Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
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\r\n\tProtein kinase driven phosphorylation is one of the vital mechanisms controlling intracellular signalling pathways that regulate many cellular processes, such as cell division, proliferation, growth, survival and apoptosis. Alteration of different protein kinases can result in remarkable changes in these processes. Moreover, these protein kinases are frequently recognized as oncogenic and can be crucial for the survival and spread of cancer cells. Because of the fundamental role of protein kinases in cell biology and their function in numerous sarcomas and cancers, an intensive search for new kinase inhibitors in academia and industries has been enduring for the last two decades. Protein kinase has become the most imperative and commercial class of drug target which is attracting pharmaceutical industries to spend 30 % of their current research investments only in developing kinase inhibitors for various therapeutic implications. This is exemplified by the fact that 75 drugs targeting protein kinase have been clinically approved to date. More than 100 kinase inhibitors are in the final stages of development and likely to be approved in the coming years. There is plenty of scope to work in the area of exploring protein kinase as only about 10 % of kinases have been studied extensively to date. The development of kinase inhibitors is expected to be at the forefront of medicine for the foreseeable future.
\r\n
\r\n\tIn this context, this book intends to provide a collection of research and review articles from the experts focusing on protein kinases signalling pathways as a molecular drug target. Various chapters on the mechanism of action and antitumor activity of protein kinase inhibitors on various cancer types will also be presented. New opportunities, challenges and future perspectives in the context of the function of protein kinases will also be discussed in different chapters.
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His major area of research interests are drug-design, polymer-drug conjugates for targeted delivery to cancerous cells and CNS, antimalarial therapeutic agents, natural product chemistry and green chemistry approaches for chemical synthesis. Dr. Singh has over 15 years of teaching experience and guided 01 PhD and 18 PG students. He is currently guiding 02 PhDs and 01 M. Pharmacy students. He has published more than 60 peer-reviewed SCI-indexed scientific research papers of total impact factor more than 100 in various Chemistry and Pharmacy Journals including the European Journal of Medicinal Chemistry, Biorganic Chemistry, Biomedicine and Pharmacotherapy, European Journal of Pharmaceutical Sciences, Mini-Reviews in Medicinal Chemistry, Pharmaceutical Research, Medicinal Chemistry, Bentham, J. Enzyme Inh. Med Chem. (Informa Healthcare), Res. Chem. Intermediate (Springer), Arabian Journal of Chemistry, etc as main or corresponding author. He currently serves on Editorial Advisory Board Member of 09 Peer-reviewed International Journals including SCI indexed MRMC and PeerJ. He has received Publon Award 2016, 2017 for top reviewer and 'Publon Excellent Peer Reviewer Award” for outstanding reviewing more than 150 research papers of different International Journals of ACS, RSC, Springer, Elsevier, Dove, Informa, and Bentham of Impact Factor varies from 1.0 to 9.5. He has also to his credit 46 National and International Conference Abstracts, 2 Book, 5 Best Paper Presentation Awards, 1 Travel grants to attend Int. Conf. and 5 Research Projects funded by Govt. Agencies, India. He is also on the panel of International Reviewer for reviewing Research Proposal for Royal Society Grants. 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1. Introduction
The golden standard for risk assessment of health effects from ionizing radiation are mortality data from the LSS (Life Span Study) cohort of survivors after the atomic bombings in Hiroshima and Nagasaki in 1945. Based on epidemiological data from the 93,000 survivors, the currently accepted linear nontreshold (LNT) risk model has been established. There are however several important shortcomings of this model. Firstly the LSS cohort is mainly based on mortality data. It is well-known that mortality data is inexact in diagnostic criteria, mostly lacking autopsy data. Cancer registries for cancer incidence data using histologically verified sampling have better diagnostic accuracy. Secondly the LSS cohort is based on acute exposure at the time of the bombing, but very little chronic exposure due to local fallout. Most radioactivity was spread in the atmosphere after the bombings giving relatively little local fallout. Thirdly the LNT model is poorly verified in the so called low dose region (<100 mGy/mSv). A recent follow-up of the LSS-cohort after 52 years point at uncertainties of the shape of the dose response curve supporting a linear-quadratic model [1]. Perhaps the most debated detail about the LNT model is the introduction of a risk reduction for the low dose region. The so called “dose and dose-rate effectiveness factor”, DDREF, suggest that the risk of malignancy should be lowered by a factor of 2 in the low dose region (<100 mSv) introduced by the International Commission on Radiological Protection (ICRP). The theoretical argument for this arbitrary halving of risk estimates was that cellular repair mechanisms ought to be more efficient at low doses and low dose-rates. Perhaps a corrected radiation risk model will be considered in the light of new data and based on both physical, epidemiological and biologic data. Most other biological, medical and toxicological systems have exponential or s-shaped relationships between exposure and outcome, instead of linear. Models for radiation protection are also made mainly for regulatory purposes and do not directly reflect risk of disease, especially for exposures to populations in the low dose region. Therefore, nuclear accidents, such as in Harrisburg, Chernobyl or Fukushima, differ substantially from the conditions on which the LSS cohort and the LNT model are based. Other approaches using national health databases and environmental monitoring to detect health risks might be useful.
2. Assessment of dose
2.1. Uncertainties in dose measurements
The currently used dose estimates, such as equivalent dose or effective dose, are constructions used for radiation protection, focusing on the regulatory use in standards for workers but are seldom useful for members of the public. These dose estimates make use of several weighing factor, depending on type of radiation and the organ affected.
However, environmental exposure are often complex, including multiple tissues or whole body exposure. It is also often a combination of both external and internal exposure. For that purpose the International Commission on Radiological Protection (ICRP) recommends a weighing factor for effective dose, specific for 14 different organ/tissue categories. This weighing factor is based on years of life lost and also genetic effects, rather than the biological risk of cancer development. As a consequence thyroid cancer is weighed one third of bone marrow malignancy, breast cancer and stomach cancer, which is not related to the biological risk of developing a malignancy from a certain radiation dose.
The currently used dose estimates are primarily not constructed to be used in epidemiological studies on cancer incidence, since the weighing factors are evaluating the severity of health outcomes, mortality and even genetic effects. Therefore a discussion should be introduced about what dose risk estimates might be more suitable for epidemiological studies of cancer incidence, for example using absorbed dose energy with both radiophysically and biologically based correction factors.
2.2. Alternative biological dosimetry techniques
There are no biological markers for the assessment of low dose or low dose-rate exposes to humans [2]. After receiving larger external doses, nail and tooth enamel magnetic resonance analysis might be used, though with a large inaccuracy of dosimetry of 30–50 mGy, high costs and advanced laboratory equipment limiting the practical use [3]. Examples of other physical and biological dosimetry techniques being evaluated, though not yet practically applicable are: protein biomarkers, hematological changes, chromosomal damages, micronuclei and thermoluminescence [4].
2.3. Indirect dose assessment in non-occupational populations
Personal dosimetry is mainly used for the protection of radiation workers to ensure that the exposure to ionizing radiation is kept within dose equivalent limits. When a larger population is exposed to radionuclides dosimeters are not available in sufficiently large numbers. An exception is the internal dose to the thyroid gland which can be accessed via direct thyroid scans of radio-iodine uptake. The external dose contribution and the contributions from other radionuclides are more difficult to assess, especially multi-organ or whole-body doses.
Instead environmental monitoring from both stationary and mobile dosimeters can map geographical patterns of contamination. From these environmental data indirect dose assessments can be calculated for larger populations. External radiation doses to a population can be estimated via deposition maps, meteorological modeling or distance from the radiation source, including factors such as shielding. Internal doses can be measured for a limited amount of subjects via whole-body counting or thyroid scanners, but for most of the population estimations of doses can be made based on residence, inhalation and ingestion assumptions. An example of a well-developed model for indirect dose assessment is the Radiation Effects Research Foundation (RERF) dose estimation model (DS02R1) from an atomic bomb. The model takes into account distance to the hypocenter, shielding from buildings and terrain [1].
2.4. An example of indirect dose assessment among Swedish hunters
Using transfer factors based on whole-body counting from the Swedish population an example of a model for the assessment of life-time (70 years) extra dose from the Chernobyl fall-out was calculated for 16,000 hunters with families in the three mostly contaminated counties in Sweden. An extra life-time dose up to 9.4 mSv was calculated, depending on the factors age, gender and habitat. About 75% of the life-time dose was from internal contamination from food [5].
If only the external dose contribution is accounted for during the first year the relative dose contribution from so called short-lived fission products was 36%, 37% for cesium-134 and 27% for cesium-137. After 70 years the proportions were 11%, 29% and 60% respectively [6].
2.5. Dose assessment among reindeer herders
The highest radionuclide exposure to a population outside the former Soviet Union after the Chernobyl accident was received among Nordic reindeer herders, receiving about 10–100 times higher doses than urban populations, according to Swedish whole-body counts [7]. The reindeer livelihood was severely affected by the Chernobyl fall-out. Due to radiation protection actions about 80% of the Swedish reindeer meat was destroyed the first years following the accident, and the slaughter had to be moved from winter season to summer, when browse was less contaminated. Middle aged reindeer herdsmen also received similar or even higher doses from the global fall-out during the 1950ies and 1960ies making them exposed twice [8]. According to population data from Statistics Sweden there are only about 700 reindeer herders by occupation in Sweden, which gives too low power for epidemiological analyses on cancer incidence, but a combined study from all Nordic countries might be possible.
3. Use of national health data registries
Although the LSS-cohort outcome is the supposedly golden standard for cancer risk there is a fundamental shortcoming due to lack of early data covering the Hiroshima and Nagasaki prefecture populations, since prefecture cancer registries were not in use until 1958. Furthermore the LSS-cohort is mainly based on mortality data although cancer incidence registries usually are based on histological sampling with higher diagnostic accuracy. This gives uncertainties to the LSS-data concerning early health effects for the cancer risk models. In japan a “National Health Promotion” law put in place in Japan in the early 2000s said that prefectures must track illnesses including cancer. This law led to the introduction of some new cancer registries in Japan. The Fukushima prefecture begun a cancer registry in 2010 using a standardized database system governed by the Japanese National Cancer Center. But the data produced in the first few years the cancer registry was of poor quality and is still being developed by the year 2017. This is a great drawback for the estimation of health outcomes, including cancer, for the population of the Fukushima prefecture following the nuclear accident in 2011.
The lack of official health data or a national health data base were even more striking in the former Soviet union at the time of the Chernobyl accident in 1986. The absence of data for researchers has made follow-up of health outcomes difficult in the former Soviet states, though national cancer registries are now built up in Belarus, Ukraine and the Baltic states.
In the Nordic countries there are national cancer registries at the individual level covering all population. In Sweden a national cancer registry is in use since 1958 [9]. Good quality cancer registries make it possible to register changes in baseline incidences following environmental changes such as radio-nuclide releases to the population, especially as a complement when dosimetry is absent or very inexact.
3.1. The example of detecting increased cancer incidence in South Wales around Windscale
The first population study apart from the LSS-cohort showing a possible increased risk of cancer was in South Wales. From a fuel reprocessing plant at Windscale waste was discharged into the Irish See via a pipeline and deposition occurred in the sea bottom, fish and sea weed. The fission product ruthenium-106 was taken up very efficiently and concentrated in the sea weed Porphyra umbilicales. It was harvested and used in laver bread, consumed mainly in South Wales. The use had to be stopped. The activity in fish was mainly from cesium-137. When an ecosystem is contaminated with radionuclides and local food is the main source of internal exposure to radiation the individual doses to the population are very difficult to assess since food habits and lifestyle differ fundamentally between individuals and regions. Whole-body counting can be made to a small sample of the population, mainly concerning gamma-radiation from gamma-emitting nuclides and indirectly from alpha-emitters with gamma-decay, but has lower sensitivity for detecting the beta-radiation, such as from ruthenium-106. Therefore health surveillance via national cancer registries was fundamental to monitor the health effects to the population with an ecosystem is contaminated by radionuclides. Several epidemiological studies have shown increased incidences of cancer of the population around Windscale [10].
3.2. The example of detecting increased cancer incidence for people living at the Techa river
In 1949 the Mayak Production Association, located in the Southern Urals, started production of plutonium for the Soviet Nuclear weapons program. A cohort of 30,000 residents of 40 rural villages along the Techa river or the Chelyabinsk City with low-dose and low-dose-rate exposures have been followed for more than 50 years for incident cases of cancer. Individual radiation doses were based on geographic information of residence and food habits. Calculated external exposures were due to gamma rays from contamination of the soil and the internal exposures were assessed from expected consumption of water, milk and food containing uranium fission products. All solid cancers as a group were related to stomach doses ranging from 0 to 960 mGy with a mean of 60 mGy. Dose–response between estimated radiation dose and solid cancers and leukemia were shown with an excess relative risk (ERR) after exposure to 100 mGy of 0.08 [11].
3.3. The example of detecting increased incidence of thyroid cancer in Ukraine after the Chernobyl accident
Chemical composition, deposition, uptake and metabolism of iodine make thyroid dosimetry complicated, but direct measurement using a gamma-meter of the thyroid gland can be made. To estimate individual thyroid absorbed doses from radioiodine in the Ukrainian population from May–June 1986, more than 150,000 individual examinations were carried out by special dosimetric teams. The collective thyroid dose was 64,000 person-Gy, which theoretically could give about 300 extra cases of thyroid cancer [12].
Another study was performed on behalf of the International Agency for Research on Cancer (IARC). A population-based case–control study was designed of thyroid cancer among young people who lived in the areas that were heavily contaminated by the Chernobyl accident, Indirect dosimetry was performed based on data of the habitat and dietary habits of 1615 cases and controls aged 0–18 y at the time of the accident. A strong dose–response relationship was observed between estimated radiation dose to the thyroid received in childhood and thyroid cancer risk [13].
3.4. The example of detecting increased cancer incidence in Sweden after the Chernobyl accident
Sweden received the largest deposition of radionuclides outside the former USSR, where about 4.4% of the total Chernobyl fall-out was deposited [14]. Deposition was strongly dependent on local weathering giving highest deposition in coastal areas around the Bothnian sea. A food regulation program was introduced to assure that the annual extra dose did not exceed 1 mSv in the population. In a study indirect individual doses were assessed for 734,537 persons living in the three most contaminated counties in Sweden. Personal dosimetry could not be performed 30 years after the accident, so a cumulative exposure based on measured ground activity of cesium-137 of the residence of the subjects. A cumulative exposure estimate during 5 years following the accident was used as proxy for received dose. 82,495 cases of cancer were diagnosed from 1991 to 2010 and retrieved from the Swedish national cancer registry. A non-parametric dose–response could be shown between the deposition of cesum-137 and cancer incidence [15].
4. Conclusion
A paradigm shift is needed from the dominance of radiation protection to a more biologically based health risk assessment from ionizing radiation. Models for radiation protection are made for regulatory purposes and do not directly reflect the risk of disease. Also dose estimates are poorly applicable for risk assessment for populations exposed in the low dose region. Only to rely on technical surveillance could be insufficient. Instead other approaches using national health databases in combination with environmental monitoring could be more efficient for the detection of health risks. Medical surveillance and health registries are good complements, especially in the absence of dosimeter data, complex environmental exposures and when large populations are exposed. When nuclear facilities are in use national health registries could be the most sensitive source for the detection of increased cancer incidence and other disease from nuclear accidents or other emission of radionuclides to the environment. Apart from nuclear power plants possible exposure could emanate from uranium mining, fuel processing, nuclear waste processing and nuclear waste repositories.
\n',keywords:"cancer, health surveillance, ionizing radiation, nuclear accident, risk assessment",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/58556.pdf",chapterXML:"https://mts.intechopen.com/source/xml/58556.xml",downloadPdfUrl:"/chapter/pdf-download/58556",previewPdfUrl:"/chapter/pdf-preview/58556",totalDownloads:509,totalViews:141,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,dateSubmitted:"May 19th 2017",dateReviewed:"December 12th 2017",datePrePublished:null,datePublished:"February 28th 2018",dateFinished:null,readingETA:"0",abstract:"The currently established linear nontreshold (LNT) risk model is used for radiation protection and is actually not intended for risk assessment. Also dose concepts such as effective dose are constructions used for radiation protection, focusing on the regulatory use in standards for workers but is seldom useful for members of the public. Both the LNT model, as well as use of the concept effective dose, are also not applicable in the low dose area. An alternative method for public health risk assessment and disease surveillance can be the combination of environmental radiation monitoring and health databases. For example, after the Chernobyl accident, airborne measurements of cesium-137 gamma spectrum from the ground, activity data from food samples and high quality national health registries were used for the risk assessment of cancer development.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/58556",risUrl:"/chapter/ris/58556",book:{slug:"risk-assessment"},signatures:"Robert Wålinder",authors:[{id:"36169",title:"Dr.",name:"Robert",middleName:null,surname:"Wålinder",fullName:"Robert Wålinder",slug:"robert-walinder",email:"robert.walinder@medsci.uu.se",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Assessment of dose",level:"1"},{id:"sec_2_2",title:"2.1. Uncertainties in dose measurements",level:"2"},{id:"sec_3_2",title:"2.2. Alternative biological dosimetry techniques",level:"2"},{id:"sec_4_2",title:"2.3. Indirect dose assessment in non-occupational populations",level:"2"},{id:"sec_5_2",title:"2.4. An example of indirect dose assessment among Swedish hunters",level:"2"},{id:"sec_6_2",title:"2.5. Dose assessment among reindeer herders",level:"2"},{id:"sec_8",title:"3. Use of national health data registries",level:"1"},{id:"sec_8_2",title:"3.1. The example of detecting increased cancer incidence in South Wales around Windscale",level:"2"},{id:"sec_9_2",title:"3.2. The example of detecting increased cancer incidence for people living at the Techa river",level:"2"},{id:"sec_10_2",title:"3.3. The example of detecting increased incidence of thyroid cancer in Ukraine after the Chernobyl accident",level:"2"},{id:"sec_11_2",title:"3.4. The example of detecting increased cancer incidence in Sweden after the Chernobyl accident",level:"2"},{id:"sec_13",title:"4. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Grant EJ, Brenner A, Sugiyama H, Sakata R, Sadakane A, Utada M, et al. Solid cancer incidence among the life span study of atomic bomb survivors: 1958-2009. Radiation Research. 2017 May;187(5):513-537'},{id:"B2",body:'Boice JD Jr. The linear nonthreshold (LNT) model as used in radiation protection: An NCRP update. International Journal of Radiation Biology. 2017 Oct 3;93(10):1079-1092'},{id:"B3",body:'Fattibene P, Callens F. EPR dosimetry with tooth enamel: A review. Applied Radiation and Isotopes. 2010 Nov 1;68(11):2033-2116'},{id:"B4",body:'Ainsbury EA, Bakhanova E, Barquinero JF, Brai M, Chumak V, Correcher V, et al. Review of retrospective dosimetry techniques for external ionising radiation exposures. Radiation Protection Dosimetry. 2011 Nov;147(4):573-592'},{id:"B5",body:'Tondel M, Rääf C, Wålinder R, Mamour A, Isaksson M. Estimated lifetime effective dose to hunters and their families in the three most contaminated counties in Sweden after the Chernobyl nuclear power plant accident in 1986 – A pilot study. Journal of Environmental Radioactivity. 2017 Oct 1;177:241-249'},{id:"B6",body:'Jönsson M, Tondel M, Isaksson M, Finck R, Wålinder R, Mamour A, et al. Modelling the external radiation exposure from the Chernobyl fallout using data from the Swedish municipality measurement system. Journal of Environmental Radioactivity. 2017 Nov 1;178:16-27'},{id:"B7",body:'Rääf CL, Hubbard L, Falk R, Agren G, Vesanen R. Transfer of 137Cs from Chernobyl debris and nuclear weapons fallout to different Swedish population groups. Science of the Total Environment. 2006 Aug 15;367(1):324-340'},{id:"B8",body:'Skuterud L, Thørring H. Averted doses to Norwegian Sámi reindeer herders after the Chernobyl accident. Health Physics. 2012 Feb;102(2):208-216'},{id:"B9",body:'Barlow L, Westergren K, Holmberg L, Talbäck M. The completeness of the Swedish Cancer Register: A sample survey for year 1998. Acta oncologica (Stockholm, Sweden). 2009;48(1):27-33'},{id:"B10",body:'Gardner MJ. Review of reported increases of childhood cancer rates in the vicinity of nuclear installations in the UK. Journal of the Royal Statistical Society. Series A, Statistics in Society. 1989;152(3):307-325'},{id:"B11",body:'Davis FG, KL Y, Preston D, Epifanova S, Degteva M, Akleyev AV. Solid cancer incidence in the Techa River incidence cohort: 1956-2007. Radiation Research. 2015 Jul;184(1):56-65'},{id:"B12",body:'Likhtarev IA, Shandala NK, Gulko GM, Kairo IA, Chepurny NI. Ukrainian thyroid doses after the Chernobyl accident. Health Physics. 1993 Jun;64(6):594-599'},{id:"B13",body:'Cardis E, Kesminiene A, Ivanov V, Malakhova I, Shibata Y, Khrouch V, et al. Risk of thyroid cancer after exposure to 131I in childhood. Journal of the National Cancer Institute. 2005 May 18;97(10):724-732'},{id:"B14",body:'Izrael YA, De Cort M, Jones AR, Nazarov IM, Fridman SD, Kvasnikova EV, et al. The atlas of Caesium-137 contamination of Europe after the Chernobyl accident. In: Karaoglu A, Desmet G, Kelly GN, Menzel HG, editors. The Radiological Consequences of the Chernobyl Accident. ECSC-EC-EAEC, Brussels; 1997. pp. 1-10'},{id:"B15",body:'Alinaghizadeh H, Wålinder R, Vingård E, Tondel M. Total cancer incidence in relation to 137Cs fallout in the most contaminated counties in Sweden after the Chernobyl nuclear power plant accident: A register-based study. BMJ Open. 2016 Dec 20;6(12):e011924'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Robert Wålinder",address:"robert.walinder@medsci.uu.se",affiliation:'
Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
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1. Introduction
It is well accepted that inflammation in the peripheral organs can influence homeostasis and immune responses in the central nervous system (CNS) [1]. In common neuropsychiatric conditions such as schizophrenia and depression, evidence indicates that neuroinflammation plays a role in the disease pathogenesis [2]. Long-lasting effects of neuroinflammation in such neuropsychiatric conditions are implicated with altered innate immune responses in the absence of specific pathogens [2]. However, until recently, it is not well understood how innate immunity, which was thought to have no lasting memory unlike adaptive immunity, can exert prolonged actions on the CNS. The recent discovery of innate immune memory (trained immunity vs. tolerance) shed a light in a long postulated role of innate immunity in neuropsychiatric diseases [3, 4].
Since the existence of the immune system was recognized more than 50 years ago, the immune system has been thought to be comprised of two components, innate immunity and adaptive immunity. Innate immunity is the arm that mounts nonspecific, acute immune responses, by sensing microbial by-products called pathogen-associated molecular patterns (PAMPs) or by-products derived from tissue injuries called damage-associated molecular patterns (DAMPs) [5]. Signaling through PAMPs and DAMPs are thought to play a major role in plant immunity [6]. In animals, adaptive immunity is the arm that develops antigen (Ag)-specific responses. The development of Ag-specific responses requires lengthy processes including antigen (Ag) processing by Ag-presenting cells (APCs), Ag presentation to T and B cells, and TCR or immunoglobulin gene arrangements of T and B lymphocytes, respectively, which lead to the development of Ag-specific T and B cells and finally antibodies (Abs) [7]. Adaptive immunity effectively eliminates hazards from the body through Ag-specific cellular and humoral immune responses [7]. Adaptive immunity results in the development of long-lasting Ag-specific memory T/B cells [8]. In this way, the body retains immune memory against specific pathogens for a prolonged time. It is well known that individuals who have survived measles will retain measles-specific immune defense for life.
In contrast, immunology textbooks have long taught us that innate immunity does not have any lasting effects or memory, and it is mainly effective in containing infection until adaptive immunity takes over. Innate immunity has also been known to shape adaptive immunity through multiple mechanisms such as affecting actions of APCs, thereby indirectly modifying adaptive immune responses [7]. However, recent exciting research revealed that innate immunity can have its own memory, following an immune stimulus, and this depends on time, amount, and the kinds of stimuli through metabolic and epigenetic changes [3, 9]. More importantly, the stimuli that evoke innate immune memory are not restricted to microbes; nonpathogenic challenges such as stress and obesity are also found to cause innate immune memory [3, 10].
As described previously, despite the accumulating evidence, it was difficult to understand how innate immunity exerts lasting effects, in the absence of specific pathogens or other persistent environmental stimuli, in neuropsychiatric conditions. The recognition of innate immune memory (trained immunity vs. tolerance) has provided us new insights with regard to the role of innate immunity in physiological as well as pathogenic consequences in the brain. In this chapter, research efforts shaping a concept of innate immune memory (trained immunity vs. innate immune tolerance) will be discussed first. In the latter part of the chapter, a potential role of innate immune memory in neuropsychiatric conditions, especially in ASD, will be discussed.
2. Innate immune memory
2.1 Trained immunity
The presence of innate immune memory was first suspected because of unexpected, nonspecific effects of vaccinations. This is best known for a Bacillus Calmette-Guérin (BCG) vaccine. Epidemiological studies and subsequent randomized trials showed that the BCG vaccination not only provided protection for tuberculosis but also protection against other pathogens, especially those causing respiratory infection, which resulted in a reduction in infant mortality greater than expected for reducing tuberculosis-associated mortality [11, 12]. Likewise, the measles vaccination resulted in a striking reduction in children’s mortality, which was again not to be explained by the reduction in mortality caused by measles [11]. These epidemiological observations were further explored by researchers in the Netherlands. They first demonstrated that innate immune memory does exist in animal models [13]. Namely, these researchers showed that BCG provided enhanced protection against Candida albicans through nonspecific adaptation of innate immunity, independent of lymphocytes [13]. They proposed to name this process of innate immune memory “trained immunity.” The following studies by the same group also revealed that such adaptive changes in innate immunity are present not only in monocyte-macrophage lineage cells but also in other innate immune cells such as natural killer (NK) cells [14] and progenitor cells of innate immune cells in the bone marrow [15, 16]. Further studies revealed the presence of trained immunity in humans [17, 18, 19]. It became clear that trained immunity is similar to plant immunity which does not develop Ag-specific immunity, but develops prolonged immune defense by metabolic and epigenetic modulation [20]. Mounting evidence has now repeatedly shown that trained immunity is Ag nonspecific; the second stimulus (DAMP or PAMP) causing innate immune activation can be different from the first stimulus [3].
2.2 Mechanisms of trained immunity
Adaptive changes observed in “in vitro” models of trained immunity with β-glucan, a representative PAMP from Candida albicans, have been extensively studied. It was revealed that ß-glucan treatment induces activation of the dectin-1/Akt/PTEN/mTOR/HIF-1α signaling pathway in innate immune cells [21]. That is, β-glucan activates dectin-1 which recruits Akt, leading to activation of mammalian target of rapamycin (mTOR) with suppression of PTEN expression and phosphorylation of the tuberous sclerosis complex (TSC) [22]. Activation of this pathway switches cellular metabolism from oxidative phosphorylation (ATP synthesis) to glycolysis, thereby reducing basal cellular respiration and increasing in glucose consumption, resulting in higher production of lactate [21]. Such metabolic changes lead to the exportation of citrate to the cytoplasm for cholesterol synthesis and phospholipid synthesis [23, 24].
This metabolic shift described above results in the replenishment of the Krebs cycle by metabolization of glutamine into glutamate and α-keto-glutamate, leading to an accumulation of fumarate [23, 24]. Higher concentration of fumarate inhibits the KDM5 family of H3K4 demethylase that eventually leads to epigenetic reprogramming [23]. It has been reported that in the initial phase of trained immunity, lysine 27 of histone 3 (H3K27) is acetylated and lysine 4 of histone 3 (H3K4) is methylated rapidly [25]. Although H3K27Ac gradually returns to the baseline over time, H3K4me3 was found to remain elevated in the trained immunity [25]. Such epigenetic histone modification (accumulation of H3K4me3) is known to lead to the remodeling of the local chromatin into an open and accessible state, resulting in the facilitation of the loading of transcriptional machinery. The remaining accumulation of H3K4me3 on chromatin has been implicated in the establishment of the epigenetic memory in the trained immunity [25, 26]. It was hypothesized that H3K4me3 increases the local hydrophobicity of the chromatin, allowing for liquid-liquid phase separated transcription factors to engage with the DNA in the aqueous environment of the nucleus, subsequently rendering loading of transcriptional machinery onto promoters [27, 28, 29]. This will allow cells to start rapid transcription of the genes necessary for immune responses, thereby causing a much stronger Ag nonspecific pro-inflammatory response.
Long noncoding RNAs (lncRNAs) can function as a molecular scaffold where multiple protein complexes can assemble, and they also guide these complexes to specific gene loci [30]. Recent research disclosed a new class of lncRNAs named immune gene-priming lncRNAs (IPLs), and IPLs were found to have a crucial role in the accumulation of H3K4me3 on chromatin [31]. A candidate IPL, termed upstream master lncRNA of the inflammatory chemokine locus (UMLILO), was found to be crucial for trained immunity; ablation of the UMLILO transcript abolished β-glucan-induced trained immunity in both human and murine monocytes [30].
As shown in epidemiological studies of vaccinations, trained immunity, caused by metabolic and epigenetic changes, will be beneficial in providing broader immune defense and promoting tissue repair [32]. On the other hand, maladapted trained immunity can be detrimental to human health. Chronic inflammatory conditions including neuropsychiatric conditions have been implicated with maladapted changes in trained immunity [2, 9]. It should also be noted that induction of trained immunity appears to be associated with doses of PAMP, perhaps DAMP in humans; depending on the dose and the kinds of PAMP/DAMP, tolerance can be induced, instead of trained immunity [2]. It has been shown that low to moderate doses of β-glucan, tri-DAP, and muramyl dipeptides are reported to induce trained immunity [33]. It also needs to be cautioned that the effects of trained immunity are likely associated with individual’s genetic and epigenetic background. For example, nonspecific effects of infant BCG vaccination are reported to be heterogeneous, affected by multiple genetic and environmental factors including age, gender, interactions with other vaccines, and exposure to infectious pathogens at the time of BCG vaccination [34].
2.3 Mediators of trained immunity
It has been reported that pre-administration of pro-inflammatory innate cytokines [interleukin-1 (IL-1), tumor necrosis factor-α (TNF-α), and IL-6] provided protection against a variety of microbes [35]. Among the cytokines administered, IL-1 showed superior effects over TNF-α or IL-6 [35]. In BCG-vaccinated individuals, increase in production of these innate cytokines by monocytes in response to other microbes, other than BCG, was also found; this effect was again the most dependent on IL-1β [32]. IL-1β has also been reported to be crucial in the induction of trained immunity in NK cells [36]. On the other hand, in individuals with chronic mucocutaneous candidiasis, STAT-1-mediated type II interferon (IFN) induction was found to be crucial for induction of trained immunity [37]. The role of type II IFN (IFN-γ) in animal models was also reported by Kaufmann et al. [16]. However, in humans, innate immunity-associated protection (trained immunity) has been mainly implicated with IL-1β and other IL-1 families [38].
As detailed in the previous section, a metabolic shift from oxidative phosphorylation to aerobic glycolysis through the Hypoxia inducible factor-1α (HIF-1α) pathway downstream to mTOR is crucial for the development of trained immunity, since inhibition of this pathway is abolished induction of trained immunity [21]. Namely, in HIF-1α knockout mice, trained immunity was not induced [21]. IL-1β is known to be a direct target of HIF-1α [39], having a HIF-1α binding site in the promoter region of IL-1β gene [40]. It is now thus proposed that HIF-1α-induced IL-1β also plays a role in epigenetic changes, through histone modifications [35]. Alternatively, IL-1β has been shown to upregulate HIF-1α [41].
Given the role of IL-1β in trained immunity, excessive, dysregulated production of IL-1β is likely to cause maladapted trained immunity and resultant pathogenic consequences. This may be observed in patients with autoinflammatory syndromes associated with gene mutation that lead to overproduction of IL-1β, including cryopyrin associated periodic syndrome (CAPS) [38, 42]. On the other hand, impaired induction of trained immunity can also cause detrimental effects. It was reported that patients with chronic mucocutaneous candidiasis exhibit impaired induction of STAT-1-dependent, trained immunity in response to β-glucan [37].
The above-described metabolic shift is not limited to glucose metabolism. Changes in glutamine and cholesterol metabolism have also shown to be crucial in trained immunity [24]. Consequently, it is thought that increased cholesterol content also plays a role in the development of trained immunity. Interestingly, increased levels of oxidized low-density lipoprotein (OxLDL) caused by dysregulated cholesterol metabolism are found to induce trained immunity in human monocytes [10]. Such a finding indicates a pathogenic role for maladapted trained immunity in atherosclerosis, since monocyte and macrophage cells are known to play a major role in plaque formation in vascular endothelium, a major histologic change in atherosclerosis [10].
2.4 Tolerance in innate immunity
As detailed in the previous section, trained immunity causes a metabolic shift from oxidative phosphorylation (OXPHOS) to glycolysis, rendering macrophage and monocyte lineage cells to classically activated cells or M1 phenotype; these cells exhibit impaired OXPHOS and anabolic repurposing of the tricarboxylic acid (TCA) cycle [43, 44]. In contrast, alternatively activated or the M2 phenotype of macrophages and monocytes has balanced processes of OXPHOS and TCA cycle activation; enhanced glycolytic generation of pyruvate fuels the TCA cycle, paralleling the induction of OXPHOS [44]. Trained macrophages via ß-glucan exposure are shown to reveal M1 phenotype [21]. Generation of M1 vs. M2 phenotypes of macrophages indicates the importance of regulating innate immune responses for prevention of excessive, potentially harmful inflammatory responses. In addition to generation of M2 phenotype, hypo-responsiveness of innate immunity has been described as endotoxin tolerance and compensatory anti-inflammatory response syndrome (CARS) [45]. Such regulatory mechanisms also have lasting effects, as observed in trained immunity.
Endotoxin tolerance in innate immunity was first shown in rodent models of sepsis. Namely, survival from sepsis is associated with diminished or absence of responses to LPS, an endotoxin [46]. Subsequently, it was shown that previous exposure to a sublethal dose of LPS led to resistance to a lethal dose of LPS in rodents [46]. Endotoxin tolerance is thought to be a result of innate immune memory with lasting immune hypo-responsiveness, even to non-LPS stimulants [47]. Phenotypic changes of tolerant innate immune cells are characterized with less production of inflammatory cytokines (TNF-α, IL-12, IL-6) and increase in production of counter-regulatory cytokines (IL-10 and TGF-β) upon stimulation [48, 49]. CARS was recognized as a clinical syndrome which is thought to represent a phase of immune “exhaustion,” following initial potent immune activation, known as systemic inflammatory response syndrome (SIRS) [50]. Peripheral blood monocytes and neutrophils from CARS patients are reported to reveal similar phenotype to endotoxin-tolerant cells observed in rodent models [45, 49]. Recent research revealed that persistent effects of endotoxin tolerance and CARS are mediated by lncRNAs as well as microRNAs (miRNAs).
LPS activates TLR4 which leads to the activation of the myeloid differentiation factor 88 (MyD88)-mediated pathway and the TIR-domain-containing adaptor-inducing interferon-β (TRIF) pathway [45]. The molecular signature of endotoxin tolerance involves downregulation of TLR4, decreased recruitment of MyD88 or TRIF to TLR4, decreased activation of IL-1 receptor-associated kinase (IRAK)1 and IRAK4, diminished nuclear factor κ chain of B-cell (NF-κB) signaling, as well as upregulation of negative regulatory molecules including SH2 domain-containing inositol phosphatase 1 (SHIP1) [51].
2.5 Regulators of innate immune tolerance
Recent research revealed a role of miRNAs in the regulation of endotoxin tolerance. Specifically, miR-155 and miR-146α have been shown to regulate endotoxin tolerance [52]. MiR-146α reduces TLR signaling, by targeting IRAK1 and TRAF6, key components of TLR signaling pathway [53]. In contrast, miR-155 is reported to inhibit expression of SHIP1 and SOCS1, negative regulators of TLR signaling, prohibiting or attenuating tolerance induction by endotoxin [54, 55]. Several other miRNAs are also implicated with regulation of endotoxin intolerance [45]. It was shown recently that miR-221/miR-222 regulates functional reprogramming of macrophages during LPS-induced tolerization [47]. miR-221/miR-222 targets brahma-regulated gene 1 (Brg1), rendering transcriptional silencing of a subset of inflammatory genes that depend on SWI/SNF and STAT-mediated chromatin remodeling [47].
Recent research also revealed a role of lncRNAs in endotoxin tolerance; lncRNAs exert transcriptional, posttranscriptional, and translational regulation of gene expression [56, 57, 58]. Multiple lncRNAs are reported to regulate target molecules of TLR4 signaling pathways. LPS-responsive lncRNAs Mirt2, THRIl, MALTAT1, NKILA, lincRNA-21, and SeT have been reported to suppress expression of pro-inflammatory mediators including TNF-α [45]. For example, Mirt2 is reported to inhibit TRAF6 ubiquitination, leading to a decrease in TNF-α production [59]. However, at this time, relationships between actions of miRNAs and lncRNA in innate immune tolerance are not well understood. Other soluble mediators such as cytokines (IL-1β, IL-10, TGF-β, and TNF-α) are also reported to induce cross-tolerance or cytokine-mediated tolerance, causing a signaling cascade similar to that observed in TLR signaling [60]. In contrast, interferons (IFN-γ, α2-IFN, etc.) are known to abrogate endotoxin tolerance [61, 62]. Again these soluble mediators exert their actions on endotoxin tolerance via modulation of intracellular lncRNAs [45].
This type of innate immune memory (tolerance) is thought to be important in maintaining brain homeostasis, and impaired tolerance of innate immunity has been suspected in chronic neurodegenerative conditions such as Alzheimer’s disease [9]. Aging is associated with an increased load of gram-negative bacteria in the GI tract and mouth mucosa, resulting in an increase in endotoxin levels in the blood and the brain [62]. However, aging individuals tolerate higher LPS levels in the brain through developing endotoxin tolerance [63].
3. Role of innate immunity in the nervous system
It is known that innate immunity does exist in the brain, playing a crucial role in brain morphogenesis and homeostasis. The major innate immune cells in the central nervous system (CNS) are microglial cells which are endogenously generated in the brain, but they can also be developed from bone marrow-derived monocytes, which are called BM-derived microglial cells (BMDM) [64, 65]. BMDM-induced inflammation has been implicated in neuropsychiatric conditions [64, 65]. It has also been reported that peripherally derived macrophages modulate microglial function after CNS injury; in this case, they are reported to exert anti-inflammatory effects [66]. Other innate immune cells in the CNS such as astrocytes are also known to exert important physiological roles [9, 67].
3.1 Trained immunity in the CNS
Inflammation in the periphery can prompt immune responses in the brain [1, 4]. Given the effects of trained immunity (activation vs. tolerance) in rodent models and humans, the development of maladapted innate immune memory in the CNS is expected to result in undesired, hazardous effects to the brain. However, reports concerning the effects of trained immunity and/or innate immune tolerance in the brain have been limited. Nevertheless, it was shown that microglial cells isolated from adult rats that were exposed to E. coli during the newborn period had increased expression of IL-1β mRNA [68]. The rats exposed to E. coli as newborns were also found to have impaired memory when they were challenged with a low dose of LPS, which was blocked by minocycline [2]. In experiments employing microglial cells obtained from sheep fetuses whose mother was given LPS intravenously, these fetal microglial cells were shown to have metabolic and epigenetic modulation, as has been reported in trained immunity [69].
Independent of the studies concerning trained immunity in the brain, persistent effects of maternal immune activation (MIA) on fetuses have been extensively studied, as one of the best studied rodent models of ASD [70]. In this model, sterile inflammation in pregnant rodents was induced with the use of PAMPs such as LPS, poly I:C, resulting in impaired neuropsychiatric symptoms in offspring in their adult years [70]. That is, offspring of MIA mothers have been shown to suffer from persistent behavioral symptoms and cognitive deficits frequently seen in ASD subjects later in life [70]. In addition, MIA also causes persistent alteration of adaptive immunity [71]. However, in this model, it is not yet well understood how innate immune memory (most likely trained immunity in this model) plays a role in a MIA model, causing persistent behavioral changes and impaired cognitive development. Children exposed to stressful events during the fetal and newborn period have also been reported to have higher levels of pro-inflammatory cytokines and neurodevelopmental impairment than control children [2]. Given the research findings in molecular mechanisms of trained immunity described in the previous section, there is a possibility that maladapted trained immunity contributes to the onset and progress of some neuropsychiatric disorders.
3.2 Innate tolerance in the brain
Tolerized innate immunity in the brain is thought to be crucial for limiting excessive inflammatory responses during brain tissue repair that involves phagocytosis of apoptotic cells and damaged tissue debris by tolerant phagocytes [72]. In rodent models, disruption of this pathway leads to neuroinflammation and subsequent neuronal damage [73]. An important regulator of this pathway is the triggering receptor expressed on myeloid cells 2 (TREM-2), which is expressed on microglial cells [74]. Blockade of TREM-2 was shown to exacerbate experimental autoimmune encephalitis (EAE), a rodent model of multiple sclerosis (MS) [75]. Apolipoprotein E (ApoE) which is a TREM-2 ligand was shown to have a role in maintaining tolerized phenotype of phagocytic cells [74]. This interaction was found to be impaired in patients with Alzheimer’s disease [9]. In animal models of Alzheimer’s disease treated with trained immunity vs. tolerance inducing stimuli, it was reported that long-term modulation of brain immune responses were observed, and the authors attributed this prolonged effects on innate immune memory to reprogramming of microglial cells [4].
3.3 mTOR-related pathology in neuropsychiatric disorders
In the previous section describing molecular pathways associated with trained immunity, the importance of mTOR signaling has been repeatedly shown. One thing we learned from the research on trained immunity is that multiple lineage cells reveal metabolic and epigenetic reprogramming in the process of innate immune memory, which, in animal models, can also be applied to microglial cells [4]. Interestingly, brain dysfunction caused by dysregulated mTOR signaling has been implicated in several neuropsychiatric disorders. In the next paragraph, we summarize mTOR-related brain dysfunctions and proposed mechanisms.
One of the expected consequences of excessive mTOR signaling caused by trained immunity is the impairment of lysosomal degradation of intracellular components, since mTOR activation inhibits autophagy via inhibition of the early steps of autophagosome biogenesis [76, 77]. Autophagy is a key physiological cellular function that clears intracellular molecules and thought to be developed to adjust the state of nutrient depletion [76, 77]. However, this is also an important mechanism to remove misfolded proteins that naturally occur in living cells [22]. In addition to degradation of misfolded proteins, autophagy also degrades altered subcellular organelles, such as the mitochondria [22]. Prolonged dysfunction in autophagy can lead to detrimental effects and is implicated in the pathogenesis of multiple neuropsychiatric conditions including dementia, movement disorders, seizures, brain ischemia, ASD, affective disorder, and schizophrenia [78, 79, 80, 81, 82]. In rodent models of depression, tuberous sclerosis, and ASD, rapamycin (sirolimus), a representative mTOR inhibitor, has been shown to attenuate social interactions and reverse behavioral effects on their neuropsychiatric symptoms [83, 84, 85, 86]. Thus metabolic and epigenetic changes caused by trained immunity may have profound effects through altered levels of autophagy, as a result of metabolic and epigenetic reprograming, as detailed in the previous section.
3.4 ASD and a possible role of trained immunity
In this section, we discuss a possible role for trained immunity in the onset and progress of ASD. As a clinician, the author observed that an apparent strong immune stimulus altered the responses to subsequent immune stimuli in some, but not all ASD children and these ASD children also exhibit fluctuating neuropsychiatric symptoms, following microbial infection [87, 88]. As discussed in the previous section, in the MIA model of ASD, prolonged effects of MIA on the offspring brain can be explained through a concept of trained immunity occurring to the fetus at the time of sterile immune activation in the mother. This may have also happened in ASD subjects as described above. However, it should be noted that ASD is a behaviorally defined syndrome, diagnosed on the basis of behavioral symptoms, except for a minority of ASD cases that have well-defined gene mutations [89]. Therefore, based on the author’s clinical experience, it is likely that trained immunity plays a role in a subset of ASD subjects for whom neuroinflammation is associated in their ASD pathogenesis.
In ASD patients, just like in other neuropsychiatric conditions, a role of inflammation has been long suspected, and more and more evidence has been accumulating [90, 91, 92]. In the research of innate immune abnormalities in ASD children, we have also found evidence of dysregulated innate immune responses, shifting to pro-inflammatory responses in a subset of ASD subjects [88, 93, 94]. We also experienced that these ASD subjects suffer from various comorbid medical conditions involving the gastrointestinal (GI) tract and other organs [87]. Retrospectively, our findings may be reflecting maladapted innate immunity as a form of trained immunity in such ASD subjects; these ASD subjects may fall into an ASD subset which we have called inflammatory autism, mimicking the rodent ASD model of MIA [93]. Our previous findings that may indicate altered innate immune memory in such ASD patients are as follows:
In some but not all the ASD subjects, we found significant changes in innate immune abnormalities which are best reflected in changes in IL-1β/IL-10 ratios produced by purified peripheral blood monocytes (PBMo) [88, 93]. Namely, some patients reveal high ratios of IL-1β/IL-10, while others showed low ratios, and these rations can change from time to time, depending on their exposure to immune insults [93].
ASD subjects who revealed high and/or low IL-1β/IL-10 ratios also revealed fluctuating behavioral symptoms following immune insults [94]. Parents of these subjects often describe more severe, prolonged illnesses and frequent respiratory infection following microbial infection [87]. They also seem to reveal significant changes in their behavioral symptoms and cognitive activity with immune stimuli not associated with microbial infection; these ASD children may exhibit worsening neuropsychiatric symptoms, following flare-ups of aeroallergen allergy, delayed-type food allergy, and adverse reactions to medications including vaccinations [87, 94].
ASD subjects who revealed high and/or low IL-1β/IL-10 ratios also revealed changes in production of inflammatory monocyte cytokines including TNF-α and IL-6 [93, 95].
PBMo from ASD subjects who revealed altered IL-1β/IL-10 ratios also revealed changes in miRNA expression by PBMo, as compared to cells obtained from neurotypical, non-ASD controls [93].
We also studied changes in mitochondrial respiration in peripheral blood mononuclear cells (PBMCs) obtained from ASD subjects and non-ASD controls. Our results revealed evidence of altered mitochondrial respiration in association with changes in IL-1β/IL-10 ratios by PBMo in ASD subjects [95].
In recent studies, we also found changes in miRNA in sera of ASD subjects, when tested by high-throughput deep sequencing. Again, changes in serum miRNA levels are closely associated with changes in IL-1β/IL-10 ratios by PBMo, production of monocyte cytokines (TNF-β, IL-6, IL-10, CCL2 mostly), along with parameters of mitochondrial respiration (manuscript submitted for publication). Interestingly, in ASD subjects, miRNA levels are mostly decreased, as compared to non-ASD controls (submitted for publication). Targeted genes by miRNAs that are altered in serum levels in ASD subjects with high or low IL-1β/IL-10 ratios are associated with pathways involved in innate immune responses, including the mTOR signaling pathway (unpublished observation).
The above-described findings may be best explained by altered innate immune responses associated with innate immune memory (trained immunity vs. tolerance). So, if this is the case, for these ASD subjects, can clinical features that indicate an alternation of innate immune memory be detected? The author is a pediatric immunologist and, as indicated before, as stated previously, observes exacerbation of neuropsychiatric symptoms, following immune insults. Herein, a representative ASD case, in which trained immunity may be associated with the onset and progression of ASD, is presented.
3.5 Case presentation
A 10-year-old female child presented to the pediatric allergy/immunology clinic at our institution secondary to fluctuating behavioral symptoms. Fluctuation of behavioral symptoms often occurred, following microbial infection.
The patient was born at 41 weeks of gestation via cesarean section due to breech presentation, following an uneventful pregnancy. The patient was developing typically until 24 months of age and then suffered from significant developmental regression. Prior to the onset of the developmental regression, parents took the patient to South Asia to visit other family members and friends. During this visit, the patient suffered an insect bite which was complicated by a secondary bacterial skin infection. When treated with oral antibiotics abroad, the patient developed generalized hives and severe GI symptoms (nausea, vomiting, diarrhea, and bloating): the patient then became intolerant to multiple foods. After returning to the United States, the patient was given multiple vaccinations including live vaccines to catch up the vaccination schedule. All these vaccines were given while the patient was still suffering from GI symptoms and an active skin infection. Within several days after vaccinations (multiple vaccines given all together), noticeable loss of cognitive and motor skills became apparent in the patient. The patient was eventually diagnosed with ASD around 2.5 years of age.
Eventually, the patient’s GI symptoms subsided, but this subject never regained the cognitive skills that this patient had once acquired prior to the onset of developmental regression. Prior to advancing to pre-kindergarten, the patient was given booster doses of vaccines which were well tolerated. However, after starting pre-kindergarten, the patient started getting sick frequently with upper respiratory infections, which often evolved into ear infection. The patient missed many days of school, since the patient suffered a prolonged course of illness and more severe symptoms, as compared to peers. While the patient presented with symptoms of upper respiratory infection, this patient’s behavioral symptoms continue to fluctuate, most evident in worsening of obsessive compulsive behaviors and frequency of “rage” episodes. Worsening behavioral symptoms would always follow immune insults, worse in a convalescence stage. Avoidance of sick contacts by placing the patient in home schooling attenuated the fluctuating behavioral symptoms. At 7–8 years of age, the fluctuating behavioral symptoms seen were mainly associated with teething. After the completion of teething, behavioral symptoms became more stable. However, the patient stopped growing, falling under the first percentile of the growth curve in height and weight. An exhausting workup for primary mitochondrial diseases, endocrine diseases, primary immunodeficiency with known gene mutations, and congenital metabolic and genetic diseases was unrevealing. However, video electric encephalogram revealed a focal epileptic activity. Family history is negative for neuropsychiatric, genetic, autoimmune, immune, and metabolic diseases.
In the case presented above, did neuroinflammation caused by maladapted trained immunity have a role in her clinical features? It is hard to prove, but it may be speculated that the initial stressful events that occurred abroad shaped trained immunity in this patient, and the subsequent multiple unrelated immune stimuli may have caused prolonged maladapted trained immunity, leading to persistent neuroinflammation and impairment of cognitive activity, as observed in the MIA models of ASD. Interestingly, changes in GI conditions, such as changes in microbiome, have been implicated with neuropsychiatric diseases, triggering maladapted trained immunity [96]. It is also reported that trained innate immunity can be induced in human monocytes by cow’s milk [97]. Thus her severe GI symptoms and subsequent intolerance to multiple foods may be associated with excessive trained immunity in the gut of this patient.
3.6 Evidence of impaired trained immunity
As summarized in the previous section, we have found that IL-1β/IL-10 ratios produced by PBMo are altered in some ASD subjects in association with fluctuating behavioral symptoms [94]. Thus if innate immune memory (trained immunity) is associated with her above-described remarkable clinical symptoms, we may also find altered IL-1β/IL-10 ratios, as an indicator of altered innate immune responses.
Thus we assessed IL-1β/IL-10 ratios produced by PBMo in response to a panel of innate immune stimuli, including β-glucan, as reported previously [95]. As shown in Figure 1, the presented case revealed increase in IL-1β/IL-10 ratios in response to zymosan, CL097, and β-glucan. High IL-1β/IL-10 ratio in response to CL097, an agonist of TLR7/TLR8, was especially striking. We also observed increase in production of TNF-α and IL-6 and decrease in the production of IL-10, as well. Given these findings, it is possible that maladapted trained immunity may have caused excessive inflammatory responses to various innate immune stimuli, which then led to developmental regression and fluctuating behavioral symptoms in this presented case.
Figure 1.
IL-1β/IL-10 ratios produced by purified peripheral blood monocytes in response to medium only (no stimulus), LPS (TLR4 agonist), zymosan (TLR2/TLR6 agonist), CL097 (TLR7/TLR8 agonist), and β-glucan in the presented case (patient) and control cells from a non-ASD neurotypical subject. IL-1β/IL-10 ratios are shown in a log scale.
4. Conclusions
Our deepening knowledge of innate immune memory (trained immunity vs. tolerance) has shed light on the understanding of nonspecific effects of microbial infection and other immune stimuli, which have been implicated in the onset and progress of various neuropsychiatric diseases. Recent research indicates a possibility for a role of maladapted innate immune memory in various neuropsychiatric conditions. The finding of innate immune memory is especially exciting in the field of neuroimmunology, since we now likely have better tools for addressing the long-suspected role of immune-mediated inflammation that is not associated with specific pathogens or environmental factors, in various neuropsychiatric conditions. The concept of innate immune memory will be especially important in addressing insults to the brain during the early years of CNS development, and the resultant lasting intellectual disabilities, as seen in MIA models [70]. More importantly, an improved understanding of the role of innate immune memory (trained immunity vs. tolerance) in pathogenic neuroinflammation can lead to novel therapeutic measures that are desperately needed for the treatment of neuropsychiatric diseases.
Acknowledgments
The part of the study presented in this manuscript was funded from the Jonty Foundation, St. Paul, MN. The author is thankful for the critical review of this manuscript by Dr. L. Huguenin.
upstream master lncRNAs of the inflammatory chemokine locus
\n',keywords:"innate immunity, cytokines, neuroinflammation, neuroimmune network, immune metabolic processes",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/67905.pdf",chapterXML:"https://mts.intechopen.com/source/xml/67905.xml",downloadPdfUrl:"/chapter/pdf-download/67905",previewPdfUrl:"/chapter/pdf-preview/67905",totalDownloads:704,totalViews:0,totalCrossrefCites:0,dateSubmitted:"December 10th 2018",dateReviewed:"May 31st 2019",datePrePublished:"July 4th 2019",datePublished:"August 19th 2020",dateFinished:null,readingETA:"0",abstract:"The neuroimmune network represents a dense network of multiple signals mediated by neurotransmitters, hormones, growth factors, and cytokines produced by multiple lineage cells and is crucial for maintaining neuroimmune homeostasis. Endogenous and exogenous stimuli, which are dangerous to the body, are detected by sensor cells, and they rapidly inform the brain through this network. Innate immunity is thought to play a major role in the neuroimmune network, through cytokines and other mediators released from secretary innate immune cells. Recent research has revealed that innate immunity has its own memory. This is accomplished by metabolic and epigenetic changes. Such changes may result in augmenting immune protection with a risk of excessive inflammatory responses to subsequent stimuli (trained immunity). Alternatively, innate immune memory can induce suppressive effects (tolerance), which may impose a risk of impaired immune defense. Innate immune memory affects the neuroimmune network for a prolonged period, and dysregulated innate immune memory has been implicated with pathogenesis of neuropsychiatric conditions. This chapter summarizes a role of innate immune memory (trained immunity vs. tolerance) in neuroinflammation in association with neuropsychiatric conditions including autism spectrum disorders (ASD).",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/67905",risUrl:"/chapter/ris/67905",signatures:"Harumi Jyonouchi",book:{id:"7853",title:"Cytokines",subtitle:null,fullTitle:"Cytokines",slug:"cytokines",publishedDate:"August 19th 2020",bookSignature:"Payam Behzadi",coverURL:"https://cdn.intechopen.com/books/images_new/7853.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"45803",title:"Ph.D.",name:"Payam",middleName:null,surname:"Behzadi",slug:"payam-behzadi",fullName:"Payam Behzadi"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"289040",title:"Dr.",name:"Harumi",middleName:null,surname:"Jyonouchi",fullName:"Harumi Jyonouchi",slug:"harumi-jyonouchi",email:"hjyonouchi@gmail.com",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Innate immune memory",level:"1"},{id:"sec_2_2",title:"2.1 Trained immunity",level:"2"},{id:"sec_3_2",title:"2.2 Mechanisms of trained immunity",level:"2"},{id:"sec_4_2",title:"2.3 Mediators of trained immunity",level:"2"},{id:"sec_5_2",title:"2.4 Tolerance in innate immunity",level:"2"},{id:"sec_6_2",title:"2.5 Regulators of innate immune tolerance",level:"2"},{id:"sec_8",title:"3. Role of innate immunity in the nervous system",level:"1"},{id:"sec_8_2",title:"3.1 Trained immunity in the CNS",level:"2"},{id:"sec_9_2",title:"3.2 Innate tolerance in the brain",level:"2"},{id:"sec_10_2",title:"3.3 mTOR-related pathology in neuropsychiatric disorders",level:"2"},{id:"sec_11_2",title:"3.4 ASD and a possible role of trained immunity",level:"2"},{id:"sec_12_2",title:"3.5 Case presentation",level:"2"},{id:"sec_13_2",title:"3.6 Evidence of impaired trained immunity",level:"2"},{id:"sec_15",title:"4. Conclusions",level:"1"},{id:"sec_16",title:"Acknowledgments",level:"1"},{id:"sec_19",title:"Conflict of interest",level:"1"},{id:"sec_18",title:"Abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'Perry VH, Cunningham C, Holmes C. Systemic infections and inflammation affect chronic neurodegeneration. Nature Reviews. Immunology. 2007;7(2):161-167'},{id:"B2",body:'Salam AP, Borsini A, Zunszain PA. Trained innate immunity: A salient factor in the pathogenesis of neuroimmune psychiatric disorders. Molecular Psychiatry. 2018;23(2):170-176'},{id:"B3",body:'van der Heijden C, Noz MP, Joosten LAB, Netea MG, Riksen NP, Keating ST. Epigenetics and trained immunity. Antioxidants & Redox Signaling. 2018;29(11):1023-1040'},{id:"B4",body:'Wendeln AC, Degenhardt K, Kaurani L, Gertig M, Ulas T, Jain G, et al. Innate immune memory in the brain shapes neurological disease hallmarks. Nature. 2018;556(7701):332-338'},{id:"B5",body:'Krakauer T. 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Department of Pediatrics, Rutgers-RWJ, Saint Peter’s University Hospital (SPUH), United States
Rutgers-Robert Wood Johnson Medical School, United States
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