\r\n\tLiterature showed the presence of ACE2 receptors on the membrane of erythrocyte or red blood cell (RBC), indicating that erythrocyte (RBC) can be considered as a peripheral biomarker for SARS-C0V2 infection.
\r\n
\r\n\tIncreased levels of glycolysis and fragmentation of RBC membrane proteins were observed in the SARS-C0V2 infected patients, demonstrating that not only RBC’s metabolism and proteome but its membrane lipidome could be influenced by SARS-C0V2 infection changing the homeostasis of the infected erythrocyte. This altered RBC may result in the clot and thrombus formation; the major signs of critically ill Covid-19 patients.
\r\n
\r\n\tThis book is going to be a succinct source of knowledge not only for the specialists, researchers, academics and the students in this area but for the general public who are concern about the present situation and are interested in knowing about simple non-invasive measures for identifying viral and bacterial infections through their red blood cells.
",isbn:"978-1-83969-121-8",printIsbn:"978-1-83969-120-1",pdfIsbn:"978-1-83969-122-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"fa5f4b6ef59e28b6e7c1a739c57c5d2f",bookSignature:"Prof. Kaneez Fatima Shad",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10494.jpg",keywords:"Spike Protein, Hemoglobin, Proteins for Oxygen Transport, Altered Protein Structures, RBC ACE Receptors, RBC ACE-2 Receptors, Carboxypeptidase, Mas Receptor, Metabolomics, Gas Transport, Glucose-6-Phosphate, Phosphoglycerate",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 15th 2020",dateEndSecondStepPublish:"November 30th 2020",dateEndThirdStepPublish:"January 29th 2021",dateEndFourthStepPublish:"April 19th 2021",dateEndFifthStepPublish:"June 18th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Shad is a governing body member and mentor of Women in World Neuroscience (WWN), a division of the International Brain Research Organization (IBRO). 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During this period, she was also engaged in doing research by getting local and international grants (total of over 3.3 million USD) and translating them into products such as a rapid diagnostic test for stroke and other vascular disorders. She published over 60 articles in refereed journals, edited 8 books, and wrote 7 book chapters, presented at 97 international conferences, mentored 34 postgraduate students. 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From chapter submission and review, to approval and revision, copy-editing and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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1. Introduction
Autism is a developmental lifelong condition of the human brain, and a behavioral characterization as a spectrum (autism spectrum disorder: ASD) is the best way to illustrate this complex trait (Frith, 2001; Rapin, 1997; Wing, 1997). The predominant presence of autistic cases without comorbidity (idiopathic or primary ASD) (Freitag, 2007) clearly means that the biological effects associated with the known concomitant medical conditions (cytogenic abnormalities, fragile X syndrome, tuberous sclerosis, congenital infections, maternal thalidomide use, epilepsy, etc.) cannot be the common prerequisite for ASD at least in the majority of the cases. The presence of a strong genetic contribution is evident from the results of twin studies, which demonstrated that 70-90% of monozygotic twins are concordant for ASD, and the concordance in dizygotic twins and the recurrence rate in the proband’s siblings are both less than 10% (Rapin & Katzman, 1998). A broadening of the criteria of diagnosis leads the monozygotic concordance ratio to more than 90%, but 100% concordance is never obtained (Rapin & Katzman, 1998). Therefore, it is claimed that genetic factors contribute about 90% to ASD with environmental factors contributing no more than 10% (Garber, 2007). Although a flood of genetic information in the field of ASD is continuously growing, even the newest genome-wide molecular studies cannot detect the universal genetic prerequisite for idiopathic cases with ASD, compelling some researchers to speculate that ASD has a huge inter-case heterogeneity of the related gene variants.
Many gene variants, which seem to affect brain development and synaptic functions, have been reported in association with the autistic development (Betancur, 2011; Garber, 2007; Persico & Bourgeron, 2006; Pinto et al., 2010). In families with the candidates for autism gene variants, however, the strict co-segregation, in which the gene variant is found only in individuals with ASD among family members including parents, is still exceptional (Table 1). To explain this fact, the broader distribution of the more primary phenotype or pre-behavioral phenotype (endophenotype) beyond the categorical border is introduced as the speculative solution through this research maze (Viding & Blakemore, 2007). It may be quite difficult to detect and evaluate such endophenotypes because of the configurational or hierarchical structures of human cognitions and behaviors. Even if such speculations were all true, it is too early to conclude that “a single gene variant causes a small percentage of cases with this complex trait” (Garber, 2007; Beaudet, 2007). As clearly demonstrated in the case of human disease-associated mutations found as wild-type alleles in normal chimpanzee (L. Azevedo et al., 2006), a deleted or mutated allele does not necessarily contribute to the disease development. Because evidence consistent with a theory is not proof of that theory (Cannell, 2010), until one could delineate the molecular or biological trajectory underlying autistic development which is quantitatively different from the parents, there is still a huge black box between the de novo variant allele and complex human behaviors in the sporadic cases with idiopathic ASD. The reported gene variants are, at present, nothing but one of the concomitants in a small percentage of cases (5-7%, in Table 1). The possibility that the variantsare mere relative risk factors remains to be elucidated (Jones & Szatmari, 2002). As a general rule, a genetic link does not necessarily imply neurological damage (Simpson,
Variants
Prevalence
References
SHANK3 variants
In ASD families
15 / 227 (6.6%)a
(Durand et al., 2007)
Co-segregated cases
3 / 227 (1.3%)b
In controls
5 / 270 (1.9%)a
SHANK3 variants
In ASD families
3 / 400 (0.8%)c
(Moessner et al., 2007)
SHANK3 variants
In ASD individuals
34 / 427(8.0%)
(Gauthier et al., 2009)
In controls
16 / 190 (8.4%)
SHANK3 deletion
In ASD individuals
1 / 427 (0.2%)c
(Gauthier et al., 2009)
In controls
0 / 190
SHANK3 deletion
In ASD individuals
2 / 2,195 (0.1%)
(Glessner et al., 2009)
In controls
2 / 2,519 (0.1%)
SHANK2 de novo deletion
In ASD individuals
2 / 996 (0.2%)
(Pinto et al., 2010)
In controls
0 / 1,287, 0 / 3,677
NLGN3 variants
In ASD individuals
0 / 96
(Yan et al., 2005)
NLGN3 duplication
In ASD individuals
1 / 2,195 (0.05%)
(Glessner et al., 2009)
In controls
0 / 2,519
NLGN4 variants
In ASD individuals
4 / 148 (2.7%)d
(Yan et al., 2005)
In controls
0 / 336
NRXN1 deletion
In ASD families
1 / 1,181 (0.1%)
(AGPC, 2007)
NRXN1α variants
In ASD individuals
5 / 116 (4.3%)
(Yan et al., 2008)
In controls
1 / 192 (0.5%)
NRXN1 deletion
In ASD individuals
10 / 2,195 (0.5%)
(Glessner et al., 2009)
In controls
0 / 2,519
NRXN1 de novo variants
In ASD families
4 / 996 (0.4%)
(Pinto et al., 2010)
In controls
5 / 1,287 (0.4%)
NRXN1β variants
In ASD individuals
4 / 203 (2.0%)d,e
(Feng et al., 2006)
In controls
0 / 535
NRXN2β variants
In ASD individuals
0 / 72
(Feng et al., 2006)
NRXN3β variants
In ASD individuals
0 / 72
(Feng et al., 2006)
CNTN4 deletion
In ASD individuals
10 / 2,195 (0.5%)
(Glessner et al., 2009)
In controls
0 / 2,519
CNTN4 duplication
In ASD individuals
9 / 2,195 (0.4%)c
(Glessner et al., 2009)
In controls
1 / 2,519 (0.04%)
AUTS2
In ASD individuals
1 / 2,195 (0.05%)
(Glessner et al., 2009)
In controls
0 / 2,519
DDX53/PTCHD1 deletion
In ASD cases
7 / 996 (0.7%)
(Pinto et al., 2010)
(maternally inherited)
In controls
0 / 1,287, 0 / 3,677
CNVs at 15q11-13
In ASD individuals
15 / 2,195 (0.7%)f
(Glessner et al., 2009)
(UBE3A)
In controls
0 / 2,519
CNVs at 15q11-13
In ASD individuals
4 / 522 (0.8%)g
(Depienne et al., 2009)
CNVs at 16p11.2
In ASD families
12 / 751 (1.6%)
(Weiss et al., 2008)
In controls
5 / 4,234 (0.1%)
In ASD individuals
3 / 299 (1.0%)
In controls
7 / 18,834 (0.04%)
16p11.2duplication
In ASD individuals
9 / 2,195 (0.4%)c
(Glessner et al., 2009)
In controls
4 / 2,519 (0.2%)
16p11.2 deletion
In ASD individuals
8 / 2,195 (0.4%)h
(Glessner et al., 2009)
In controls
4 / 2,519 (0.2%)
CNV gain at 1q21
In ASD families
3 / 1,181 (0.3%)d
(AGPC, 2007)
CNV at 17p12
In ASD families
3 / 1,181 (0.3%)i
(AGPC, 2007)
CNV gain at 22q11.2
In ASD families
2 / 1,181 (0.2%)d
(AGPC, 2007)
22q11.2 duplication
In ASD individuals
9 / 2,195 (0.4%)
(Glessner et al., 2009)
In controls
0 / 2,519
De novo CNVs
In ASD families
10 / 1,181 (0.8%)
(AGPC, 2007)
Co-segregated cases
3 / 1,181 (0.3%)j
De novo CNVs
In ASD individuals
14 / 195 (7.2%)k
(Sebat et al., 2007)
In sporadic cases
12 / 118 (10.2%)
In multiplex families
2 / 77 (2.6%) k
In controls
2 / 196 (1.0%)
De novo CNVs
In ASD families
27 / 427 (6.3%)
(Marchall et al., 2008)
In sporadic cases
4 / 56 (7.1%)
In multiplex families
1 / 49 (2.0%)
De novo CNVs
In ASD families
50 / 876 (5.7%)l
(Pinto et al., 2010)
In simplex families
22 / 393 (5.6%)
In multiplex families
19 / 348 (5.5%)
Table 1.
The prevalence of variants in gene regions recently implicated in idiopathic ASDASDs: autism spectrum disorders; NLGN: neuroligin gene; NRXN: neurexin gene; CNTN: contactin gene; AUTS: autism susceptibility candidate gene; CNV: copy number variation; AGPC: the Autism Genome Project Consortium. aTwo nonsynonymous SHANK3 mutations were revealed in 4 ASD families and 2 control individuals. bIn the SHANK3 study, de novo truncating mutations in two families and a chromosomal rearrangement in one family were demonstrated as the strict co-segregated cases whose gene variants were found only in individuals with ASD among family members including parents. cOne de novo case is included. dStrict co-segregation was not shown. eTwo cases with mild facial dysmorphism are included. fTwo de novo cases are included. gThree de novo cases are included. hFive de novo cases are included. iOne case is included as a co-segregated family. jIn ASD families with two or more affected individuals (multiplex families), three de novo CNVs were found in both ASD sibs. kTwo multiplex families whose variant-phenotype co-segregation is not mentioned are included. l>0.6% cases are carrying two or more de novo events.
2003), and high heritability does not vindicate the condition as a diagnostic category (Keller & Miller, 2006). There is as yet no qualitative biological marker including microscopic lesions that can reliably help to categorize a genetically homogeneous autism subtype (Amaral et al., 2008; Moldin et al., 2006; Santangelo & Tsatsanis, 2005; Schmitz & Rezaie, 2008). In this article, the significance of gene variants which have currently been detected in autistic individuals is carefully reconsidered and the outstanding questions are addressed from multidisciplinary points of view. Such an attempt may highlight the importance of the notion that the evolutionally survived trait is the phenotypic diversity itself, in which ASD is included as an extreme tail. In addition, important concepts and mechanisms for the genetic basis of phenotypic diversity are also reviewed.
2. Facts and questions
Although some authorities appreciated the smooth behavioral continuum between individuals with ASD and the non-autistic majority (Frith, 2001; Happé, 1999; Rapin, 1997; Wing, 1997), idiopathic ASD has sometimes been misinterpreted as a qualitative disorder which can be clearly distinguished from normal development. The boundary between individuals with low-functioning ASD and a communicative subtype (Asperger syndrome) has also been misrepresented as to be qualitatively distinct (Simpson, 2003). Even the differentiation between Asperger syndrome and high-functioning ASD could be made with authority (Kamp-Becker et al., 2010). These biased constructions may be attributable to referral bias in general practice or increased probability of clinical ascertainment in individuals with low achievement (Skuse, 2007). Although ASD can still be documented as a categorical entity in clinically ascertained samples (Frazier et al., 2010), the fact that the autistic phenotype extends beyond its formal diagnostic boundaries has underscored the significance of quantitative evaluations (Lamb et al., 2000; Maestrini et al., 2000), and many population studies revealed that ASD including high-functioning subtypes are best characterized as an extreme of some bell-shaped behavioral dimensions that distribute quantitatively (Constantino & Todd, 2000; Constantino & Todd, 2003; Happé et al., 2006; Hoekstra et al., 2007; Posserud et al., 2006; Ronald et al., 2005; Ronald et al., 2006a, 2006b; Skuse et al., 2005). The description ‘qualitative’ in the autism criteria in the Diagnostic and Statistical Manual of Mental Disorders (DSM) is removed and Asperger’s disorder (Asperger syndrome) is subsumed into ASD in the draft of DSM-5 (http://www.dsm5.org /Pages/Default.aspx). The three quantitative domains including sociability, communication, and rigid/repetitive behavior correlate modestly to each other in the population (Dworzynski et al., 2007; Ronald et al., 2005, 2006a, 2006b), and the coincidence of these phenotypic extremes is also observed in hyperactive individuals with attention-deficit/hyperactivity disorder (AD/HD) (Hattori et al., 2006; Ijichi & Ijichi, 2007; Reiersen et al., 2007; Ronald et al., 2008). The diagnosis of autism is highly affected by the circumstantial consequence of social adaptability and autistic recognition and behavior sometimes does not become fully manifest until social demands exceed the individual’s limited capacities (the draft of DSM-5). The clinical picture can change with increasing age and in different circumstances (Wing, 1997), and the behavioral plasticity or clinical improvement is evident in supportive circumstances by structured behavioral interventions, mentoring, and/or social involvement with appropriate accommodation (Garcia-Villamisar & Hughes, 2007; Ijichi & Ijichi, 2007; McGovern & Sigman, 2005; Tonge et al., 1994).
The most unique and potentially meaningful property of autistic cognition is savant skill. The estimated prevalence of the cognitive superiority in ASD varies from 10% to surprising numbers (Dawson et al., 2007; Happé, 1999; Rapin & Katzman, 1998). The supposed common ‘high intelligence’ in autistic individuals with low IQ may involve high processing speed, prodigious memory capacities, and heightened primary sensory processing (Boddaert et al., 2005; McCleery et al., 2007; Scheuffgen et al., 2000). These cognitive superiorities are believed to have the same origin as the social difficulties in ASD (Brosius & Kreitman), and the term, ‘autistic savant skills’, is used to describe one of the core cognitive features of ASD (Badcock & Crespi, 2006; Scheuffgen et al., 2000). As a unifying explanation which covers the manifold autistic characteristics, excessive neuronal processing (a hyper-functionality model) is also implicated as opposed to usual hypo-functionality explanations (Markram et al., 2007).
The ratio of sibling recurrence risk to population prevalence is approximately 50 with an overwhelming predominance of sporadic cases, suggesting the multifactorial nature of ASD (AGPC, 2007). The high monozygotic concordance rate in twins and the modest recurrence risk in dizygotic twins and among siblings may also suggest that the genetic architecture for ASD has the same complexity as those for human physical appearances including facial characteristics and brain gray matter volume (Ijichi & Ijichi, 2004). In traditional views, the modest correlation between autistic behavioral domains in population studies implies that there is no single (genetic or endophenotypical) cause for the three autistic extreme characteristics and a mere coincidence of the phenotypic extremes might be the true nature of autistic social difficulties (Happé et al., 2006). Although positive assortative mating might cause phenotypic anticipation and a negative assortative mating between the couple might gather the non-overlapping genetic components in a baby (Ijichi et al., 2008), there is no evidence for such assortative mating (Hoekstra et al., 2007).
As exemplified in Table 1, there is, so far, no universal genetic marker which is co-segregated with ASD in the affected families. In contrast to the early prediction (30-40%) (Beaudet, 2007), no more than 5-7% of ASD cases may be traceable to single or multiple genetic concomitant(s) (Table 1). Although many whole-genome scans for autism susceptibility loci have identified a lot of linkage peaks, the reproduction of the results is exceptional and association studies have failed to identify the gene variants (Sykes & Lamb, 2007). The regions of structural variants including copy number variations (CNVs) seldom conform to the linkage peaks (Sebat, 2007). The lack of an unambiguous pathophysiological marker is also one of the important characteristics of idiopathic autism (Amaral et al., 2008; Moldin et al., 2006; Santangelo & Tsatsanis, 2005; Schmitz & Rezaie, 2008). The only anatomical candidate which can be consistently co-segregated with ASD including masked autistic savants may be a quantitative increase in the number of processing units of cortex (minicolumns) (Casanova, et al., 2002, 2007). The increase in the number of minicolumns is thought to be associated with mammalian brain evolution, and the finding can explain other apparent tendencies revealed in some autistic individuals, including increases in the volume of brain structures and the prevalence of epilepsy (Casanova et al., 2006). Recent preliminary findings suggest that the tendency of brain overgrowth originates prenatally (Hobbs et al., 2007; Leonard et al., 2008). Furthermore, there is no biological deficit including chemical and molecular findings which is universal in individuals with ASD or can reliably help to identify putative subgroups that are genetically homogeneous (Lauritsen & Ewald, 2001). Over-expression of neuron-associated genes is still one of the candidates for molecular markers (Lepagnol-Bestel et al., 2008; Maussion et al., 2008; Rinaldi et al., 2007).
The scientific puzzle, which is metaphorically described as “myopic investigators are still patting the elephant” (Rapin, 1999) remains to be solved (Baron, 2008). Why is the male to female ratio biased (3-4 to 1)? Why cannot the behavioral uniformity with strong genetic contribution be interpreted by common gene variant alleles? Why is the disparity between monozygotic and dizygotic concordances so large? Why do the autistic behavioral domains correlate modestly? Although these questions may provide very important clues and are encouraging researchers to speculate on reasons, the jigsaw is still incomplete. Missing puzzle pieces include the solution of the evolutionary mystery of autism prevalence. Human conditions can be selected and survive when it is somehow associated with increased reproductive success (Nesse & Williams, 1994). However, in spite of the hypo-reproductive tendency of behaviors in extreme cases with ASD (Lord et al., 2000), the estimated high prevalence has never declined (Baird et al., 2006; CDC, 2009; Fombonne, 2009).
3. Genetic and environmental explanations
It is recently recognized that ASD has the highest prevalence (more than 0.5%) in childhood neurodevelopmental conditions (CDC, 2009; Fombonne, 2009). In traditional frameworks, in which researchers are searching the human genome for the condition-specific genetic variants, three genetic models should be considered as the genetic mechanism for such a common phenotypic condition (Gibson, 2009). The quite low effect size of each ASD-related variant is suggested to be the cause of difficulty in replication of the positive findings in the common disease-common variant (CD-CV) model (Anney, 2010). Although a rare alleles of major effect (RAME) model is one of the core principles for recent genome-wide association studies in ASD (Gibson, 2009), the replication may also be complicated by chance findings, as well as differences in ascertainment, because of the modest relative risk of the rare alleles (Anney, 2010). The third model, the infinitesimal model, can make an excuse for the situation of genetic studies, because it is very hard to identify rare variants of small effect by genetic means (Manolio et al., 2009). It is, anyhow, clear that it’s time to reconsider and question simple intuitive models that link a human complex condition to mutation (Gibson, 2009).
3.1. Genetic factors
The non-universality of the candidate gene variants which have previously been implicated in ASD may be consistent with the speculation that heterogeneous sets of gene variants can contribute to ASD (Betancur, 2011; Beaudet, 2007; Garber, 2007). Furthermore, in order to explain the modest correlations between the three autistic behavioral domains, the presence of domain-specific heterogeneous sets of gene variants are also suggested (Happé et al., 2006). However, even novel genetic means including whole genome screening using microarray-based hybridization cannot fully confirm these speculations (Table 1). The frequent absence of diagnostic history of ASD in the parents of an idiopathic ASD proband may suggest that the supposed variants should be carried by a non-ASD parent (incomplete penetrance) or the proband should have de novo mutations (Beaudet, 2007; Constantino & Todd, 2005; Zhao et al., 2007) (Table 2). However again, such genetic transmission is still one of the hypotheses and the concomitant de novo variants can be detected only in a minor part of the cases (Table 1). The number of candidate gene regions is still increasing without a convincing and comprehensive demonstration of the link between such variants and autistic developmental trajectory (Glessner et al., 2009).
The genetic contribution to a quantitative trait may be attributable to the cumulative effect of a set of quantitative trait loci (QTLs) (Plomin et al., 1994, 2009; Plomin & Kosslyn, 2001). Each QTL is neither necessary nor sufficient for the overall phenotypic outcomes, the effect size of each QTL may fluctuate according to other genetic backgrounds (epistasis, non-additive gene-gene interactions) and the environment (gene-environment interactions), and a QTL may affect more than one phenotypic trait (pleiotropy). The concept of epistasis had initially been introduced for ASD as an alternative explanation of the incomplete penetrance or as a risk factor model (Bradford et al., 2001; Folstein & Rosen-Sheidley, 2001; Jones & Szatmari, 2002). Because natural chromosomal and segmental shuffling during normal meiosis is a strong random modifier of epstatic effects among QTLs in a sib-pair and dizygotic twins, the big disparity between monozygotic and dizygotic concordances in autism may be explained by the presence of epistatic QTLs. Pleiotropy can account for the presence of autistic savants. The modest correlation among autistic behavioral domains can also illustrated by unsynchronized epistatic pleiotropy (Ijichi et al., 2008). To explain the sporadic manner of the prevalence and the survival of hypo-reproductive autistic extremes, the implication of epistasis-associated intergenerational oscillation of phenotypic outcomes was introduced (Ijichi et al., 2008). Some candidates for autism QTLs have been reported (Ashley-Koch et al., 2006; Coutinho et al., 2007; Jiang et al., 2004; Weiss et al., 2007), linkage analysis with quantitative measures of some autistic characteristics revealed QTL signals (Alarcón et al., 2002, 2005; Chen et al., 2006; Duvall et al., 2007), and a quantitative covariance analysis can confirm the high genetic correlation between ‘social motivation’ and ‘range of interest/flexibility’ (Sung et al., 2005). Although the supposed contribution of QTLs ought to be traced in family studies or genome scans according to a traditional logic, “the causal gene variant can be cosegregated with the phenotypic variant”, the delay and difficulty in detecting the causal variant alleles at QTLs is strangely common to all idiopathic quantitative traits including autism, physical and physiological characteristics, and personalities (de Geus et al., 2001; Fullerton, 2006; Palmert & Hirschhorn, 2003; Willis-Owen & Flint, 2006).
Facts and questions
Explanations
Penetrance
De novo
QTLs
Environment
The quantitative feature
(○)
-
○
(○)
Partial behavioral plasticity
-
-
-
○
The presence of autistic savants
-
-
(○)
-
Strong genetic contribution
○
○
○
-
Usually sporadic without family history
(○)
○
(○)
○
Domain-specific genetic factors
-
-
(○)
-
Lack of the common genetic marker
○
○
○
-
Lack of the common pathological lesion
-
-
-
-
Lack of the common chemical marker
-
-
-
-
Lack of the common molecular marker
-
-
-
-
Why is the male to female ratio biased?
(○)
(○)
(○)
(○)
Why is it so difficult to detect autism genes?
-
-
-
-
Why do hypo-reproductive extremes survive?
-
○
-
(○)
Table 2.
Genetic and environmental explanations for the facts and outstanding questions in idiopathic autism researchesPenetrance: Poor penetrance of heterogeneous gene variants; De novo: De novo involvement of heterogeneous gene variants; QTLs: Quantitative trait loci; Environment: Environmental contribution; ○: explainable; (○): unexplainable by itself but explainable with some further speculation; -: hard to explain
3.2. Epigenetic factors and ASD
Phenotypic outcomes with robustness or plasticity cannot be exclusively determined by the DNA sequence itself which looks like the core genetic factor of the phenotype (Goldberg et al., 2007). Epigenetics is the study of changes in gene expression that occur without a change in DNA sequence and the epigenotype is meiotically and mitotically transmissible (Morris, 2005; van Vliet et al., 2007). Although the significance of the contribution made by epigenetic factors to human complex traits remains unclear, it is speculated that epigenetic factors can influence gene-environment interactions and the liability/outcomes of the traits (van Vliet et al., 2007). Epigenetic changes in gene expression are achieved through RNA-associated silencing, DNA methylation, and histone modifications (Morris, 2005), and cis-acting expansion of the epigenetic influences on the flanking genes is referred to as genomic imprinting which results in parent of origin-specific gene expression (Pauler et al., 2007). The epigenetic factors and genomic imprinting may be implicated in syndromic autistic individuals with some single gene/chromosomal disorders including Rett syndrome, fragile X syndrome, Prader-Willi syndrome, and Angelman syndrome, and a variety of factors associated with epigenetic modifications have been considered as candidates for autism genes (Badcock & Crespi, 2006; Jiang et al., 2004; Persico & Bourgeron, 2006; Schanen, 2006; Skuse, 2000; van Vliet et al., 2007). These factors, however, cannot be the common prerequisite for idiopathic ASD at least in the majority of the cases (Jiang et al., 2004; Persico & Bourgeron, 2006), and the power of epigenetic factors are recognized as an accidental cue to shift the quantitative distribution of the autistic traits in a threshold model (Skuse, 2000). If the epigenetic factors act only in gene-environment interactions in idiopathic cases, the epigenetic contribution should be modest in the overall underpinnings. Given an unforeseen transmissible powerful architecture connecting genotype and phenotype for phenotypic diversity independent of genetic diversity, the epigenetic mechanism should be referred to as merely one of the molecular-level environments derived from gene networks.
3.3. Environmental factors
Environmental factors contribute no more than 10% to ASD (Garber, 2007). However, the environmental factors including rubella, thalidomide, and valproic acid embryopathies may still be important as additive triggers of the clinical manifestation (Jones & Szatmari, 2002; Persico & Bourgeron, 2006). Environmental contributions including behavioral experiences are originally misunderstood to explain the patterns of familial recurrence risks observed in autism studies (Jorde et al., 1991). Because the genetic components affecting autistic traits seem to be the same across the sexes (Constantino & Todd; Hoekstra et al., 2007), it can be speculated that the lower prevalence of autistic traits in girls is the result of increased sensitivity to early environmental influences that operate to promote social competency (Constantino & Todd, 2003). The minimal contribution of shared environmental influences (Ronald et al., 2006a) may be associated with the autistic behavioral manifestations including resistance to change or insistence on sameness.
Combinations of the traditional theories (poor penetrance, de novo mutations, and QTLs and the environmental contribution) may answer not a few of the outstanding questions in idiopathic autism research (Table 2). However, in spite of the presence of a big genetic contribution to the autistic development, the question, “Why is it difficult to detect autism gene variants?”, still remains to be resolved. In addition, the significance of both de novo mutations and the environmental modification is just a speculation in a part of the ASD cases.
4. Evolutionary explanations
Does idiopathic ASD really represent many distinct conditions with numerous etiologies (Geschwind, 2007)? Is it really time to give up on a single explanation for autism (Baron, 2008; Happé et al., 2006)? A variety of qualitative concomitants, including gene variants and environmental factors, have already been demonstrated in part of autistic cases as exemplified above. However, it may be still too early to reach the conclusion even in such frameworks, because no single qualitative process associated with the concomitants can indicate the molecular or chemical differences between the autistic developmental extremes and the non-autistic majority. In order to understand human complex traits, genetic, molecular, and biochemical explanations should be combined with evolutionary explanations (Nesse & Williams, 1994). In autistic individuals, ASD per se does not shorten the span of life (Gillberg et al., 2010). Although high or preserved androgenic competence is suspected in ASD (Tordjman et al., 1997), the extreme cases almost never marry (Lord et al., 2000). The hypo-fertility results from reduced opportunity or behavioral ability in the mating arena. Therefore, we must probe into who is enjoying the reproductive benefits of the genetic architecture for ASD in the evolutionary framework (Table 3).
Who gets the reproductive benefits?
Hypotheses or mechanisms
References
None (an inevitable outcome)
Mutation-selection balance theory
(Keller & Miller, 2006)
Unaffected carriers of genetic factors
Hyper-systemizing theory (extreme male brain theory) Extreme imprinted brain theory
(Baron-Cohen, 2002)
(Badcock & Crespi, 2006)
All of the non-autistic majority
Population benefit theory Monomorphic loci theory
(Fitzgerald, 2002) (Ijichi et al., 2011)
Table 3.
Evolutionary explanations for the survival of autistic extremeness
4.1. Mutation-selection balance theory
In the mutation-selection balance theory, individuals with a high load of mutations are postulated to be at higher chance of passing risk on to their offspring, and it is not necessary that there are individuals with the reproductive benefits (Keller & Miller, 2006). Importantly, according to the proposed model, everyone alive has minor brain deviations that cause them to be a little bit abnormal in behavioral and cognitive dimensions (Keller & Miller, 2006). The non-autistic majority in the population is regarded as the genetic carrier-state for ASD and the mutation load and the risk of having autistic offspring may vary quantitatively. In the mutation-selection balance theory, balancing selection for genetic diversity is recognized to be unsuitable to explain persistent heritability in human conditions (Keller & Miller, 2006; Zhang & Hill, 2005). One of the grounds of this exclusion of balancing selection is the absence of an ongoing homeostatic mechanism that counteracts the homogenizing effect of genetic drift and stabilizing selection, and the reproductive benefits of the genetic burden for autism are not addressed (Keller & Miller, 2006). The mutation-selection perspective can be an evolutionary interpretation of a cumulative effect of de novo mutations and is at least consistent with the quantitative distribution of autistic domains.
4.2. Extreme male brain theory
The second is a group of theories in which only a part of the population is regarded as the genetic carrier-state for ASD. The prevalence or maintenance of positive assortative mating between the non-autistic carriers is critical to accumulate genetic factors in these theories, and the remaining non-autistic majority does not have the genetic components for ASD. In the hyper-systemizing theory, the unaffected carriers of the genetic factors are high systemizers and ASD is the result of both parents being the high systemizers (Baron-Cohen, 2002, 2004, 2006). Systemizing is the drive to understand and predict the next step of inanimate events and acts contrary to empathizing. In males, the systemizing mechanism is set at a slightly higher level than non-autistic males (Baron-Cohen, 2004). This extreme male brain theory of autism had originally been proposed by Asperger in 1944. Individuals including both parents of individuals with autism, who are placed in the adjacent part to the autistic extremeness, systemize at a higher level than average (above average systemizers) and account for approximately a half of the vast majority. Over successive generations, the above average systemizers carry the genetic components for ASD and might enjoy the reproductive benefits. As one of the genetic bases of the hyper-systemizing theory, the extreme imprinted brain theory had been proposed (Badcock & Crespi, 2006).
4.3. Population benefit theory and individual benefit theory
In the third framework, it is suggested that the evolutionarilly selected and conserved phenotype is not the hypo-reproductive extremeness but the whole quantitative distribution itself. A group selection theory has been introduced to bring sense into the link between autism and exceptional creativity (Fitzgerald, 2003). In this population benefit theory, the creativity, which can be concomitant with autism, benefits all members of the human community and the community can survive. On the other hand, the third framework can also include individual benefit concepts (the monomorphic loci theory) (Ijichi et al., 2011). In the individual benefit concepts, everybody has both the genetic architecture for ASD and the possibility to enjoy the reproductive benefits of autism genes. Each phenotypic outcome, however, varies individually mainly according to the differences in genetic background noise and environmental factors, whose functions are not necessarily related to ASD phenotypes directly. In the process of reaching the monomorphic loci theory, the epistasis-mediated intergenerational oscillation of phenotypic outcomes has been advanced in a QTL model (Ijichi et al., 2008). The monomorphic loci theory does not dismiss the comprehensive view of the known genetic contributions, including major gene effects and additive genetic networks (Ijichi et al., 2011). The postulated involvement of monomorphic loci can be valid as merely one of the genetic constituents in complex (additive and/or non-additive) interactions with polymorphic loci.
4.4. The monomorphic loci theory and gene networks
Because both positive and negative epistasis may be byproducts of evolution (L. Azevedo et al., 2006; R.B.R. Azevedo et al., 2006; Harrison et al., 2007), the invisibility of the contribution of monomorphic epistatic loci from the traditional genetic view is an attractive candidate for the explanation of the black box between polymorphic genotype and phenotypic diversity (Ijichi et al., 2011). Complex phenotypes have hierarchical structures, including RNA (transcript traits), protein, metabolite, and functional levels. It has been suggested that less heritability of metabolite traits than transcript traits is associated with the difference in the quantity of biological noise between the genetic determinants and the trait (Rowe et al., 2008). The more steps that are involved between genotype and the trait level, the more biological noise may reside in the process. Such biological noise originates from inter-locus interactions and gene-environment interactions, and the inter-locus interactions may have an important role in the biological noise. Additive and/or non-additive inter-locus interactions with other loci are available in a variety of processes including cis-, trans-, and inter-cellular interactions (Figure 1). The presence of gene-environment-gene circuits may make it difficult to distinguish inter-locus interactions from gene-environment interactions in the biological noise (Ijichi et al., 2011). In these interactions, an intergenerational change in the number or property of factors (environment and/or other related loci) in the regulatory circuit may easily individualize the balance of each hierarchical trajectory (coding RNA, non-coding RNA, translation, autocrine, paracrine, and endocrine levels) and individually determine the developmental outcomes. The net non-additive effects of the biological noise are metaphorically interpreted as hub-and-spoke structures of regulatory networks among polymorphic loci (Benfey & Mitchell-Olds, 2008).
Figure 1.
Cellular and molecular interactions of biological noise in regulatory networks around a gene locus (A). Additive and/or non-additive phenomena can be involved in each interaction (Ijichi et al., 2011). In this explanation, an arrow represents the net contribution between loci and the gene-environment relationship. The locus A can interact with other loci in association with coding RNA and/or non-coding RNA level in cis-acting manner (①, ②) and trans-acting manner (③, ④). The cis-acting interactions are involved in genetic imprinting. After translation, interactions can be mediated through autocrine, paracrine, and endocrine mechanisms (⑤, ⑥). Gene-environment interactions can modify penetrance of the outcomes affected by the locus A. The network constituents can change the sensitivity to environmental influences (⑦), that can provide gene-environment-gene circuits. In the monomorphic loci theory, the gene A can be monomorphic and the link between monomorphic A and the A-associated polymorphic noise is usually invisible in the context of traditional genetics.
5. Quantitative domains and genetic factors
The distributional shift of a bell-shaped curve and the change in the curve shape illustrates the mean value change and the variance alteration of the quantitative dimension, respectively (Gibson, 2009). These changes can affect the proportion of individuals with autism to those without as determined by a liability threshold. The biased male to female ratio (3-4 to 1) in ASD is plausibly interpreted as a distributional shift of the quantitative bell-shaped curve as a gender gap. In the hyper-systemizing theory, the male systemizing mechanism is set at a slightly higher level than in females (Baron-Cohen, 2004). In an imprinted-X liability threshold model, actions of some X-linked genes, which are expressed only from paternal X-chromosome, are suggested to be associated with the male predisposition to ASD (Skuse, 2000). The gender is a bimorphic genetic variation and there is a gender gap in sensitivity or vulnerability to environmental factors (Constantino & Todd, 2003). The relationship between a bell-shaped quantitative distribution and the genetic factors underlying the complex phenotype still remains to be elucidated.
5.1. Polygenic liability model
The traditional concept of polygenic liability supposes a normal distribution of frequencies of susceptibility variant alleles (Gibson, 2009). The manner of the allele contribution is additive, and each allele contribution usually results in a positive or negative effect on the phenotype in the carrier individual and the quantitative population dimension results from such additive allele contributions. To explain the smooth normal distribution, an environmental variance of each allele contribution is addressed in this model.
In a genetic model, oligogenicity with epistasis, the contributing genes are likely to be common ones in the population (Folstein & Rosen-Sheidley, 2001). There is no evidence that the genetic causative processes affecting the autistic extreme are different from those contributing the autistic dimension including individuals without autism (Ronald et al., 2006a). If the presence of epistasis, pleiotropy, and gene-environment interactions are all supposed, the polymorphic genetic underpinning is referred to as QTLs (Plomin et al., 1994, 2009; Plomin & Kosslyn, 2001). However, it is also the fact that the delay and difficulty in detecting the causal variant alleles at QTLs is common to all idiopathic quantitative traits including ASD, physical and physiological characteristics, and personalities (de Geus et al., 2001; Fullerton, 2006; Palmert & Hirschhorn, 2003; Willis-Owen & Flint, 2006).
If the genetic factors for a tail of the bell-shaped curve are different from those for the majority and have extremity-specific properties including serious involvement of coding gene segments (Mitchison, 2000), the variant alleles should be more detectable. Because the genetic contribution in ASD is the biggest in human complex traits and the environmental influence on ASD is quite minimal as described above, the difficulty in finding the universal genetic marker for ASD warrants the necessity of a paradigm shift.
5.2. Additive and non-additive interactions between mono- and poly-morphic loci
It has been emphasized that the three behavioral domains of ASD modestly correlate to each other and the set of genes for each domain may be partly different (Dworzynski et al., 2007; Happé et al., 2006; Ronald et al., 2005, 2006a, 2006b). The speculated modest genetic overlap among autistic domains may be indistinguishable from that among human complex phenotypes including ASD, bipolar disorder, and schizophrenia (Rzhetsky et al., 2007), suggesting that the autistic domains and these psychiatric conditions might share the same genetic architecture at least in part (Craddock & Owen, 2010). In an argument about domain-specific genes for cognitive functions, it is expected that the domain-general genes are responsible for the brain infrastructure including receptors, neurotransmitters, dendritic spines, synapse vesicles, and axonal filaments (Marcus & Rabagliati, 2006). Although the universality of the domain-general genes for cognitive functions among other human complex phenotypes is controversial, genes for the brain infrastructure are also current topics in the field of ASD (Garber, 2007; Persico & Bourgeron, 2006). Both the heterogeneity of genetic markers for ASD and the modest correlation among autistic core domains can be explained by epistasis-mediated oscillation of the domain-general effect values and unsynchronized epistatic pleiotropy in the monomorphic loci theory, which never dismiss the comprehensive view of the known genetic contributions, including major gene effects and additive genetic networks (Ijichi et al., 2011). The assumption of the random outcomes mediated by the non-additive interactions between functional monomorphic loci and polymorphic backgrounds may transform the traditional complementary roles of some monomorphic loci (Gjuvsland et al., 2007) to active and leading roles for the phenotypic diversity (Ijichi et al., 2011). However, the controversy concerning the importance of non-additive effects in phenotypic diversity still exists (Gale et al., 2009; Hill et al., 2008; Malmberg & Mauricio, 2005).
5.3. Social environmental changes and decanalization
The decanalization concept may have sizable significance in searching the cause of the maintained or increasing prevalence of ASD. Canalization is an evolutionary phenomenon characterized by robustness to genetic or environmental perturbation, and most individuals tend to cluster around the optimal phenotype in canalized populations (Gibson, 2009). If the phenotypic dimension consists of multiple endophenotypic vectors which have nonlinear relationships to each other and are partially determined by genetic factors, overt environmental perturbations for one of the endophenotypes can be the cue of decanalization, which changes the shape of the phenotypic demensional distribution (Gibson, 2009). Social environmental perturbations may also shift the entire distribution of ASD liability, or move the liability threshold.
6. Conclusions
The difficulty in detecting the universal biological marker for the predisposition to ASD presents significant challenges and conflicts to researchers in related fields. The reported gene variants in some sporadic cases with idiopathic ASD are nothing but one of the concomitants, until the molecular or biological trajectory underlying autistic development is clearly delineated or association studies reproduce the causal relationship. Before the speculation that idiopathic ASD represents many distinct conditions with numerous etiologies, the quantitative manner of the distribution of the behavioral domains and the fact that ASD is a mere tail of the behavioral dimensions should strictly be considered and emphasized. Even combinations of traditional theories including poor penetrance, de novo mutations, quantitative trait loci, and environmental contribution cannot fully account for the entire genetic underpinning. Importantly, the almost monolithic insight into the prevalence of ASD can only be obtained in an evolutionary framework on the assumption that the complex genetic networks are responsible not for the individual cases but for the human behavioral diversity itself. Gender differences, environmental factors, epigenetic mechanisms including genetic imprinting, and major gene effects may all be mere accidental modifiers of the relationship between the diversity and the liability threshold.
Acknowledgments
The authors greatly thank Professor Bryan H. King for his helpful suggestions.
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Introduction",level:"1"},{id:"sec_2",title:"2. Facts and questions",level:"1"},{id:"sec_3",title:"3. Genetic and environmental explanations",level:"1"},{id:"sec_3_2",title:"3.1. Genetic factors",level:"2"},{id:"sec_4_2",title:"3.2. Epigenetic factors and ASD",level:"2"},{id:"sec_5_2",title:"3.3. Environmental factors",level:"2"},{id:"sec_7",title:"4. Evolutionary explanations",level:"1"},{id:"sec_7_2",title:"4.1. Mutation-selection balance theory",level:"2"},{id:"sec_8_2",title:"4.2. Extreme male brain theory",level:"2"},{id:"sec_9_2",title:"4.3. Population benefit theory and individual benefit theory",level:"2"},{id:"sec_10_2",title:"4.4. The monomorphic loci theory and gene networks",level:"2"},{id:"sec_12",title:"5. Quantitative domains and genetic factors",level:"1"},{id:"sec_12_2",title:"5.1. Polygenic liability model",level:"2"},{id:"sec_13_2",title:"5.2. Additive and non-additive interactions between mono- and poly-morphic loci",level:"2"},{id:"sec_14_2",title:"5.3. 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1Health Service Center, Kagoshima University, Kagoshima, Japan
1Health Service Center, Kagoshima University, Kagoshima, Japan
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Tzallas, Markos G. Tsipouras, Dimitrios G. Tsalikakis, Evaggelos C. Karvounis, Loukas Astrakas, Spiros Konitsiotis and Margaret Tzaphlidou",authors:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",slug:"alexandros-tzallas"},{id:"94709",title:"Dr.",name:"Markos",middleName:null,surname:"Tsipouras",fullName:"Markos Tsipouras",slug:"markos-tsipouras"},{id:"94710",title:"Dr.",name:"Dimitrios",middleName:null,surname:"Tsalikakis",fullName:"Dimitrios Tsalikakis",slug:"dimitrios-tsalikakis"},{id:"94712",title:"Dr.",name:"Loukas",middleName:null,surname:"Astrakas",fullName:"Loukas Astrakas",slug:"loukas-astrakas"},{id:"94714",title:"Dr.",name:"Spiros",middleName:null,surname:"Konitsiotis",fullName:"Spiros Konitsiotis",slug:"spiros-konitsiotis"},{id:"94873",title:"Prof.",name:"Margarita",middleName:null,surname:"Tzaphlidou",fullName:"Margarita Tzaphlidou",slug:"margarita-tzaphlidou"},{id:"128137",title:"Dr.",name:"Evaggelos",middleName:null,surname:"Karvounis",fullName:"Evaggelos Karvounis",slug:"evaggelos-karvounis"}]},{id:"30008",title:"Automated Non-Invasive Identification and Localization of Focal Epileptic Activity by Exploiting Information Derived from Surface EEG Recordings",slug:"automated-non-invasive-identification-and-localization-of-focal-epileptic-activity-by-exploiting-inf",signatures:"Amir Geva, Merav Ben-Asher, Dan Kerem, Mayer Aladjem and Alon Friedman",authors:[{id:"31020",title:"Prof.",name:"Alon",middleName:null,surname:"Friedman",fullName:"Alon Friedman",slug:"alon-friedman"},{id:"101306",title:"Dr",name:"Amir",middleName:null,surname:"Geva",fullName:"Amir Geva",slug:"amir-geva"},{id:"101307",title:"Dr.",name:"Dani",middleName:null,surname:"Kerem",fullName:"Dani Kerem",slug:"dani-kerem"},{id:"127445",title:"MSc.",name:"Merav",middleName:null,surname:"Ben-Asher",fullName:"Merav Ben-Asher",slug:"merav-ben-asher"},{id:"127446",title:"Prof.",name:"Mayer",middleName:null,surname:"Aladjem",fullName:"Mayer Aladjem",slug:"mayer-aladjem"}]},{id:"30011",title:"Hyper-Synchronization, De-Synchronization, Synchronization and Seizures",slug:"hyper-synchronization-de-synchronization-synchronization-and-seizures",signatures:"Jesús Pastor, Rafael García de Sola and Guillermo J. Ortega",authors:[{id:"27730",title:"Dr.",name:"Jesús",middleName:null,surname:"Pastor",fullName:"Jesús Pastor",slug:"jesus-pastor"},{id:"36503",title:"Dr.",name:"Rafael G",middleName:null,surname:"Sola",fullName:"Rafael G Sola",slug:"rafael-g-sola"},{id:"85177",title:"Dr.",name:"Guillermo",middleName:null,surname:"Ortega",fullName:"Guillermo Ortega",slug:"guillermo-ortega"}]},{id:"30013",title:"Long-Term Monitoring: An Overview",slug:"long-term-monitoring-an-overview",signatures:"B. Mesraoua, D. Deleu and H. G. Wieser",authors:[{id:"94911",title:"Dr.",name:"Boulenouar",middleName:null,surname:"Mesraoua",fullName:"Boulenouar Mesraoua",slug:"boulenouar-mesraoua"},{id:"94941",title:"Prof.",name:"Heinz Gregor",middleName:null,surname:"Wieser",fullName:"Heinz Gregor Wieser",slug:"heinz-gregor-wieser"},{id:"130893",title:"Prof.",name:"Dirk",middleName:null,surname:"Deleu",fullName:"Dirk Deleu",slug:"dirk-deleu"}]},{id:"30015",title:"Neuropsychological Evaluation in Epilepsy Surgery – A Cross-Cultural Perspective",slug:"neuropsychological-evaluation-in-epilepsy-surgery-a-cross-cultural-perspective",signatures:"Ahmed M. Hassan",authors:[{id:"85712",title:"Dr.",name:"Ahmed",middleName:"M.",surname:"Hassan",fullName:"Ahmed Hassan",slug:"ahmed-hassan"}]},{id:"30016",title:"Psychic Seizures and Their Relevance to Psychosis in Temporal Lobe Epilepsy",slug:"psychic-seizures-and-their-relevance-to-psychosis-in-temporal-lobe-epilepsy",signatures:"Kenjiro Fukao",authors:[{id:"32519",title:"Dr.",name:"Kenjiro",middleName:null,surname:"Fukao",fullName:"Kenjiro Fukao",slug:"kenjiro-fukao"}]},{id:"30017",title:"Personality Profiles of Patients with Psychogenic Nonepileptic Seizures",slug:"personality-profiles-of-patients-with-psychogenic-non-epileptic-seizures",signatures:"Krzysztof Owczarek and Joanna Jędrzejczak",authors:[{id:"103725",title:"Dr",name:"Krzysztof",middleName:null,surname:"Owczarek",fullName:"Krzysztof Owczarek",slug:"krzysztof-owczarek"},{id:"127151",title:"Dr.",name:"Joanna",middleName:null,surname:"Jedrzejczak",fullName:"Joanna Jedrzejczak",slug:"joanna-jedrzejczak"}]},{id:"30019",title:"Psychogenic Pseudoepileptic Seizures – From Ancient Time to the Present",slug:"psychogenic-pseudoepileptic-seizures-from-ancient-history-to-the-present",signatures:"Joanna Jędrzejczak and Krzysztof Owczarek",authors:[{id:"103725",title:"Dr",name:"Krzysztof",middleName:null,surname:"Owczarek",fullName:"Krzysztof Owczarek",slug:"krzysztof-owczarek"},{id:"127151",title:"Dr.",name:"Joanna",middleName:null,surname:"Jedrzejczak",fullName:"Joanna Jedrzejczak",slug:"joanna-jedrzejczak"}]},{id:"30021",title:"Children with Cerebral Palsy and Epilepsy",slug:"children-with-cerebral-palsy-and-epilepsy",signatures:"Emira Švraka",authors:[{id:"29419",title:"Associate Prof.",name:"Emira",middleName:null,surname:"Švraka",fullName:"Emira Švraka",slug:"emira-svraka"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"68162",title:"A Review of the Role of Natural Clay Minerals as Effective Adsorbents and an Alternative Source of Minerals",doi:"10.5772/intechopen.87260",slug:"a-review-of-the-role-of-natural-clay-minerals-as-effective-adsorbents-and-an-alternative-source-of-m",body:'\n
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1. Introduction
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Natural clay minerals (NCMs) have gained considerable attention due to their unique properties and their use in huge range of industrial and environmental applications [1, 2]. NCMs are unique in the sense that these minerals are studied by, and used in, many disciplines for essential and applied research [3, 4]. These minerals are nontoxic to ecosystem and play important role in the development of human civilization. They have been utilized in agricultural applications, engineering and construction applications, environmental remediation, geology, pharmaceuticals, food processing and many other industrial applications [2, 5]. The economic benefits look evident due to the fact that NCMs are widespread, and inexpensive compared with other raw materials [6]. For these reasons, NCMs research is being actively pursued by many scientists and in several countries, and the future of clay science seems exciting, and promising.
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1.1. Structure and composition of the NCMs
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NCMs can arguably be considered as phyllosilicate class, containing layered structures of shared octahedral aluminum and tetrahedral silicon sheets, water molecules and hydrated cations that can move in and out of the interlayer spaces [7, 8]. Commonly, isomorphous substitution of one cation with another (of similar size but with lesser charge, such as Al3+ for Si4+ or Mg2+ for Al3+) within crystal structures leads to a charge imbalance in silicate NCMs, which accounts for the permanent negative charge on NCMs particles, hence the ability of clays to attract cations to the surface. Amphoteric▬OH groups at the surface/edge of clays (i.e., silanol and aluminol groups) could also contribute to surface charge (pH-dependent reversible charge).
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The physical and chemical properties of any particular NCMs are structure and composition dependent. A general review of the structure and composition of the various NCMs are essentially hydrous aluminum silicates that sometimes with variable amounts of iron, magnesium, alkali metals, alkaline earths, and other cations found on or near some planetary surfaces [9]. The atomic structure of NCMs consists of two basic units, an octahedral sheet and a tetrahedral sheet. The octahedral sheet is comprised of closely packed oxygens and hydroxyls in which aluminum, iron, and magnesium atoms are arranged in octahedral coordination (Figure 1a). The second structural unit is the silica tetrahedral layer in which the silicon atom is equidistant from four oxygens or possibly hydroxyls arranged in a tetrahedron with the silicon atom in the center (Figure 1b). NCMs are usually classified based on their structure and layer type [10]. The classification of Grim becomes the basis for outlining the nomenclature and the differences between the various NCMs [3]. Although, it is not possible to compress the discussion of structure and classification of NCMs in this chapter, a simple classification of NCMs is available in literatures, NCMs can be divided into four main groups: kaolinite group, illite group, smectite group, and vermiculite group.
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Figure 1.
Diagrammatic sketch of the octahedral (a) and the tetrahedral sheet (b).
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The structure and composition of the major industrial NCMs are different even though they are each comprised of octahedral and tetrahedral sheets as their basic building blocks. The arrangement and composition of the octahedral and tetrahedral sheets account for most of the differences in their physical and chemical properties. Therefore, for their applications an understanding of the structure, physical and chemical properties attributes of the individual clay minerals is important. The huge variety of physical and chemical properties of NCMs provides unlimited scope for future application, particularly in environment protection or as minerals resources. A general review of the structure and composition of the NCMs are given in this chapter. A more detailed discussions of the structures of the various NCMs were discussed in literature [5, 9, 10, 11, 12, 13].
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1.2. Properties and factors that affect the application ability of natural clay minerals
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The use of NCMs for specific applications depends on its type of structure (1.1 or 2.1 layer type) and on its chemical composition [14]. The identity of all the material present in NCMs should be determined in order to evaluate their properties. The most important characteristic of NCMs is the cation exchange capacity (CEC). CEC is to measure the capacity of NCMs to exchange cations from the solution [15], which depends on the volume of the total layer charge. Since the surface layer charge is the function of pH, thus, CEC also changes with pH and regularly CEC is measured at pH 7 [16, 17]. The popular metallic cations found in exchange positions in NCMs are Ca2+, Mg2+, Na+, and K+. The presence of charge in NCMs play important role for cation exchange and the swelling properties of the minerals. The hydrolysis of Si▬OH or Al▬OH bonds along the NCMs lattices supplies the surface charge. Depending on the silica structure and the solution pH, the net surface charge can be either positive or negative. The tetrahedral and octahedral sheets of NCMs usually have a charge. The charge in the NCMs occurs in two forms: structural and surface charge. The structural charge is permanent and present due to ion substitutions, which arises inside the interior of the layers. The surface charges, generally in NCMs depend on the pH value, with 2:1 layer, the surface charge creates on the basal surface of the tetrahedral sheets while the surface charge for layer type 1:1, derives from both of tetrahedral and octahedral sheets. Also, the edges of both 1:1 and 2:1 layer contribute to the surface charge [16]. Several books have explained the details of the structure and properties of NCMs such as Handbook of Clay Science, edited by Bergaya et al. [13].
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Furthermore, the presence of amount of exchangeable ions, non-NCMs, soluble salts, and quality of their texture are factors which can affect their properties and applications. The presence of cations in octahedral sheet, and isomorphic substitutions in the octahedral and tetrahedral sheets result in net charge deficits. Varying according to the sheet unit, and ultimately, in different mineral phases giving rise to varied technical behavior. The textural differences between structurally and chemically identical NCMs also affect their adsorptive properties [15, 17, 18].
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The type and amount of non-clay minerals are present with NCMs affect their properties and applications. Non-clay minerals commonly associated with the NCMs include quartz, feldspar, mica, calcite, dolomite, opal C-T, and minor amounts of heavy and trace minerals such as ilmenite, rutile, brookite, anatase, leucoxene, sphene, tourmaline, zircon, kyanite, goethite, hematite, magnetite, garnet, augite, florencite, apatite, andalusite, and barite. Subsequently, when developing applications for NCMs, it is necessary to take these factors into consideration. It is important to know the specific properties of NCMs one is using in order to ensure that it is appropriate for one’s needs or to better understand their mechanism behavior during experimental process.
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1.3. Techniques of NCMs characterization
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There is increasing trend in the popularity of productive research in the field of NCMs. Characterization of NCMs is given significance as they are mainly used as cation exchangers, sorbents/hosts, and catalysts. Usually, the characterization of a number of techniques has to be done in order to get comprehensive details of the NCMs.
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Moreover, the multitude of techniques also accelerates the process of development of NCMs, particularly as catalysts, as different aspects are discovered. Extensive research in the field of instrumentation has resulted in advanced techniques of analysis that have helped in characterization of molecular sieves in general and NCMs in particular. In common, the characterization of NCMs should provide information about; (i) chemical composition; (ii) structure and morphology; (iii) ability to adsorb and retain molecules, and (iv) ability to chemically convert these molecules.
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The techniques for NCMs characterization, include X-ray diffraction (XRD), transmission electron microscopy (TEM), electron-beam-based microscopy, scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDX), Fourier transform infrared (FTIR) spectroscopy, X-ray fluorescence (XRF), magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy (MASNMR), X-ray photoelectron spectroscopy (XPS) analyses, N2 adsorption-desorption isotherms and zeta potential analysis to obtain the mineralogical and physicochemical parameters.
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XRD is generally used to identify the presence and quantitative determination of crystalline NCMs. SEM is useful for morphological analysis and chemical analyses at specific locations. The chemical compositions are determined using XRF. IR and NMR provide insight into acid sites and framework structure. It is not possible to compress the discussion of such techniques and research done on their scope and development. Literatures provide useful insight into various characterization techniques for NCMs [5, 13, 15].
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Here, we compile research data from various publications related to the use of different NCMs-based adsorbents and the leaching technology generations for REE extraction, notably thorough literature of our current researches. In the first part of this chapter, general structure, properties and the factors that affect the application ability of NCMs are discussed. The techniques of NCMs characterization are also summarized. The main goal of this review is to explain why an understanding of the structure and surface properties of the individual NCMs are so important. This chapter provides an elaborate information about the different NCMs as effective adsorbents in environment protection and their importance for the extraction of rare earth elements in ion adsorption clays. It has also adequately summarized the role of factors that affect adsorption (i.e., NH4+ and REE) and extraction behavior of REE onto NCMs.
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2. Adsorption behavior of contaminants and recovery of rare earth elements adsorbed on natural clay minerals
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In environment protection, NCMs have been used in the elimination and storage of hazardous chemicals [14, 19, 20]. NCMs have the catalytic capability to neutralize certain organic hazardous chemicals [15, 20, 21]. The ability of NCMs to contain hazardous substances depends on their cation exchange capacity (CEC) while the process of retaining toxic materials mainly occurs by the ion exchange and/or adsorption. Due to their high cation exchange capacity, NCMs are very effective for the adsorption of cations from the solution. Although the NCMs are electronegatively charged [22], these minerals still can adsorb organic and non-ionic substances in significant amounts. The adsorption characteristics are dependent upon the chemical/structural makeup of the adsorbent, the Si/Al ratio, cation type; number and location are particularly influential in adsorption. The adsorption capacity of NCMs can be improved by modification with inorganic salts (NaCl, CaCl2, BaCl2, NH4Cl, AlCl, FeCl3), cationic surfactants, acid, base and organic [23, 24]. Consequently, the NCMs become hydrophobic and organophilic, which led to the enhancement of the adsorption of non-ionic and organic compounds [25, 26]. Notably, in our brief studies of NH4+ and REE adsorption, we used non-modified NCMs, to better understand the natural system reactivity of NCMs, and also the modification of natural minerals at a larger scale may increase the processing cost; thus, reliable water treatment by using non-modified clay minerals is highly desirable. Therefore, utilization of NCMs would solve disposal problem, and also access to inexpensive materials in the wastewater treatment. Moreover, due to low cost of NCMs, there is no need to regenerate them; which provide more advantages in using NCMs as an adsorbent materials.
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2.1. A brief review of adsorption of NH4+
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Nitrogen compounds in aqueous environments are commonly found in the form of ammonium ions (NH4+). Important sources of NH4+ include effluent from the application in agricultural practices and industrial processes resulting in algal bloom in lakes and rivers [27, 28]. NH4+ concentration, in certain surface waters serving as a source of potable water, is much higher than the permissible level, due to large quantities of industrial and municipal wastewater being discharged into existing water resources [29, 30, 31]. Also, the NH4+ concentration for most fish species must not exceed 1.5 mg [32, 33]. Therefore, complete removal of NH4+ is required due to its toxicity to the majority of aquatic lives.
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For these reasons, the prevention of nitrogen pollution with NH4+ removal from wastewater is of great importance [34, 35, 36]. Various methods including air stripping, biological methods and activated carbon have been used for NH4+ removal [37]. However, these techniques are not suitable for use in the removal of low contaminants concentrations, which cause damage both to the environment and life [31]. Additionally, high costs, poor regeneration and uncertainty of outcome are some of the frequently encountered limitations in the application of these methods [36, 38, 39]. Furthermore, contingency on temperature and climate conditions constitutes another disadvantage in this process.
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Compared with the above mentioned methods, high safety, low cost [34, 40, 41] and relative simplicity of application and operation are some of the attributes that are attracting an increasing focus on the use of adsorption method for environment applications [33, 42, 43]. Adsorption process is a suitable technique for pollutants removal from wastewater, because of the significant advantages like low-cost, profitability, availability, and effectiveness than other methods. This method is easy to operate and equally effective in the removal of toxic contaminants, even at low concentrations [44].
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2.1.1. Investigations of NH4+ adsorption properties of six natural clay minerals
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This research presented six types of NCMs-based adsorbents namely kaolinite, halloysite, montmorillonite, vermiculite, palygorskite, and sepiolite were examined and compared in the same study [44]. The study illustrated that among all the NCMs studied, vermiculite and montmorillonite have the highest ammonium adsorption capacities. The study revealed that the cation exchange is the main mechanism for the NH4+ adsorption. Negatively charged surface, specific surface area, water absorption process and surface morphology of NCMs might also contribute to the high adsorption capacities. Adsorption kinetics showed that the adsorption behavior followed the pseudo-second-order kinetic model whereas the isotherms fitted the Langmuir model. The insights obtained in this study are useful for applications of NCMs in environmental remediation. The results illustrated that the structure and surface properties of NCMs are the key factors that affect the adsorption capacities for NH4+. The study concluded that the NCMs have significant potential as economic, safe and effective adsorbent materials for the NH4+ adsorption from the aqueous solution at low concentrations.
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2.2. A brief review of adsorption/extraction of rare earth elements
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2.2.1. Adsorption of rare earth elements (REE)
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REE group consists of 17 elements and is divided into two categories namely the light rare earths (L-REE) and the heavy rare earths (H-REE). REE have been used widely in metallurgy, chemical engineering, electronics and electrooptics, medicine, biomedicine, for manufacturing of magnetostriction materials and lasers [45, 46, 47]. Its applications in advanced technologies are increasing [48]. In modern societies, the rare earth elements (REE) are considered because of their unique physical and chemical properties. REE will be of substantial attention for the foreseeable future, with demand likely to grow.
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Therefore, due to the increasing use of REE in industries, determination of REE has been of a recent increasing concern. Several analytical techniques were used to determine REE in samples such as inductively coupled plasma-mass spectrometry (ICP-MS) [49], neutron activation (INAA) [50]. Energy dispersive X-ray fluorescence (EDXRF) [51] and inductively coupled plasma optical emission spectroscopy (ICP-OES) [52]. Research should continue to play an important role in the search for rare earth ore deposits and their extraction, ensuring that as little damage is done to the environment as conceivable.
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Various techniques have been used for removal of REE ions from aqueous systems such as solid-phase extraction, solvent extraction, ion exchange, ion-selective electrodes [53, 54, 55, 56, 57, 58, 59] and adsorption [60, 61, 62]. Adsorption method is the best technique because of low cost, simplicity of design and operation. The ion-adsorption type rare earths ore, is mainly located in China and REE in these deposits were released by weathering of REE-rich granites and subsequently adsorbed by NCMs.
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Recently, there has been a significant interest in adsorption of rare earth elements with NCMs [1, 63, 64, 65]. Piasecki and Sverjensky [66] also had studied REE speciation/distribution on wide ranges of pH and ionic strength. They concluded that most of the surface-adsorbed lanthanides occur as simple “clay-REE” or as hydrolyzed “clay-O-REE2+” species.
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NCMs are electronegative, saturated with cations such as Na+, K+, Ca2+, and Mg2+ are capable of exchanging cations such as REE to the surface. Previous researches have shown that REE contained in NCMs are mainly present as physisorbed ions, which can be easily recovered by a simple ion-exchange procedure [66, 67]. It is evident that the adsorption of REE ions on NCMs would have great influence on the mineralization process and the leaching process of the ion-adsorption type rare earths ore.
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2.2.2. Extraction of REE from ion adsorption clays
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The ion-adsorption type rare earths ore are generally formed by weathering of REE rich host rocks (granitic or igneous) and transfer into an aqueous solution which percolates through the weathering body and are adsorbed onto NCMs [68, 69, 70, 71]. This provides evidence that NCMs have the ability of adsorbing lanthanide ions released/solubilized during weathering [72]. However, although, the NCMs deposits containing adsorbed lanthanides which are of substantially lower grade than other types of REE mineral resources, the economic benefits look remarkable, because NCMs are abundant in surface layers in nature, easier ionic exchange of REE, ease of mining and processing [66, 73]. It is thus evident that the adsorption of rare earth ions on NCMs would have great influence on the mineralization process and the leaching process of the ion-adsorption type rare earths ore.
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During the past 45 years, the leaching technology in REE extraction were investigated [64, 74, 75]. The extraction of REE has been a long tradition in China using the concept of ion-exchange leaching. In the ion adsorption clays 60–90% of the REE are adsorbed onto NCMs [71] and the adsorbed REE on NCMs could be easily recovered by leaching with monovalent salt solutions. Recently, the ion-adsorption rare earth ores have the focus of most research endeavors as an alternative source of REE, the results of leaching efficiencies has been reported [66, 71, 73, 75, 76]. Based on these findings, (NH4)2SO4 was identified as the best a lixiviant of REE from NCMs.
\n
\n
\n
2.2.3. Investigations of adsorption/extraction behavior for REE onto natural clay minerals
\n
Four natural clay minerals namely kaolinite, montmorillonite, muscovite and illite were systematically investigated and compared for their adsorption/extraction behavior for REE [77]. The study reported that the montmorillonite exhibits highest adsorption and regeneration efficiencies for REE while kaolinite has highest extractions efficiencies for both REE light and heavy in the order of kaolinite > illite > montmorillonite > muscovite. Also study found that the lack extractions of REE from muscovite than other NCMs are believed to presence of iron oxide and biotite mineral (produce iron oxide as a result of its alteration) associated with muscovite. The leaching process of the REE is a kind of the reversibility of the ion-exchange process, it was evident that the cation exchange and negatively charged surfaces are the mechanism for REE adsorption. It was concluded that NH4+ is lacking as a lixiviant from NCMs since NCMs are associated with iron oxide, particularly, either with NCMs containing iron (i.e., biotite) or minerals which always associate with biotite such as muscovite. The important role of the pH in extraction of REE from NCMs was evidenced, when REE-NCMs come into contact with the NH4+ solution, the pH is rapidly increased from the initial pH solution for both montmorillonite and muscovite, leading to the decrease of the availability of ion-exchangeable REE with NH4+ ions. That is one of the factors that influence the reduction in the REE extraction from montmorillonite and muscovite when compared with those of kaolinite and illite. The results illustrated that the structure and surface properties of NCMs are also the key factors that affect the rare earth leaching, consequently identifying the types of NCMs and associated impurities in clay materials is important for getting the best leaching system [77].
\n
\n
\n
\n
\n
3. Conclusion
\n
NCMs have gained a significant interest among the scientific community, because of their abundance, low cost and their unique properties. In this regard, a systematic comparison study under identical experimental conditions could help to better understand the influence of structure and properties of NCMs on their adsorptive/extraction behaviors towards contaminants and elements in leaching process. Adsorption is a very promising and efficient technology for the removal of hazardous contaminants from water source, thus NCMs have been successfully used as an adsorbent materials and alternative source of minerals. Batch adsorption experiments have demonstrated that the contact time, initial pollutants concentration, adsorbent dosage and solution pH have significant effects on contaminants adsorption/desorption. Among all the NCMs studied, montmorillonite and vermiculite exhibit the highest adsorption efficiencies towards NH4+ and REE. The presence of iron oxide with NCMs found to help enhance REE adsorption (REE-Fe-oxides), meanwhile it also influences the extraction of REE because REE-Fe-oxides cannot be easily recovered by monovalent salt solutions using the concept of ion exchange i.e., NH4+. The structure and surface properties of NCMs are the key factors that affect the adsorption capacities for contaminants and extraction of minerals (i.e., REE). The review suggests that NCMs can be considered as ideal adsorbents and alternative source of minerals owing to their low cost, abundant, high safety, and good adsorption efficiencies. Identifying the types of NCMs and associated impurities in clay materials is important either for getting the best adsorption or the best leaching system. Thus, when developing applications for NCMs, it is essentially to take these factors into consideration. However, further study is necessary to establish the process parameters to generate better quality of products. Also, modification and thermal treatment of natural clay minerals could provide potential future applications in water treatment.
\n
\n
Acknowledgments
\n
This work was supported by the scientific research start up fund (099/CGZ07273), School of Environmental and Chemical Engineering, Foshan University, Foshan, Guangdong 528000, China.
\n
\n',keywords:"natural clay minerals, adsorption mechanism, ammonium, rare earth elements, REE extraction",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/68162.pdf",chapterXML:"https://mts.intechopen.com/source/xml/68162.xml",downloadPdfUrl:"/chapter/pdf-download/68162",previewPdfUrl:"/chapter/pdf-preview/68162",totalDownloads:523,totalViews:0,totalCrossrefCites:0,dateSubmitted:"March 14th 2018",dateReviewed:"June 5th 2019",datePrePublished:"July 18th 2019",datePublished:"November 13th 2019",dateFinished:null,readingETA:"0",abstract:"The minerals with unique properties such as natural clay minerals (NCMs) have promising approach in environmental and industrial sphere. In fact, under some specific conditions the NCMs could be used either as effective adsorbent material or alternative source of minerals. This chapter presents an outline of a general review of factors that affect the application ability of NCMs and a descriptive analysis of NH4+ and REE adsorption behavior and extraction of rare earth elements (REE) by an ion-exchange with NH4+ ions onto NCMs. Clays and NCMs both effectively remove various contaminants from aqueous solution and serve as alternative sources of minerals, as extensively discussed in this chapter. This review compiles thorough literature of current research and highlights the key findings of adsorption (NH4+ and REE) that use different NCMs as adsorbents or alternative sources of minerals (i.e., REE). The review confirmed that NCMs excellently remove different cations pollutants and have significant potential as alternative source of REE. However, modification and further development of NCMs applications for getting the best adsorption and the best extraction of REE onto NCMs, which would enhance pollution control and leaching system is still needed.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/68162",risUrl:"/chapter/ris/68162",signatures:"Aref Alshameri, Xinghu Wei, Hailong Wang, Yang Fuguo, Xin Chen, Hongping He, Chunjie Yan and Feng Xu",book:{id:"7315",title:"Minerals",subtitle:null,fullTitle:"Minerals",slug:"minerals",publishedDate:"November 13th 2019",bookSignature:"Khalid S. Essa",coverURL:"https://cdn.intechopen.com/books/images_new/7315.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"102766",title:"Prof.",name:"Khalid S.",middleName:null,surname:"Essa",slug:"khalid-s.-essa",fullName:"Khalid S. Essa"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"172947",title:"Prof.",name:"Xin",middleName:null,surname:"Chen",fullName:"Xin Chen",slug:"xin-chen",email:"451807924@qq.com",position:null,institution:null},{id:"250327",title:"Dr.",name:"Aref",middleName:null,surname:"Alshameri",fullName:"Aref Alshameri",slug:"aref-alshameri",email:"arefalshameri@gig.ac.cn",position:null,institution:null},{id:"306625",title:"Dr.",name:"Aref",middleName:null,surname:"Alshameri",fullName:"Aref Alshameri",slug:"aref-alshameri",email:"aref_alshmiri@yahoo.com",position:null,institution:{name:"Foshan University",institutionURL:null,country:{name:"China"}}},{id:"306656",title:"Prof.",name:"Fuguo",middleName:null,surname:"Yang",fullName:"Fuguo Yang",slug:"fuguo-yang",email:"fgyang2002@126.com",position:null,institution:{name:"Foshan University",institutionURL:null,country:{name:"China"}}},{id:"306658",title:"Dr.",name:"Wei",middleName:null,surname:"Xinghu",fullName:"Wei Xinghu",slug:"wei-xinghu",email:"weixinghu1964@163.com",position:null,institution:{name:"Foshan University",institutionURL:null,country:{name:"China"}}},{id:"306660",title:"Prof.",name:"Wang",middleName:null,surname:"Hailong",fullName:"Wang Hailong",slug:"wang-hailong",email:"hailongwang@fosu.edu.cn",position:null,institution:{name:"Foshan University",institutionURL:null,country:{name:"China"}}},{id:"306664",title:"Prof.",name:"Yan",middleName:null,surname:"Chunjie",fullName:"Yan Chunjie",slug:"yan-chunjie",email:"chjyan2005@126.com",position:null,institution:{name:"China University of Geosciences",institutionURL:null,country:{name:"China"}}},{id:"306665",title:"Dr.",name:"Xu",middleName:null,surname:"Feng",fullName:"Xu Feng",slug:"xu-feng",email:"fengxu@fosu.edu.cn",position:null,institution:{name:"Foshan University",institutionURL:null,country:{name:"China"}}},{id:"306671",title:"Prof.",name:"He",middleName:null,surname:"Hongping",fullName:"He Hongping",slug:"he-hongping",email:"hehp@gig.ac.cn",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Structure and composition of the NCMs",level:"2"},{id:"sec_2_2",title:"1.2. Properties and factors that affect the application ability of natural clay minerals",level:"2"},{id:"sec_3_2",title:"1.3. Techniques of NCMs characterization",level:"2"},{id:"sec_5",title:"2. Adsorption behavior of contaminants and recovery of rare earth elements adsorbed on natural clay minerals",level:"1"},{id:"sec_5_2",title:"2.1. A brief review of adsorption of NH4+",level:"2"},{id:"sec_5_3",title:"2.1.1. Investigations of NH4+ adsorption properties of six natural clay minerals",level:"3"},{id:"sec_7_2",title:"2.2. A brief review of adsorption/extraction of rare earth elements",level:"2"},{id:"sec_7_3",title:"2.2.1. Adsorption of rare earth elements (REE)",level:"3"},{id:"sec_8_3",title:"2.2.2. Extraction of REE from ion adsorption clays",level:"3"},{id:"sec_9_3",title:"2.2.3. Investigations of adsorption/extraction behavior for REE onto natural clay minerals",level:"3"},{id:"sec_12",title:"3. Conclusion",level:"1"},{id:"sec_13",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Anastopoulos I, Bhatnagar A, Lima E. Adsorption of rare earth metals: A review of recent literature. Journal of Molecular Liquids. 2016;221:954-962. DOI: 10.1016/j.molliq.2016.06.076'},{id:"B2",body:'Reyes C, Fiallo L. Application of illite-and kaolinite-rich clays in the synthesis of zeolites for wastewater treatment. In: Imran Ahmad Dar (ed.), Earth and Environmental Sciences. Rijeka, Croatia: Intech Open; 2011. p. 234-246. DOI: 10.5772/25895'},{id:"B3",body:'Grim R. Applied Clay Mineralogy. New York, USA: McGraw-Hill Book Company; 1962. 6d. DOI: 10.1080/11035896209447314'},{id:"B4",body:'Su L, Zeng X, He H, Tao Q, Komarneni S. Preparation of functionalized kaolinite/epoxy resin nanocomposites with enhanced thermal properties. 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School of Environmental and Chemical Engineering, Foshan University, China
Guangdong Provincial Key Laboratory of Mineral Physics and Materials and Key Laboratory of Mineralogy and Metallogeny, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, China
Geological Survey and Mineral Resources Board, Ministry of Oil and Minerals, Yemen
Engineering Research Center of Nano-Geomaterial of Education Ministry, China University of Geosciences, China
Guangdong Provincial Key Laboratory of Mineral Physics and Materials and Key Laboratory of Mineralogy and Metallogeny, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, China
School of Environmental and Chemical Engineering, Foshan University, China
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