Genotypic and phenotypic evaluation of a total of 182 accessions from Asia (91), Africa (35), South America (9) and Central America (47) was carried out to estimate the genetic variation. A very large genetic variation by DNA-marker in the pool of Central American accessions was observed as compared from other regions. According to Luis et al. [16] the Central American accessions can be considered as the most important source for plant breeding as they have highest phenotypic variation. Further, it is also stated that Mexico and Central America have highest genetic diversity in J. curcas than in other parts of the world because the Mexico and Central America (Mesoamerican region) may be a centre of origin and diversity of J. curcas [17]. The genetic diversity study consisted of 114 accessions from 15 populations of 4 different species: J. curcas, J. costaricensis, J. gossypifolia and J. stevensii collected from Costa Rica were analysed by AFLP. The results showed that the species that obtained the highest average of polymorphic loci was J. curcas, followed by J. gossypifolia, J. costaricensis, and J. stevensii [18]. A broad genetic base of 48 J. curcas germplasm from six different states in India was reported [19]. Genetic and fatty acid variability in four datasets of accessions and pre-breeding lines of J. curcas was analysed. The results revealed that both genetic as well as fatty acid variability was significantly higher in the newly created pre-breeding lines and the level of fatty acid variability in these datasets was different and highly correlated to the level of their genetic variability as revealed by AFLP markers [20].

    Table 1. Genetic Diversity of J. curcas by using AFLP Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference/s
    1 58 China and Malaysia Genetic Diversity 7 [27]
    2 7 India Genetic Diversity 56 [8]
    3 38 India, Nigeria and Thailand Genetic Diversity 32 [34]
    4 48 India Genetic Diversity 7 [19]
    5 5 China, Indonesia, Suriname, Tanzania and India Agronomic traits 23 [35]
    6 28 India Genetic Diversity 30 [36]
    7 38 China and Indonesia. Genetic diversity 9 [37]
    8 134 Chiapas, Mexico: Soconusco, Isthmus, Center, Frailesca and Border Genetic Diversity 209 [17]
    9 88 Mexico Genetic diversity on floral traits. 6 [38]
    10 240 Africa, China and Asia Genetic Diversity 6 [15]
    11 182 Asia, Africa, South America and Central America Oil yield 20 [16]
    12
    13
    14    		 114 (accessions from 15 populations of 4 different species of J. curcas.
    65 (J. curcas accessions (13), BC1 (28), BC1F2 (12) and single seeds (12). The BC1, BC1F2 and single seed dataset were derived from an interspecific cross between J. curcas and J. integerrima)
    6 populations amounting to a total number of 70 genotypes of Jatropha curcas L. originating from Africa (Senegal, Mali, Burkina Faso and Madagascar)    		 Costa Rica
    India
    Africa    		 Agronomic Traits
    Fatty acid composition
    Genetic Diversity    		 3
    4
    2    		 [18]
    [20]
    [39]
     | Show Table
    DownLoad: CSV

    2.2. Randomly amplified polymorphic DNA (RAPD)

    The RAPD technique is simple, rapid, low-cost and can be deployed even in the absence of any prior information related the genome or DNA of the plant. The RAPD technique has been used for assessment of genetic diversity for J. curcas (Table 2) and has revealed that low to moderate level of genetic diversity of Indian germplasms. Assessment of genetic diversity among 43 germplasm collected from different regions in India showed moderate level of genetic variation, however, wide genetic variation was observed between the Indian and Mexican genotypes [21]. Hybrid conformity using RAPD markers was carried out for a backcross involving J. curcas and J. integerrima, thereby, indicating the potential of employing the RAPD analysis for pre-breeding and genetic enhancement of J. curcas through interspecific hybridization [22]. A narrow genetic diversity in 192 J. curcas accessions of Brazil was revealed by using RAPD markers [23].

    Table 2. Genetic Diversity of J. curcas by using RAPD Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference/s
    1 43 India and Mexico Genetic Diversity 400 [21]
    2 18 India Genetic Diversity 11 [40]
    3 12 India Genetic Diversity 26 [41]
    4 13 India Genetic Diversity 20 [42]
    5 7 India Genetic Diversity 5 [43]
    6 34 accessions comprising eight agronomically important Jatropha species India Agronomic traits 100 [22]
    7 26 India Genetic Diversity 55 [44]
    8 7 India Genetic Diversity 180 [8]
    9 38 India, Nigeria and Thailand Genetic Diversity 10 [45]
    10 19 Mexico, South America, Asia and Africa Genetic Diversity 10 [5]
    11 40 India Genetic Diversity 50 [46]
    12 28 India Genetic Diversity 52 [35]
    13 192 Brazil Genetic Diversity 96 [23]
    14 10 India Genetic Diversity 43 [47]
    15 24 China Genetic Diversity 5 [48]
    16 4 India Genetic Diversity 13 [49]
    17 160 Kenya Genetic Diversity 10 [4]
    18 48 Malaysia Genetic Diversity 8 [50]
    19
    20    		 29
    24    		 India
    Indonesia    		 Genetic Diversity
    Genetic Diversity    		 47
    22    		 [51]
    [52]
     | Show Table
    DownLoad: CSV

    The genetic diversity and genetic structure analysis of 160 individuals from eight Kenya populations, suggested that the Kenya germplasms have a broad genetic base and are therefore, important and useful for breeding programmes of Jatropha [4].

    2.3. Inter simple sequence repeats (ISSRs)

    The ISSR analysis, is technically simple, it has been used for evaluating the genetic variation and genetic relatedness of the Jatropha species and high level of genetic variation is predicted in Jatropha by using ISSR markers (Table 3). The genetic variability among 332 J. curcas cultivated accessions from Brazil were investigated using ISSR primers revealed high genetic diversity of J. curcas at species level [24]. A high level of genetic diversity in 224 J. curcas accessions in China was reported based on ISSR molecular profiles [25]. Genetic diversity analysis of J. curcas accessions from Mexico revealed a high genetic diversity in germplasm [26]. Characterization of Jatropha species occurring in India is using nuclear and organelle specific primers for supporting interspecific gene transfer. The J. tanjorensis is considered as a natural hybrid between J. gossypifolia and J. curcas via ISSR markers [22].

    Table 3. Genetic Diversity of J. curcas by using ISSR Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference/s
    1 43 India and Mexico Genetic Diversity 100 [21]
    2 9 China Genetic Diversity 10 [53]
    3 13 India Genetic Diversity 25 [42]
    4 34 accessions comprising eight agronomically important Jatropha species India Agronomic traits 100 [22]
    5 11 India Genetic Diversity 9 [54]
    6 19 Mexico, South America, Asia and Africa Genetic Diversity 6 [5]
    7 224 China and Myanmar Genetic Diversity 100 [25]
    8 10 India Genetic Diversity 12 [55]
    9 17 India and Zimbabwe Genetic Diversity 13 [51]
    10 24 China Genetic Diversity 12 [48]
    11 332 Brazil Genetic Diversity 32 [24]
    12 39 accessions with six different Jatropha sps. and the last and most distinct group was Ricinus communis.) Mexico, China, Vietnam and Thailand Genetic Diversity 86 [26]
    13 16 Malaysia Genetic Diversity 8 [9]
    14
    15
    16
    17
    18    		 29
    24
    66
    10
    24    		 India
    Indonesia
    Brazil
    Brazil
    Mexico    		 Genetic Diversity
    Genetic Diversity
    Genetic variability
    Genetic Diversity
    Genetic Diversity    		 25
    9
    10
    9
    6    		 [29]
    [52]
    [56]
    [57]
    [58]
     | Show Table
    DownLoad: CSV

    2.4. Simple sequence repeats (SSRs)

    The SSRs (microsatellites), with their larger number and immense potential for variation, form an indispensable component of genetic diversity studies. There is a wide scope and utility for these SSR markers towards diversity estimation and marker assisted breeding of J. curcas (Table 4). A total of 182 accessions were evaluated at genetic and phenotypic level using SSRs for genetic diversity assessment revealed moderate diversity [16]. Low genetic diversity was recorded among 192 J. curcas accessions collected from different geographical regions throughout Brazil using SSR markers [23]. Very low genetic diversity was observed among the 58 accessions of J. curcas collected across China as out 17 genomic SSRs, only one was polymorphic [27]. Pamidimarri DVNS et al. [28] analysed 12 microsatellite markers, and found seven polymorphic markers between the toxic and non-toxic varieties at molecular level.

    Table 4. Genetic Diversity of J. curcas by using SSR Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference/s
    1 58 China and Malaysia Genetic Diversity 17 [27]
    2 7 India Genetic Diversity 12 [28]
    3 19 Mexico, South America, Asia and Africa Genetic Diversity 10 [5]
    4 192 Brazil Genetic Diversity 6 [23]
    5 41 Brazil Genetic Diversity 9 [59]
    6
    7    		 29
    4    		 Mexico, South America and Africa 2 toxic (Africa and South America)
    2 Nontoxic (Mexico)    		 Toxic trait
    Phorbol esters    		 40
    5    		 [60]
    [61]
    8
    9
    10    		 182
    93
    158    		 Asia, Africa, South America and Central America
    Mexico
    Ecuador    		 Oil yield
    Genetic Diversity
    Genetic Diversity    		 29
    10
    10    		 [16]
    [62]
    [63]
     | Show Table
    DownLoad: CSV

    2.5. Expressed sequence tag (EST)-SSRs

    The EST-SSRs markers are important to investigate genetic diversity of J. curcas. The SSR (including EST-SSRs) have predicted lower genetic diversity of J. curcas germplasm as compared to AFLP, RAPD and ISSR makers in several research reports (Table 5). This is SSR markers identify the variation in repeat regions only whereas entire genome is used by AFLP, RAPD and ISSR makers for diversity analysis. Moderate level of genetic diversity was observed among 45 J. curcas accessions using EST-SSRs [29]. The genetic relationships determined by EST-SSRs among 25 J. curcas accessions were grouped into three main clusters which reveals low genetic diversity among accessions [30]. Out of 432 EST-SSR primer pairs, 269 were polymorphic among the Jatropha and Jatropha-related species [31].

    Table 5. Genetic Diversity of J. curcas by using EST-SSR Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference/s
    1 45 Indonesia, China, Grenada and South America Genetic Diversity 187 EST-SSR and 54 Genomic SSR [29]
    2 25 India Genetic Diversity 12080 Sequences [30]
    3 2 J.curcas and and four Jatropha-related species. Thailand Phorbol esters 432 Sequences [31]
    4 50 Costa Rica Genetic Diversity 21 [64]
     | Show Table
    DownLoad: CSV

    2.6. Single-nucleotide polymorphisms (SNPs)

    In recent years, the employment of SNP markers towards assessing population genetic structure in different species have increased. The unavailability of DNA sequence information restricts the use of SNPs for assessing the population genetic structure of the diverse J. curcas accessions. As SNPs show the most abundant source of genetic polymorphism, there is an immediate need to develop SNP markers and use them in various studies in J. curcas (Table 6). A narrow level of genetic diversity was observed among 148 global collections of J. curcas lines using SNPs [32]. The genetic diversity analysis among 273 J. curcas accessions using SNP markers revealed the presence of low genetic diversity [33]. Twenty candidate SNPs were identified from J. curcas accessions having low and high phorbol esters (PEs), and interestingly, one gene involved PE biosynthesis pathway was also identified [31].

    Table 6. Genetic Diversity of J. curcas by using SNP Marker.
    Sl. No. No. of accessions studied Country/Region Trait No. of primers used Reference
    1 148 India, North America, South America and Africa Oil yield 103 [32]
    2 273 Africa, Asia and America Genetic Diversity 8 [33]
    3 2 J.curcas and four Jatropha-related species. Thailand Phorbol esters 20 [31]
     | Show Table
    DownLoad: CSV

    3. Conclusions

    The review suggests that the analysis of J. curcas germplasm via different molecular markers have led to identification of low genetic diversity of accessions in the Asian region and also a close clustering of African and Asian accessions highlighting the existence of a common ancestor. The low genetic base of the African and Asian accessions could be attributed to less introduction from other areas, the prevelance of asexual reproduction and/or occurrence of apomix. According to the [2], J. curcas distribution and spread at the tropical belt was via the Cape Verde Islands, which was further confirmed by analysing diversity employing various molecular markers. The South American, Mexican and Meso-American regions show the existence of rich allelic diversity with useful and novel genes. These accessions can be an important resource for improving genetic base of J. curcas. Although molecular markers suggest variations, however, only limited quantitative genetic variability is predicted [27]. Hence, detailed evaluation of molecular diversity is the need of the hour, to identify divergent material for molecular breeding, construction of linkage maps, diversity analysis and QTL/association mapping for J. curcas.

    Contributions by authors

    All authors have equally contributed towards writing and have read and finalized the MS.

    Acknowledgements

    The authors wish to thank CSIR for funding the project MLP 0014. The authors also wish to thank the anonymous reviewers for critically evaluating the manuscript and providing valuable suggestions which helped in refining the manuscript. This manuscript bears PRIS registration no. 107/2017 of CSIR-CSMCRI.

    Conflict of interest

    The authors declare there is no conflict of interest.



    Conflict of interest


    The authors declare no conflict of interest.

    [1] Akdis M, Akdis CA (2014) Mechanisms of allergen-specific immunotherapy: multiple suppressor factors at work in immune tolerance to allergens. J Allergy Clin Immunol 133: 621-631. https://doi.org/10.1016/j.jaci.2013.12.1088
    [2] Buckley CD, McGettrick HM (2018) Leukocyte trafficking between stromal compartments: lessons from rheumatoid arthritis. Nat Rev Rheumatol 14: 476-487. https://doi.org/10.1038/s41584-018-0042-4
    [3] Kidd P (2003) Th1/Th2 balance: the hypothesis, its limitations, and implications for health and disease. Altern Med Rev 8: 223-246.
    [4] Romagnani S (2004) Immunologic influences on allergy and the TH1/TH2 balance. J Allergy Clin Immunol 113: 395-400. https://doi.org/10.1016/j.jaci.2003.11.025
    [5] Lee GR, Kim ST, Spilianakis CG, et al. (2006) T helper cell differentiation: regulation by cis elements and epigenetics. Immunity 24: 369-379. https://doi.org/10.1016/j.immuni.2006.03.007
    [6] Matsuzaki J, Tsuji T, Imazeki I, et al. (2005) Immunosteroid as a regulator for Th1/Th2 balance: its possible role in autoimmune diseases. Autoimmunity 38: 369-375. https://doi.org/10.1080/08916930500124122
    [7] Ngoc PL, Gold DR, Tzianabos AO, et al. (2005) Cytokines, allergy, and asthma. Curr Opin Allergy Clin Immunol 5: 161-166. https://doi.org/10.1097/01.all.0000162309.97480.45
    [8] Podbielska M, Banik NL, Kurowska E, et al. (2013) Myelin recovery in multiple sclerosis: the challenge of remyelination. Brain Sci 3: 1282-1324. https://doi.org/10.3390/brainsci3031282
    [9] Arellano G, Acuña E, Reyes LI, et al. (2017) Th1 and Th17 cells and associated cytokines discriminate among clinically isolated syndrome and multiple sclerosis phenotypes. Front Immunol 8: 753. https://doi.org/10.3389/fimmu.2017.00753
    [10] Wang K, Song F, Fernandez-Escobar A, et al. (2018) The properties of cytokines in multiple sclerosis: pros and cons. Am J Med Sci 356: 552-560. https://doi.org/10.1016/j.amjms.2018.08.018
    [11] Hirahara K, Nakayama T (2016) CD4+ T-cell subsets in inflammatory diseases: beyond the Th1/Th2 paradigm. Int Immunol 28: 163-171. https://doi.org/10.1093/intimm/dxw006
    [12] Wambre E, Bajzik V, DeLong JH, et al. (2017) A phenotypically and functionally distinct human TH2 cell subpopulation is associated with allergic disorders. Sci Transl Med 9: eaam9171. https://doi.org/10.1126/scitranslmed.aam9171
    [13] Tang C, Inman MD, van Rooijen N, et al. (2001) Th type 1-stimulating activity of lung macrophages inhibits Th2-mediated allergic airway inflammation by an IFN-gamma-dependent mechanism. J Immunol 166: 1471-1481. https://doi.org/10.4049/jimmunol.166.3.1471
    [14] Tang L, Benjaponpitak S, DeKruyff RH, et al. (1998) Reduced prevalence of allergic disease in patients with multiple sclerosis is associated with enhanced IL-12 production. J Allergy Clin Immunol 102: 428-435. https://doi.org/10.1016/S0091-6749(98)70131-9
    [15] Okada H, Kuhn C, Feillet H, et al. (2010) The “hygiene hypothesis” for autoimmune and allergic diseases: an update. Clin Exp Immunol 160: 1-9. https://doi.org/10.1111/j.1365-2249.2010.04139.x
    [16] Bach JF (2002) The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med 347: 911-920. https://doi.org/10.1056/NEJMra020100
    [17] Cunniffe N, Coles A (2021) Promoting remyelination in multiple sclerosis. J Neurol 268: 30-44. https://doi.org/10.1007/s00415-019-09421-x
    [18] Lazibat I, Rubinić-Majdak M, Županić S (2018) Multiple sclerosis: new aspects of immunopathogenesis. Acta Clin Croat 57: 352-361. https://doi.org/10.20471/acc.2018.57.02.17
    [19] Yamout B, Alroughani R (2018) Multiple sclerosis. Semin Neurol 38: 212-225. https://doi.org/10.1055/s-0038-1649502
    [20] Dobson R, Giovannoni G (2019) Multiple sclerosis—a review. Eur J Neurol 26: 27-40. https://doi.org/10.1111/ene.13819
    [21] Walton C, King R, Rechtman L, et al. (2020) Rising prevalence of multiple sclerosis worldwide: Insights from the Atlas of MS, third edition. Mult Scler 26: 1816-1821. https://doi.org/10.1177/1352458520970841
    [22] Filippi M, Bar-Or A, Piehl F, et al. (2018) Multiple sclerosis. Nat Rev Dis Primers 4: 43. https://doi.org/10.1038/s41572-018-0041-4
    [23] Lassmann H, Brück W, Lucchinetti CF (2007) The immunopathology of multiple sclerosis: an overview. Brain Pathol 17: 210-218. https://doi.org/10.1111/j.1750-3639.2007.00064.x
    [24] Kearney H, Altmann DR, Samson RS, et al. (2015) Cervical cord lesion load is associated with disability independently from atrophy in MS. Neurology 84: 367-373. https://doi.org/10.1212/WNL.0000000000001186
    [25] Schiess N, Calabresi PA (2016) Multiple sclerosis. Semin Neurol 36: 350-356. https://doi.org/10.1055/s-0036-1585456
    [26] Dendrou CA, Fugger L, Friese MA (2015) Immunopathology of multiple sclerosis. Nat Rev Immunol 15: 545-558. https://doi.org/10.1038/nri3871
    [27] Amato MP, Ponziani G, Siracusa G, et al. (2001) Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Arch Neurol-Chicago 58: 1602-1606. https://doi.org/10.1001/archneur.58.10.1602
    [28] Oh J, Vidal-Jordana A, Montalban X (2018) Multiple sclerosis: clinical aspects. Curr Opin Neurol 31: 752-759. https://doi.org/10.1097/WCO.0000000000000622
    [29] McGinley MP, Goldschmidt CH, Rae-Grant AD (2021) Diagnosis and treatment of multiple sclerosis: a review. JAMA 325: 765-779. https://doi.org/10.1001/jama.2020.26858
    [30] Przybek J, Gniatkowska I, Mirowska-Guzel D, et al. (2015) Evolution of diagnostic criteria for multiple sclerosis. Neurol Neurochir Pol 49: 313-321. https://doi.org/10.1016/j.pjnns.2015.07.006
    [31] Milo R, Miller A (2014) Revised diagnostic criteria of multiple sclerosis. Autoimmun Rev 13: 518-524. https://doi.org/10.1016/j.autrev.2014.01.012
    [32] Garg N, Smith TW (2015) An update on immunopathogenesis, diagnosis, and treatment of multiple sclerosis. Brain Behav 5: e00362. https://doi.org/10.1002/brb3.362
    [33] Klineova S, Lublin FD (2018) Clinical course of multiple sclerosis. Cold Spring Harb Perspect Med 8: a028928. https://doi.org/10.1101/cshperspect.a028928
    [34] Hart FM, Bainbridge J (2016) Current and emerging treatment of multiple sclerosis. Am J Manag Care 22: s159-s170.
    [35] Baecher-Allan C, Kaskow BJ, Weiner HL (2018) Multiple sclerosis: mechanisms and immunotherapy. Neuron 97: 742-768. https://doi.org/10.1016/j.neuron.2018.01.021
    [36] Alfredsson L, Olsson T (2019) Lifestyle and environmental factors in multiple sclerosis. Cold Spring Harb Perspect Med 9: a028944. https://doi.org/10.1101/cshperspect.a028944
    [37] Selter RC, Hemmer B (2013) Update on immunopathogenesis and immunotherapy in multiple sclerosis. ImmunoTargets Ther 2: 21-30. https://doi.org/10.2147/ITT.S31813
    [38] Baxter AG (2007) The origin and application of experimental autoimmune encephalomyelitis. Nat Rev Immunol 7: 904-912. https://doi.org/10.1038/nri2190
    [39] Kuerten S, Lichtenegger FS, Faas S, et al. (2006) MBP-PLP fusion protein-induced EAE in C57BL/6 mice. J Neuroimmunol 177: 99-111. https://doi.org/10.1016/j.jneuroim.2006.03.021
    [40] Derdelinckx J, Cras P, Berneman ZN, et al. (2021) Antigen-specific treatment modalities in MS: The past, the present, and the future. Front Immunol 12: 624685. https://doi.org/10.3389/fimmu.2021.624685
    [41] D'Angelo C, Reale M, Costantini E, et al. (2018) Profiling of canonical and non-traditional cytokine levels in interferon-β-treated relapsing-remitting-multiple sclerosis patients. Front Immunol 9: 1240. https://doi.org/10.3389/fimmu.2018.01240
    [42] Marchetti L, Engelhardt B (2020) Immune cell trafficking across the blood-brain barrier in the absence and presence of neuroinflammation. Vasc Biol 2: H1-H18. https://doi.org/10.1530/VB-19-0033
    [43] Gold R, Wolinsky JS (2011) Pathophysiology of multiple sclerosis and the place of teriflunomide. Acta Neurol Scand 124: 75-84. https://doi.org/10.1111/j.1600-0404.2010.01444.x
    [44] Holman DW, Klein RS, Ransohoff RM (2011) The blood-brain barrier, chemokines and multiple sclerosis. Biochim Biophys Acta 1812: 220-230. https://doi.org/10.1016/j.bbadis.2010.07.019
    [45] Sonar SA, Lal G (2018) Blood-brain barrier and its function during inflammation and autoimmunity. J Leukocyte Biol 103: 839-853. https://doi.org/10.1002/JLB.1RU1117-428R
    [46] Thompson AJ, Baranzini SE, Geurts J, et al. (2018) Multiple sclerosis. Lancet 391: 1622-1636. https://doi.org/10.1016/S0140-6736(18)30481-1
    [47] Piehl F (2021) Current and emerging disease-modulatory therapies and treatment targets for multiple sclerosis. J Intern Med 289: 771-791. https://doi.org/10.1111/joim.13215
    [48] Claes N, Fraussen J, Stinissen P, et al. (2015) B cells are multifunctional players in multiple sclerosis pathogenesis: Insights from therapeutic interventions. Front Immunol 6: 642. https://doi.org/10.3389/fimmu.2015.00642
    [49] Milo R (2019) Therapies for multiple sclerosis targeting B cells. Croat Med J 60: 87-98. https://doi.org/10.3325/cmj.2019.60.87
    [50] McFarland HF, Martin R (2007) Multiple sclerosis: a complicated picture of autoimmunity. Nat Immunol 8: 913-919. https://doi.org/10.1038/ni1507
    [51] Inglese M (2006) Multiple sclerosis: new insights and trends. Am J Neuroradiol 27: 954-957.
    [52] Voet S, Prinz M, van Loo G (2019) Microglia in central nervous system inflammation and multiple sclerosis pathology. Trends Mol Med 25: 112-123. https://doi.org/10.1016/j.molmed.2018.11.005
    [53] Strik M, Cofré Lizama LE, Shanahan CJ, et al. (2021) Axonal loss in major sensorimotor tracts is associated with impaired motor performance in minimally disabled multiple sclerosis patients. Brain Commun 3: fcab032. https://doi.org/10.1093/braincomms/fcab032
    [54] Akdis CA (2006) Allergy and hypersensitivity: mechanisms of allergic disease. Curr Opin Immunol 18: 718-726. https://doi.org/10.1016/j.coi.2006.09.016
    [55] Murphy K, Travers P, Walport M (2008) Allergy and hypersensitivity. Janeway's Immunobiology . UK: Garland Science. https://doi.org/10.1007/978-3-8274-2219-4
    [56] Simon D (2018) Recent advances in clinical allergy and immunology. Int Arch Allergy Imm 177: 324-333. https://doi.org/10.1159/000494931
    [57] Kumar Y, Bhatia A (2013) Immunopathogenesis of allergic disorders: current concepts. Expert Rev Clin Immunol 9: 211-226. https://doi.org/10.1586/eci.12.104
    [58] Vaillant AAJ, Vashisht R, Zito PM (2022) Immediate hypersensitivity reactions In: StatPearls, Treasure Island (FL): StatPearls Publishing.
    [59] Breiteneder H, Peng YQ, Agache I, et al. (2020) Biomarkers for diagnosis and prediction of therapy responses in allergic diseases and asthma. Allergy 75: 3039-3068. https://doi.org/10.1111/all.14582
    [60] Galli SJ, Tsai M, Piliponsky AM (2008) The development of allergic inflammation. Nature 454: 445-454. https://doi.org/10.1038/nature07204
    [61] Yao Y, Chen CL, Yu D, et al. (2021) Roles of follicular helper and regulatory T cells in allergic diseases and allergen immunotherapy. Allergy 76: 456-470. https://doi.org/10.1111/all.14639
    [62] Muñoz-Carrillo JL, Castro-García FP, Chávez-Rubalcaba F, et al. (2018) Immune system disorders: hypersensitivity and autoimmunity. Immunoregulatory Aspects of Immunotherapy . London: InTechOpen 1-30. https://doi.org/10.5772/intechopen.75794
    [63] Remington B, Broekman HCH, Blom WM, et al. (2018) Approaches to assess IgE mediated allergy risks (sensitization and cross-reactivity) from new or modified dietary proteins. Food Chem Toxicol 112: 97-107. https://doi.org/10.1016/j.fct.2017.12.025
    [64] Kanagaratham C, El Ansari YS, Lewis OL, et al. (2020) IgE and IgG antibodies as regulators of mast cell and basophil functions in food allergy. Front Immunol 11: 603050. https://doi.org/10.3389/fimmu.2020.603050
    [65] Janeway CA, Travers P, Walport M, et al. (2001) Immunobiology: The immune system in health and disease. Effector Mechanisms in Allergic Reactions . New York: Garland Science.
    [66] Kitaura J, Song J, Tsai M, et al. (2003) Evidence that IgE molecules mediate a spectrum of effects on mast cell survival and activation via aggregation of the FcepsilonRI. P Natl Acad Sci USA 100: 12911-12916. https://doi.org/10.1073/pnas.1735525100
    [67] Dispenza MC (2019) Classification of hypersensitivity reactions. Allergy Asthma Proc 40: 470-473. https://doi.org/10.2500/aap.2019.40.4274
    [68] Miyake K, Karasuyama H (2017) Emerging roles of basophils in allergic inflammation. Allergol Int 66: 382-391. https://doi.org/10.1016/j.alit.2017.04.007
    [69] Prussin C, Metcalfe DD (2006) 5. IgE, mast cells, basophils, and eosinophils. J Allergy Clin Immunol 117: S450-S456. https://doi.org/10.1016/j.jaci.2005.11.016
    [70] Sampson AP (2000) The role of eosinophils and neutrophils in inflammation. Clin Exp Allergy 30: 22-27. https://doi.org/10.1046/j.1365-2222.2000.00092.x
    [71] Drazdauskaitė G, Layhadi JA, Shamji MH (2020) Mechanisms of allergen immunotherapy in allergic rhinitis. Curr Allergy Asthma Rep 21: 2. https://doi.org/10.1007/s11882-020-00977-7
    [72] Akhouri S, House SA (2022) >Allergic rhinitis In: StatPearls, Treasure Island (FL): StatPearls Publishing.
    [73] Yu W, Freeland DMH, Nadeau KC (2016) Food allergy: immune mechanisms, diagnosis and immunotherapy. Nat Rev Immunol 16: 751-765. https://doi.org/10.1038/nri.2016.111
    [74] Iweala OI, Choudhary SK, Commins SP (2018) Food allergy. Curr Gastroenterol Rep 20: 17. https://doi.org/10.1007/s11894-018-0624-y
    [75] Peters RL, Krawiec M, Koplin JJ, et al. (2021) Update on food allergy. Pediatr Allergy Immu 32: 647-657. https://doi.org/10.1111/pai.13443
    [76] Rehman A, Amin F, Sadeeqa S (2018) Prevalence of asthma and its management: A review. J Pak Med Assoc 68: 1823-1827.
    [77] Ogeyingbo OD, Ahmed R, Gyawali M, et al. (2021) The relationship between vitamin D and asthma exacerbation. Cureus 13: e17279. https://doi.org/10.1111/pai.13443
    [78] Bush A (2019) Pathophysiological mechanisms of asthma. Front Pediatr 7: 68. https://doi.org/10.3389/fped.2019.00068
    [79] Nakamura Y, Tamaoki J, Nagase H, et al. (2020) Japanese guidelines for adult asthma. Allergol Int 69: 519-548. https://doi.org/10.1016/j.alit.2020.08.001
    [80] Bilò MB, Martini M, Tontini C, et al. (2021) Anaphylaxis. Eur Ann Allergy Clin Immunol 53: 4-17. https://doi.org/10.23822/EurAnnACI.1764-1489.158
    [81] Pflipsen MC, Colon KMV (2020) Anaphylaxis: recognition and management. Am Fam Physician 102: 355-362.
    [82] Hackett TL, Singhera GK, Shaheen F, et al. (2011) Intrinsic phenotypic differences of asthmatic epithelium and its inflammatory responses to respiratory syncytial virus and air pollution. Am J Resp Cell Mol 45: 1090-1100. https://doi.org/10.1165/rcmb.2011-0031OC
    [83] Siddiqui S, Johansson K, Joo A, et al. (2021) Epithelial miR-141 regulates IL-13-induced airway mucus production. JCI Insight 6: e139019. https://doi.org/10.1172/jci.insight.139019
    [84] Vercelli D (2008) Discovering susceptibility genes for asthma and allergy. Nat Rev Immunol 8: 169-182. https://doi.org/10.1038/nri2257
    [85] Akdis CA (2021) Does the epithelial barrier hypothesis explain the increase in allergy, autoimmunity and other chronic conditions?. Nat Rev Immunol 21: 739-751. https://doi.org/10.1038/s41577-021-00538-7
    [86] Kansen HM, Lebbink MA, Mul J, et al. (2020) Risk factors for atopic diseases and recurrent respiratory tract infections in children. Pediatr Pulm 55: 3168-3179. https://doi.org/10.1002/ppul.25042
    [87] D'Amato G, Chong-Neto HJ, Ortega OPM, et al. (2020) The effects of climate change on respiratory allergy and asthma induced by pollen and mold allergens. Allergy 75: 2219-2228. https://doi.org/10.1111/all.14476
    [88] Prescott S, Saffery R (2011) The role of epigenetic dysregulation in the epidemic of allergic disease. Clin Epigenetics 2: 223-232. https://doi.org/10.1007/s13148-011-0028-4
    [89] Wilson CB, Rowell E, Sekimata M (2009) Epigenetic control of T-helper-cell differentiation. Nat Rev Immunol 9: 91-105. https://doi.org/10.1038/nri2487
    [90] Thorburn AN, Macia L, Mackay CR (2014) Diet, metabolites, and “western-lifestyle” inflammatory diseases. Immunity 40: 833-842. https://doi.org/10.1016/j.immuni.2014.05.014
    [91] Yazdanbakhsh M, Kremsner PG, van Ree R (2002) Allergy, parasites, and the hygiene hypothesis. Science 296: 490-494. https://doi.org/10.1126/science.296.5567.490
    [92] Frei R, Lauener RP, Crameri R, et al. (2012) Microbiota and dietary interactions: an update to the hygiene hypothesis?. Allergy 67: 451-461. https://doi.org/10.1111/j.1398-9995.2011.02783.x
    [93] Raj D, Kabra SK, Lodha R (2014) Childhood obesity and risk of allergy or asthma. Immunol Allergy Clin 34: 753-765. https://doi.org/10.1016/j.iac.2014.07.001
    [94] Metsälä J, Lundqvist A, Virta LJ, et al. (2013) Mother's and offspring's use of antibiotics and infant allergy to cow's milk. Epidemiology 24: 303-309. https://doi.org/10.1097/EDE.0b013e31827f520f
    [95] Loh W, Tang MLK (2018) The epidemiology of food allergy in the global context. Int J Environ Res Public Health 15: 2043. https://doi.org/10.3390/ijerph15092043
    [96] Simon D (2019) Recent advances in clinical allergy and immunology 2019. Int Arch Allergy Imm 180: 291-305. https://doi.org/10.1159/000504364
    [97] Oro AS, Guarino TJ, Driver R, et al. (1996) Regulation of disease susceptibility: decreased prevalence of IgE-mediated allergic disease in patients with multiple sclerosis. J Allergy Clin Immunol 97: 1402-1408. https://doi.org/10.1016/S0091-6749(96)70210-5
    [98] Cameron MH, Nilsagard Y (2018) Balance, gait, and falls in multiple sclerosis. Handb Clin Neurol 159: 237-250. https://doi.org/10.1016/B978-0-444-63916-5.00015-X
    [99] Rosiak K, Zagożdżon P (2017) Quality of life and social support in patients with multiple sclerosis. Psychiatr Pol 51: 923-935. https://doi.org/10.12740/PP/64709
    [100] Beiske AG, Naess H, Aarseth JH, et al. (2007) Health-related quality of life in secondary progressive multiple sclerosis. Mult Scler 13: 386-392. https://doi.org/10.1177/13524585070130030101
    [101] Lock C, Hermans G, Pedotti R, et al. (2002) Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis. Nat Med 8: 500-508. https://doi.org/10.1038/nm0502-500
    [102] Pedotti R, DeVoss JJ, Youssef S, et al. (2003) Multiple elements of the allergic arm of the immune response modulate autoimmune demyelination. P Natl Acad Sci USA 100: 1867-1872. https://doi.org/10.1073/pnas.252777399
    [103] Musio S, Gallo B, Scabeni S, et al. (2006) A key regulatory role for histamine in experimental autoimmune encephalomyelitis: disease exacerbation in histidine decarboxylase-deficient mice. J Immunol 176: 17-26. https://doi.org/10.4049/jimmunol.176.1.17
    [104] Lapilla M, Gallo B, Martinello M, et al. (2011) Histamine regulates autoreactive T cell activation and adhesiveness in inflamed brain microcirculation. J Leukocyte Biol 89: 259-267. https://doi.org/10.1189/jlb.0910486
    [105] Gregory GD, Robbie-Ryan M, Secor VH, et al. (2005) Mast cells are required for optimal autoreactive T cell responses in a murine model of multiple sclerosis. Eur J Immunol 35: 3478-3486. https://doi.org/10.1002/eji.200535271
    [106] Alonso A, Hernán MA, Ascherio A (2008) Allergy, family history of autoimmune diseases, and the risk of multiple sclerosis. Acta Neurol Scand 117: 15-20.
    [107] Alonso A, Jick SS, Hernán MA (2006) Allergy, histamine 1 receptor blockers, and the risk of multiple sclerosis. Neurology 66: 572-575. https://doi.org/10.1212/01.wnl.0000198507.13597.45
    [108] Karimi P, Modarresi SZ, Sahraian MA, et al. (2013) The relation of multiple sclerosis with allergy and atopy: a case control study. Iran J Allergy Asthma Immunol 12: 182-189.
    [109] Krishna MT, Subramanian A, Adderley NJ, et al. (2019) Allergic diseases and long-term risk of autoimmune disorders: longitudinal cohort study and cluster analysis. Eur Respir J 54: 1900476. https://doi.org/10.1183/13993003.00476-2019
    [110] Mansouri B, Asadollahi S, Heidari K, et al. (2014) Risk factors for increased multiple sclerosis susceptibility in the Iranian population. J Clin Neurosci 21: 2207-2211. https://doi.org/10.1016/j.jocn.2014.04.020
    [111] Chen J, Taylor B, Winzenberg T, et al. (2020) Comorbidities are prevalent and detrimental for employment outcomes in people of working age with multiple sclerosis. Mult Scler 26: 1550-1559. https://doi.org/10.1177/1352458519872644
    [112] Lo LMP, Taylor BV, Winzenberg T, et al. (2021) Comorbidity patterns in people with multiple sclerosis: A latent class analysis of the Australian Multiple Sclerosis Longitudinal Study. Eur J Neurol 28: 2269-2279. https://doi.org/10.1111/ene.14887
    [113] Hill E, Abboud H, Briggs FBS (2019) Prevalence of asthma in multiple sclerosis: A United States population-based study. Mult Scler Relat Disord 28: 69-74. https://doi.org/10.1016/j.msard.2018.12.012
    [114] Sorensen A, Conway DS, Briggs FBS (2021) Characterizing relapsing remitting multiple sclerosis patients burdened with hypertension, hyperlipidemia, and asthma. Mult Scler Relat Disord 53: 103040. https://doi.org/10.1016/j.msard.2021.103040
    [115] Tremlett HL, Evans J, Wiles CM, et al. (2002) Asthma and multiple sclerosis: an inverse association in a case-control general practice population. QJM 95: 753-756. https://doi.org/10.1093/qjmed/95.11.753
    [116] Bergamaschi R, Villani S, Crabbio M, et al. (2009) Inverse relationship between multiple sclerosis and allergic respiratory diseases. Neurol Sci 30: 115-118. https://doi.org/10.1007/s10072-009-0036-8
    [117] Sahraian MA, Jafarian S, Sheikhbahaei S, et al. (2013) Respiratory tract rather than cutaneous atopic allergy inversely associate with multiple sclerosis: a case-control study. Clin Neurol Neurosur 115: 2099-2102. https://doi.org/10.1016/j.clineuro.2013.07.028
    [118] Pedotti R, Farinotti M, Falcone C, et al. (2009) Allergy and multiple sclerosis: a population-based case-control study. Mult Scler 15: 899-906. https://doi.org/10.1177/1352458509106211
    [119] Ren J, Ni H, Kim M, et al. (2017) Allergies, antibiotics use, and multiple sclerosis. Curr Med Res Opin 33: 1451-1456. https://doi.org/10.1080/03007995.2017.1325575
    [120] Skaaby T, Husemoen LL, Thuesen BH, et al. (2015) Specific IgE positivity against inhalant allergens and development of autoimmune disease. Autoimmunity 48: 282-288. https://doi.org/10.3109/08916934.2014.1003640
    [121] Manouchehrinia A, Edwards LJ, Roshanisefat H, et al. (2015) Multiple sclerosis course and clinical outcomes in patients with comorbid asthma: a survey study. BMJ Open 5: e007806. https://doi.org/10.1136/bmjopen-2015-007806
    [122] Ponsonby AL, Dwyer T, van der Mei I, et al. (2006) Asthma onset prior to multiple sclerosis and the contribution of sibling exposure in early life. Clin Exp Immunol 146: 463-470. https://doi.org/10.1111/j.1365-2249.2006.03235.x
    [123] Hughes AM, Lucas RM, McMichael AJ, et al. (2013) Early-life hygiene-related factors affect risk of central nervous system demyelination and asthma differentially. Clin Exp Immunol 172: 466-474. https://doi.org/10.1111/cei.12077
    [124] Lopez CM, Yarrarapu SNS, Mendez MD (2022) Food allergies In: StatPearls, Treasure Island (FL): StatPearls Publishing.
    [125] Yu JW, Pekeles G, Legault L, et al. (2006) Milk allergy and vitamin D deficiency rickets: a common disorder associated with an uncommon disease. Ann Allerg Asthma Im 96: 615-619. https://doi.org/10.1016/S1081-1206(10)63558-2
    [126] Correale J, Ysrraelit MC, Gaitán MI (2009) Immunomodulatory effects of vitamin D in multiple sclerosis. Brain 132: 1146-1160. https://doi.org/10.1093/brain/awp033
    [127] Ramagopalan SV, Dyment DA, Guimond C, et al. (2010) Childhood cow's milk allergy and the risk of multiple sclerosis: a population based study. J Neurol Sci 291: 86-88. https://doi.org/10.1016/j.jns.2009.10.021
    [128] Pichler J, Gerstmayr M, Szepfalusi Z, et al. (2002) 1 alpha,25(OH)2D3 inhibits not only Th1 but also Th2 differentiation in human cord blood T cells. Pediatr Res 52: 12-18. https://doi.org/10.1203/00006450-200207000-00005
    [129] Sakaguchi S, Yamaguchi T, Nomura T, et al. (2008) Regulatory T cells and immune tolerance. Cell 133: 775-787. https://doi.org/10.1016/j.cell.2008.05.009
    [130] Mirzakhani H, Al-Garawi A, Weiss ST, et al. (2015) Vitamin D and the development of allergic disease: how important is it?. Clin Exp Allergy 45: 114-125. https://doi.org/10.1111/cea.12430
    [131] Danikowski KM, Jayaraman S, Prabhakar BS (2017) Regulatory T cells in multiple sclerosis and myasthenia gravis. J Neuroinflammation 14: 117. https://doi.org/10.1186/s12974-017-0892-8
    [132] Ashtari F, Jamshidi F, Shoormasti RS, et al. (2013) Cow's milk allergy in multiple sclerosis patients. J Res Med Sci 18: S62-S65.
    [133] Ashtari F, Jamshidi F, Shoormasti RS, et al. (2013) Fish and egg specific immunoglobin e in multiple sclerosis patients. Int J Prev Med 4: S185-S188.
    [134] Bourne T, Waltz M, Casper TC, et al. (2017) Evaluating the association of allergies with multiple sclerosis susceptibility risk and disease activity in a pediatric population. J Neurol Sci 375: 371-375. https://doi.org/10.1016/j.jns.2017.02.041
    [135] Fakih R, Diaz-Cruz C, Chua AS, et al. (2019) Food allergies are associated with increased disease activity in multiple sclerosis. J Neurol Neurosur Ps 90: 629-635. https://doi.org/10.1136/jnnp-2018-319301
    [136] Albatineh AN, Alroughani R, Al-Temaimi R (2020) Predictors of multiple sclerosis severity score in patients with multiple sclerosis. Int J MS Care 22: 233-238. https://doi.org/10.7224/1537-2073.2019-054
    [137] Parodi B, de Rosbo NK (2021) The gut-brain axis in multiple sclerosis. Is its dysfunction a pathological trigger or a consequence of the disease?. Front Immunol 12: 718220. https://doi.org/10.3389/fimmu.2021.718220
    [138] Agirman G, Yu KB, Hsiao EY (2021) Signaling inflammation across the gut-brain axis. Science 374: 1087-1092. https://doi.org/10.1126/science.abi6087

  • This article has been cited by:

    1. Romero de Lima Souza, Luiz Antônio dos Santos Dias, Thais Roseli Corrêa, Eveline Teixeira Caixeta, Erika da Costa Fernandes, Dandara Rêgo Muniz, Lucas Barbosa de Castro Rosmaninho, Poliane Marcele Ribeiro Cardoso, Genetic variability revealed by microsatellite markers in a germplasm collection of Jatropha curcas L. in Brazil: an important plant for biofuels, 2019, 19, 1984-7033, 337, 10.1590/1984-70332019v19n3a46
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
AIMS Allergy and Immunology
0.4

Metrics

Article views(4597) PDF downloads(148) Cited by(2)

Article has an altmetric score of 1
Article has an altmetric score of 1
Preview PDF
Download XML
Export Citation
Article outline
Abstract
References

Figures and Tables

Figures(1)  /  Tables(2)

Other Articles By Authors

Related pages

Tools

Copyright © AIMS Press

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog