The basic principle of DNA isolation in the DNA extraction method performed.
\r\n\tThis book plans to focus on elaborating recent advances in the field of electrodeposition with fruitful evidence. The feasibility of electrodeposition routes to fabricate different metals and their derivatives for various uses are to be explained in detail.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"207613e28b728f2b6cd3007e746cdefa",bookSignature:"Prof. Dhanasekaran Vikraman and Dr. K. Karuppasamy",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8532.jpg",keywords:"Topic 1:Thin films\r\nKeywords: Electrodeposition, Anodic deposition, cathodic deposition, Reaction kinetics\r\nTopic 2: Metals and metal oxides \r\nKeywords: II-VI elements, copper oxide, Ferrous oxide, Silver oxide\r\nTopic 3: Chalcogens \r\nKeywords: metal dichalcogens\r\nTopic 4: Alloys\r\nKeywords: Metal alloys, Solid solution, Gold - copper, Iron - Cobalt",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"August 14th 2019",dateEndSecondStepPublish:"September 4th 2019",dateEndThirdStepPublish:"November 3rd 2019",dateEndFourthStepPublish:"January 22nd 2020",dateEndFifthStepPublish:"March 22nd 2020",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"199404",title:"Prof.",name:"Dhanasekaran",middleName:null,surname:"Vikraman",slug:"dhanasekaran-vikraman",fullName:"Dhanasekaran Vikraman",profilePictureURL:"https://mts.intechopen.com/storage/users/199404/images/system/199404.jpeg",biography:"Dr. Dhanasekaran Vikraman is an Assistant Professor in Division of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul, Korea. He received his Bachelor's degree at Mannai Rajagopalaswamy Govt. Arts College, Mannargudi, affiliated to Bharathidasan University, Tiruchirappalli, India. After that, he completed his Master and Ph.D degrees at Department of Physics, Alagappa University, India. Later, he received visiting scientist position at KIST, Korea; Marie-Curie Experienced Researcher fellowship at Department of Physics, Aristotle University of Thessaloniki, Greece; and Post-Doc positions at Sejong University and Ajou University, Korea. \r\nHe has authored more than 100 international journal articles and 1 book chapter. In addition, he served as an Editor with IntechOpen for a book entitled “Design, Simulation and Construction of Field Effect Transistors”. His research interests are mainly focused on low-cost synthesis of inorganic materials and 2D-materials for electronics and energy applications.",institutionString:"Dongguk University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Dongguk University",institutionURL:null,country:{name:"Korea, South"}}}],coeditorOne:{id:"300938",title:"Dr.",name:"K.",middleName:null,surname:"Karuppasamy",slug:"k.-karuppasamy",fullName:"K. Karuppasamy",profilePictureURL:"https://mts.intechopen.com/storage/users/300938/images/system/300938.jpeg",biography:"Dr. K. Karuppasamy is currently working as an Assistant professor at Division of Electronics & Electrical Engineering, Dongguk University-Seoul, South Korea. He received his Ph.D. in the field of nanocomposite electrolytes for lithium-ion batteries in Anna University, Chennai, India in 2014. Later, he completed his Post-Doc positions at Department of Metallurgical Engineering and Materials Science, Indian Institute of Technology Bombay, India, and Department of Chemical Engineering, Sogang University, Seoul, South Korea. His research interests mainly focus on synthesis and characterization of nanostructured materials for energy storage and conversion device applications. 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From chapter submission and review, to approval and revision, copyediting 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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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"60406",title:"Molecular Based Method Using PCR Technology on Porcine Derivative Detection for Halal Authentication",doi:"10.5772/intechopen.76071",slug:"molecular-based-method-using-pcr-technology-on-porcine-derivative-detection-for-halal-authentication",body:'Today most of the Moslem countries are still growing in terms of life style, traveling, food and so on. Food is the primary need for humankind and cannot be separated from life; consequently, everywhere human beings live, including Moslems, they need food for living. In addition, awareness among Muslims on the need and necessity to consume only halal food is annually increasing, so the global market of halal food will be predominant in the future. It is understood that the production of halal food is not only beneficial to Muslims but also to food producers, since it will increase market space for Muslims especially and non-Muslims also who are interested in consuming halal food for health reasons. Human food production starts from the ingredients chosen, preparing the equipment, processing methods, packaging and labeling.
Human mobility which is increasing requires the availability of food according to the needs of each individual. Food security extends not only to safety and health issues but also to religious considerations. In the global realm, the need of tools to ensure that food is consumed safely and is a guarantee that it is free from non-halal materials requires a technology and non-halal detection application. This chapter is discussed in relation to some reliable methods of DNA-based analysis that is needed in justifying the presence of non-halal materials for Muslim consumers, in particular, the ingredients derived from pigs which are materials prohibited in Islam for consumption.
Identification of the presence of non-halal compounds becomes a very important problem in human food products, especially those containing prohibited substances such as ingredients derived from pigs. In the concept of food safety assurance, raw material data used is very important to be included. The world with a Muslim population of about 1.3 billion makes food security globally not only toward healthy and safe food products but also must show the halal aspect of the food product [1].
Authentication is the most important criteria and is always an issue in the field of food. The one that encourages the importance of authentication is the raw material, because it determines whether the food is deserved to be consumed. In Islam, “Halal” means that it is allowed or permitted and haram refers to anything that is not allowed and includes sin when violated. If used in relation with food and drink, halal means allowed to be eaten or drunk. It is mandatory for Muslims to eat halal food and consume halal products. For a Muslim, food should not only be healthy and of good quality, but more importantly, the food must be halal. Nowadays, many kinds of animal products have been commonly consumed and spread across countries without limitations. The relatively new products such as nuggets, sausage, burger, hot dog, meat ball and so on are widely accepted by consumers regardless of gender, ethnics and age. Further processing of animal products has given more economic advantage for the producers and convenience for the consumers.
In recent years, there has been an increasing trend in some countries for mixing prohibited substances, especially pigs in food products for the purpose of falsification to obtain economic benefits [2]. Identification becomes very important so that the status of halal food becomes clear. Two approaches that can be made to determine whether pig substances are present are analysis of the pig meat elements or pig material in food products.
Various methods of detection of non-halal materials have developed rapidly. The method that has significantly developed is FTIR spectrophotometry [3] differential scanning calorimetry [4], liquid chromatography [5], immunoelectrophoresis [6], polymerase chain reaction (PCR)-RFLP DNA based methods [7] and real-time PCR [8].
Some of these methods are too laborious and time-consuming, consequently, an analytical technique offering rapid and reliable methods must be used. One of the promising methods suitable for routine analysis is polymerase chain reaction (PCR) [9]. The DNA-based analysis method has several advantages: DNA can be found in all cell types in an individual with identical genetic information. DNA is a stable molecule in the extraction process of several different types of samples.
Deoxyribonucleic acid (DNA) is a nucleic acid that contains genetic material and serves to regulate the biological development of all cellular life forms [10]. DNA contains genetic information stored in a nucleotide sequence and is used to synthesize all cell protein molecules and organisms. Another function is to provide information that is passed on to the cells or offspring of a child. Both of these functions require DNA molecules that serve as templates or models [11]. DNA has a double structure with components of pentose sugars (deoxyribose), phosphate groups and base pairs. DNA base pairs consist of purine and pyrimidine bases. The purine base consists of adenine (A) and guanine (G). The pyrimidine base is cytosine (C) and thymine (T) [12]. DNA is very important and widely used in analysis. DNA isolation is the key to successful identification of livestock derived from raw materials; therefore, the different methods of DNA isolation in each food stuff must be adapted to the conditions of the food type and food used in the diet.
Identification of species based on DNA technology depends on the success of DNA isolation. The success of DNA isolation is the basis for continuing with the next test stage. Therefore, the isolation method should be known by any researcher who wishes to detect the species or foodstuffs. Work experience in the DNA isolation laboratory is a basic skill that needs to be known in order to isolate the various food matrixes. Some of the important factors that influence the success of DNA isolation are:
type of food
food matrix
cooking time
cooking temperature
DNA isolation has several stages, that is, (1) isolation of cells; (2) lysis of walls and cell membranes; (3) extraction in solution; (4) purification; and (5) precipitation. There are two principles in performing DNA isolation, that is, centrifugation and precipitation. The main principle of centrifugation is to separate the substance based on molecular weight by providing a centrifugal force so that the heavier substances will be at the bottom, while the lighter substances will be located at the top. The centrifugation technique is carried out in a machine called centrifugation machine with varying speeds, for example, 2500 rpm (rotation per minute) or 3000 rpm [10].
Chemically, the destruction of cells is performed by utilizing chemical compounds such as ethylenediamine tetra acetic (EDTA) and sodium dodecyl sulfate (SDS). EDTA functions to destruct cells by binding magnesium ions (this ion serves to maintain cell integration and activity of nuclease enzyme which damages the nucleic acids). SDS is a kind of detergent that serves to destruct cell membranes. The proteinase K enzyme can be used to destruct proteins. Impurities due to cell lysis are separated by centrifugation. Then, the nucleotide molecules (DNA and RNA), which have been separated, are cleared of the residual proteins using phenol. In this process, a small part of RNA can also be cleaned. The RNAase enzyme is used to clean the residual proteins and polysaccharides from the solution. Purification of DNA can be done by mixing the DNA solution with NaCl, which serves to concentrate, separate DNA from the solution and precipitate DNA when mixed with ethanol [13].
The measurement of DNA concentration was done in two ways, that is, by spectrophotometer and by ethidium bromide fluorescence technique (EtBr). If the sample is pure, without large amounts of contamination such as protein, agarose, phenol or other nuclei, then the use of spectrophotometer that calculates the amount of UV irradiation absorbed by the bases is the proper way. The fluorescence technique of EtBr is used when the sample is contaminated [14].
DNA of ingredients in the form of fresh ingredients can generally be more easily isolated because most of the tissues have not been damaged. DNA of animal-derived food with cell structures easy to lysis is more easily isolated compared to a mixture of plant matrix ingredients which have stronger cell structures. Cooking duration will affect the quality and quantity of DNA that can be isolated, longer cooking duration will degrade the DNA; consequently, a lot of DNA fragments into smaller sizes, and as a result, at the time of amplification, there will occur difficulty with big-size amplicon target compared to small amplicon. The cooking temperature also has effect, the higher cooking temperature so the DNA in the food tends to be fragmented as a result for the size of the DNA with high fragment length target is difficult to amplify at PCR and difficult when identify the origin species of ingredients.
The basic principle of total DNA isolation from the tissue is to break down and extract the tissue, so cell extracts composed of tissue cells, DNA and RNA cells are formed. Then, the cell extract was purified to produce a cell pellet containing total DNA [10].
DNA is usually isolated from animal tissue cells using methods that lyse cells but prevent DNA fragmentation. This step usually involves EDTA (ethylenediamine tetra acetic) which in the process will bind magnesium ions (the cofactors required by the DNase enzyme). Furthermore, the cell membrane is preferably solubilized with a detergent. If physical disruption is required, it should be done as minimum as possible. In this disruption process, the nuclease enzyme released from the cellular component can efficiently digest the nucleic acids, so the work of the nuclease enzyme must be inhibited. Cell disruption and most of the following steps should be performed at 4°C, using a glassware and an autoclave solution (the autoclave function is to destruct DNase activity in the apparatus or solution). After removing the nucleic acid from the cell, RNA can be removed by the addition of heat-treated RNase to inactivate the DNase of the contaminant (RNase is relatively stable to heat because of the presence of disulfide bonds which will cause the renaturation process when cooled).
Other major contaminants, that is, proteins, are eliminated with phenol solution or phenol-chloroform mixture (both will denature the proteins but do not denature nucleic acids). After the mixture is made into an emulsion, centrifugation is conducted. After centrifying, an organic part will be formed in the lower part and in the top aqueous layer, which is a layer composed of a denatured protein and inside it is contained DNA. The aqueous fluid is taken and deproteinized several times until no material is visible in the middle layer. Then, the DNA that does not contain protein is mixed with two parts of ethanol. DNA will be a precipitate, separate from the sample solution. After being centrifuged, the DNA pellets are then dissolved again [15].
Samples from plants are mostly found in food products both individually and food matrix such as sausage, meatballs and nuggets in which there are materials from animals and plants. The most commonly used method for plant DNA isolation is the Cetyl Trimethyl Ammonium Bromide (CTAB) method. CTAB is a common method used in plant DNA extraction because plant DNA contains polysaccharides and polyphenol compounds [16]. There are three major steps in the extraction of plant DNA, that is, the destruction of cell walls (lysis), separation of DNA from solid materials such as cellulose and proteins and DNA purification [17].
CTAB has the same function as SDS, which acts as a lipid solvent of the cell membrane. SDS is a kind of detergent that can emulsify lipids. After overnight incubation with ethanol absolute and ammonium nitrate, the DNA filaments are known and then centrifuged to obtain the DNA pellets. After the supernatant was removed, 70% of ethanol was added for next precipitation. Then, the pellet is dried and stored at −20°C [18].
Food products are a complex food mixture. Food products may contain PCR inhibitors such as polysaccharides, polyphenols and proteins [19]. In addition, food products have undergone several stages of processing, such as mechanical treatment, heating, chemical and enzymatic. As a result, DNA isolation from food products often has difficulties [20].
Some authors have compared methods of DNA extraction from food. Zimmerman et al. [21] compared nine different extraction methods of soybean; food samples showed that five of the methods had the extracted DNA damaged, while in four other methods (CTAB, Wizard, DNeasy and nucleon Phytopure), the amount of DNA produced was relatively low but had good quality. Previously, Olexová et al. [22] have found good DNA extraction results using CTAB on soybean, corn and wheat products (flour, biscuits and instant porridge). Each sample in the food matrix needs the specific DNA isolation methods, as described by researcher [20] and they tried to compare four methods of DNA extraction (NucleoSpin kit, commercial and GeneSpin, CTAB, and Wizard method) applied to soybean processed products; CTAB method extraction showed the best results. Further, Sambrook [23] used CTAB modification by adding salt (NaCl) and twice as much CTAB volume in extracting food product samples for the identification of pork content.
Today, the DNA isolation commonly uses DNA isolation kit as it is faster and is a simple method than the manual; consequently, the price is more expensive. The commercial kit has been available in varying amounts and benefits. However, the use of kits in DNA isolation is not suitable for student learning in college; therefore, the use of manual methods in student research is highly recommended. The use of kits in DNA isolation is usually simple and follows the procedures of the company, while manual DNA isolation requires the preparation of chemicals independently. The following table illustrates some basic methods and basic principles of DNA isolation (Table 1).
Method | The principle of DNA separation |
---|---|
TNES [24] |
|
[14] modified |
|
CTAB |
|
The basic principle of DNA isolation in the DNA extraction method performed.
The results of DNA isolation research using the modified [14] method for sample of meatball and sausage as illustrated in Figure 1 is as follows.
Result of DNA isolation of meatball and sausage of various species on 1% agarose gel: (1) 100% cow meatballs, (2) 100% chicken meatballs, (3) 100% pork meatballs, (M) 100 bp marker, (4) 100% cow sausage, (5) 100% chicken sausage, (6) 100% pork sausage.
Food products are complex food mixtures which may contain inhibitors such as polysaccharides, polyphenols and proteins [19]. In addition, food products have undergone several stages of processing, such as mechanical treatment, heating, chemical and enzymatic treatments. As a result, DNA isolation from food products often has difficulties [20]. The complicities of sample affected the DNA quality [25] and the presence of additives on foods also affected the results of DNA isolation. Therefore, optimization and modification of the basic method to obtain DNA with good quality and quantity is required.
As this study applied the Sambrook method [14] without overnight incubation, the results showed that the quality of the DNA is not good enough and is marked by the appearance of DNA smear and some samples were not isolated (data not shown); therefore, the modification to prolong the lysis time and cell digestion by adding the incubation time to ±15 h (overnight) at a temperature of 55°C was made. The modification by adding the incubation time was intended so that the non-DNA molecules can be digested perfectly, thus minimizing the contaminants in the resulting DNA, since the sample was a processed meat consisting of a mixture of complex foods. The sample used in this study was a processed food product consisting of a mixture of meat (animal tissue) and non-meat (flour and spices) products that were considered as an inhibitor in the activity of DNA isolation.
The K proteinase was capable of digesting the cell completely after incubation of at least 10 h [23]. Meanwhile, previous research [26] founded that the duration of cell lysis depends on the shape of the extracted product. The more diverse the mixture and texture of the product, longer the time required. The optimization of ASL (Qiagien)-based extraction and purification of DNA by applying overnight to the cell lysis stage had been successfully performed for the identification of pork in processed meat products in Saudi Arabia [27]. The same method [28] was also used for overnight incubation at the lysis stage and digestion for the identification of pig DNA in food products. Chapela et al. [29] also used overnight incubation at the cell lysis stage in DNA extraction from canned tuna to identify species of animal origin.
DNA extraction of whole tissue is easier to do than processed meat such as meatballs, sausages and abon, where DNA has been degraded. The DNA obtained for analysis must be pure and intact to obtain good analysis.
The contaminants that are often present in the process of DNA extraction and purification are proteins [30]. DNA measurements were performed by comparing absorbance ratios at wavelengths of 260 and 280 nm (OD 260: OD 280) [15].
The quality and purity of DNA is influenced by various factors including the isolation method and the type of food samples being prepared. The purity of DNA isolates from meatball samples with various methods of DNA isolation is described in Table 2.
Repetition | Methods | ||
---|---|---|---|
Wasko [24] | Sambrook [14] | CTAB | |
1 | 1.64 | 1.91 | 1.70 |
2 | 1.65 | 1.91 | 1.70 |
3 | 1.63 | 1.91 | 1.70 |
Mean | 1.64 ± 0.01 | 1.91 ± 0.00 | 1.70 ± 0.00 |
Purity comparison of DNA isolation result of meatball sample with various methods [59].
Good DNA extraction methods not only provided good DNA results but also high DNA purity [30]. In the study, DNA purity measurements obtained from several DNA extraction methods had been performed. From Table 2, it was known that the purity of DNA obtained from the modified Sambrook method gave best results on meatball samples, (1.91 ± 0.00; 1.92 ± 0.00; and 1.87 ± 0.00). This showed that the method used could produce DNA with good purity. The value of DNA purity ranges from 1.8 to 2.0. The value of purity would be lower if there was contamination of protein or phenol [15]. Method of [23] obtained DNA purity value of 1.64 ± 0.01 (meatballs), while DNA purity value of the CTAB method was 1.7 ± 0.00 (meatballs). This value may indicate the presence of protein contamination in isolated DNA. Furthermore, in the practice of food, DNA isolation with a varying food matrix requires choice of method, method modification and development of the most suitable method according to food matrix condition whose DNA will be isolated.
The wide variety of food products available on the market in the world seems favorable but leads to several fears for the Muslim community because the consumption of pork in food products is prohibited; therefore, some analytical methods offering fast and reliable results are continuously developed by some researchers. PCR-based methods have been applied through the PCR-RFLP method for the authentication of animal products especially meatballs in the market [9].
Polymerase chain reaction (PCR) is one of the most widely studied and widely used techniques of nucleic acid amplification in vitro. PCR is used to multiply the number of DNA molecules on a particular target by synthesizing new DNA molecules that complement the target DNA molecules through the aid of enzymes and oligonucleotides as primers in a thermocycle. The target length of DNA ranges from tenths to thousands of nucleotides whose positions are flanked by a pair of primers. The primer that is located before the target is called the forward primer and which is located after the target is called the reverse primer. The enzyme used as a novel printer of DNA molecules is known as the polymerase enzyme [31]. The length of the DNA gene is 1.140 bp and has some stable sequences used for universal primers and several sequences of variables normally used for animal identification by the PCR-RFLP method [32].
A pair of primers was employed in PCR reaction (9), the PCR primers used were cytochrome b gen as follows: (5’-CCA TCC AAC ATC TCA GCA TGA TGA AA-3′) and CYTb2 (5’-GCC CCT CAG AAT GAT ATT TGT CCT CA-3′), as reported by Kocher et al. [33]. The PCR-RFLP was applied using mitochondrial cyt b gene in a final volume of 25 μl containing 250 ng of extracted DNA in order for the porcine identification with mega mix royal PCR buffer. Amplification was performed in PCR system 2400 (Perkin Elmer), programmed to perform the pre-denaturation step of 94°C for 2 min, followed by 35 cycles which is carried out with following steps: denaturation at 95°C for 36 s, annealing at 51°C for 73 s, and extension at 72°C for 84 s. Final extension at 72°C was conducted for 3 min for complete synthesis of elongated DNA molecules. The DNA amplicon then cleaved using BseDI restriction enzyme and results could able to differentiate porcine among other meat [9].
PCR has the potential sensitivity and specificity required to achieve detection of a target sequence from template DNA. Gene of cytochrome b was used for the amplification of PCR and resulted in DNA fragmentation of approximately 360 bp for bovine, chicken and porcine. These small amplicons are ideal for use with processed foods where DNA commonly was degraded. This result indicated that pig, beef and chicken DNA in processed meat was successfully amplified in PCR reaction (Figure 2). The result of PCR amplification was similar to that [35] which reported the presence of the 360 bp fragment. This result also indicated that the frying of meat products at 100°C for 15 min did not result in the degradation of DNA into small size (<200 bp). They studied the feasibility of using mitochondrial cyt b gene to detect porcine material in commercial food products from various markets and evaluated them for the presence of porcine DNA. Visualization through electrophoresis of PCR products clearly detected porcine DNA, while no amplification occurred in others meat sources such as cattle, chicken, sheep and horse [36].
Amplification of mitochondrial cytochrome b DNA gene fragments 359 bp long in samples from meatballs products separated by 2% high-resolution agarose gel electrophoresis, M: Marker 100 bp DNA ladder (Invitrogen), A-D: PCR products of cytochrome b gene from 20 of commercial meatball samples from various regent in Indonesia b: Amplicon of beef DNA, and p: Amplicon product of raw pork DNA on [34]. Source: Aust-Asian J. Anim. Sci Vol. 27 No. 10.
The result of the amplicon cleavage (Figure 3) showed that the enzyme of BseDI could differentiate pork meat among chicken, bovine or goat.
Restriction fragment length polymorphism using BseDI restriction enzymes. M: Marker 100 bp DNA ladder, lane 1–20: DNA fragment of different meatball samples from 20 commercial meatballs b: DNA fragment raw beef cytochrome b gene cleaved into different pattern, and p: DNA fragment of PCR product of raw pork cytochrome b gene cleaved into 228 and 121 bp [34]. Source: Aust-Asian J. Anim. Sci Vol. 27 no. 10.
PCR product was digested using the BseDI restriction enzyme at 2 U/μl for 3-h incubation time. The result of analysis from various levels of pork in beef sausage and chicken nugget indicated that mixture of pork could be digested by the BseDI restriction enzyme and was detected until level 1%. BseDI cleavage bands visualized in the gel were enough and suitable for the discrimination of pork in processed food. BseDI endonuclease cleaved the cytochrome b gene products of pig species into two DNA fragments of 228 and 131 bp and did not cleave cytochrome b gene of beef and chicken [33].
Recent research [37] founded that pork DNA fragment of mitochondrial cytochrome b gen could be amplified well after cooking for 0–120 min (Figure 4), while cooking more than 120 min caused DNA degradation and failed to amplify mitochondrial DNA fragment, even for the PCR using more than 500 bp primer lengths. In addition, the amplification of 300 bp DNA fragment using specific primer showed DNA amplicon fragment in slight appearance. The band density decreased to less than 50% in sausage after cooking for more than 120 min. The 200 bp primer fragment could amplify all DNA samples from cooking for 120 min. Longer cooking time showed slighter appearance in gel electrophoresis and lower band intensity. Sausages were cooked for less than 120 min showed almost the same intensity, then decreased until about 60% band intensity. It indicated that the DNA from pork sausages after cooking for 120 min did not cause denaturation process, and the molecular weight did not decrease. The charged molecules can be separated in agarose gel electrophoresis according to smaller molecules migrating faster than larger molecules.
Amplification results of cooking time treatment. M: Marker, 1: no cooking (control), 2: 15 min, 3: 30 min, 4: 60 min, 5: 120 min, 6: 240 min, 7: 480 min. Above: 500 bp primer, middle: 300 bp primer, bottom: 200 bp primer.
While cooking for more than 120 min, damage was caused on DNA fragment and could be amplified using species specific primer only above 200-bp length fragment (Figure 4). The DNA fragmentation occurred when meat was processed and cooked. The other researches [38] stated that the damaging of the DNA, as well as other meat structural changes (shrinkage of meat fibers, the aggregation and gel formation of myofibril and sarcoplasmic proteins, shrinkage and solubilization of the connective tissue, etc.), is due to the denaturation during heating.
Compared to conventional end-point PCR, the main advantage of a real-time method is the possibility of performing quantitative measurements. The meat species identification using conventional PCR assays require the visualization using gel electrophoresis. The mistake analysis could increase with the chance of the cross-contamination or sample shifting; in addition, the process could not be automated. This condition may be a consequence because the PCR tubes must be opened after amplification. An alternative, shorter time-consuming analysis to differentiate the PCR products of various meat species would improve the assay. Melting curve analysis with an intercalating dye using a real-time PCR machine could remove the gel electrophoresis step, offered that the PCR products of the different species melt at different temperatures [39]. Basic principle of real-time PCR is the development of conventional PCR methods, in which amplification products can be monitored directly during each amplification cycle and can be measured. Real-time PCR testing allows for the identification of the early stages of the PCR process, which is more accurate than the endpoint analysis associated with agarose gel electrophoresis or polyacrylamide. The collecting data of real-time PCR was obtained using fluorescence molecules that showed a correlation between fluorescence intensity with PCR product abundance [40]. Real-time PCR is widely accepted as a powerful assay for the species identification and quantification of nucleic acid molecules. This procedure has higher sensitivity and specificity, larger dynamic range of detection, and less carry-over contamination risk. In the quantitative real-time PCR (qPCR) technique, amplification of the target gene is monitored by an increased fluorescence signal which enables direct assessment of the results after the PCR application without additional detection steps [41].
The amplification process of the PCR product can be observed from the beginning of the reaction to completion as shown in Figure 5. The number of PCR cycles is seen on the X-axis and the fluorescence of the amplification reaction on the Y axis. The amplification plot shows two phases, that is, the exponential phase followed by the non-exponential plateau phase. During the exponential phase, the amount of PCR products is approximately twice that of each cycle. In the plateau phase the reaction slows down (28–40 cycles) [43].
Amplification curves A: and melting peak; B: specificity of pork mitochondrial D-Loop686 primer on DNA from various raw meat. Red line: pork; yellow line: beef; dark blue line: chicken; green lines: goat; blue line: horse [42].
Threshold (initial limit) real-time PCR is the signal level which reflects statistically significant increases in baseline signal. The threshold is adjusted to differentiate the relevant amplification signal among the background. Typically, the real-time PCR instrument software automatically adjusts 10 times the standard deviation of the baseline fluorescence value [44]. Threshold cycle or commonly abbreviated as Ct is the number of cycles during the fluorescence signal, that is, the reaction cuts the threshold. The Ct value is used to calculate the number of initial DNA copies because the value of Ct is the inverse of the initial number of targets. If the number of templates decreases, then the number of cycles required for amplification will increase [45].
In the initial reaction, the fluorescence on the base level and the increase in fluorescence is not detected at 1–18 cycles, although the product accumulates exponentially (Figure 5) until finally the amplification products sufficient to emit fluorescence signal that can be detected. The number of cycles when amplification occurs is called early cycle (threshold cycle or Ct). If the Ct value is measured in exponential phase, as long as the reagent is not limited to, real-time PCR can accurately and reliably calculate the amount of DNA present in the reaction. There are several types of fluorescence based on chemicals used for the detection of real-time PCR, which can be classified into four types: probe hydrolysis as TaqMan®, probe hairpin as molecule Beacon molecule, probe hybridization labeled with fluorescence (FRET) and the DNA intercalation dye as SYBR® Green and EvaGreen® [46, 47].
Fluorescent compounds SYBR Green are asymmetric cyanine compounds that have two aromatic rings connected by metena bridges, and each ring contains a nitrogen atom, and one of which is positively charged [48]. When SYBR Green is in the solution containing double-stranded DNA (ds-DNA), then the SYBR Green can be bound to ds-DNA and will emit a fluorescent signal at a wavelength of 254 (excitation) and 497 (emission) nm [49]. Characterization of fluorescence level that is obtained by SYBR Green can be seen through the Ct value, that is, at the DNA fragment amplification cycle, which was first detected. SYBR Green is widely used for the purpose of amplification optimization using qPCR, because it is easier and cheaper than probe [50].
The previous research [42] performed the real-time polymerase chain reaction using mitochondrial displacement loop686 and cytochrome b (cytb) gene primers for the identification specific pork DNA among other four types of DNA species: beef, chicken, goat and horse. The annealing temperature was at 62°C; however, the mitochondrial D-Loop686 showed high specificity to porcine DNA detection, as indicated by no amplification results that appeared on other species (beef, chicken, horse and goat meat) (Figure 5). It was proven that this additional peak does not result from primer dimer, since no amplification product on sample without DNA template is present.
The implementation of d-Loop 686 DNA and cyt b gene primers was carried out in order to identify pork DNA on laboratory prepared “dendeng” (Indonesian traditional beef Jerky). The results indicated that mitochondrial d-Loop686 primer had high specificity on pork DNA target. Results of experiment indicated that the primer has ability to detect pork DNA until the concentration of pork was 0.5% in the beef dendeng product with the consistent curve profile. The cytb gene primers also had a similar ability with d-Loop686 primer to amplify pork DNA until the pork concentration was of 0.5% in beef “dendeng”. The results showed that these two primers, d-Loop region and the cyt b gene, had the capability to identify pork adulteration on the mixed pork-beef “dendeng” product at all variations of tested concentrations [42].
Soares et al. [8] applied a real-time PCR approach based on SYBR Green dye for the quantitative detection of pork meat in processed meat products. For the development of the method analysis, binary meat mixtures containing known amounts of pork meat in poultry meat were used to obtain a normalized calibration model from 0.1 to 25% with high linear correlation and PCR efficiency. The method revealed high specificity by melting curve analysis and was successfully validated through its application to blind meat mixtures, which confirmed its adequacy for pork meat determination. The full applicability of the method was further demonstrated in commercial meat products, allowing verification of labeling compliance and identification of meat species in processed foods. Figure 6 showed limit of detection of the real-time PCR which was able to detect the porcine DNA until 0.1 pg. contamination.
Amplification curves of binary reference mixtures (0.01–100 pg. of pork DNA) by real-time PCR with SYBR green I dye for pork detection and the detection limit was 0.1 pg.
DNA degradation, inhibition or differences in the amount and quality of the DNA obtained from the food matrix sample was found. It meant that the processed meat products generally had several ingredients, including those from vegetable sources, and different processing treatments that might affect the target-gene amplification, the use of an endogenous control, which enables these variations to be controlled. Therefore, the structure of calibration curve based on real-time PCR normalization is essential for reliable quantitative analysis because this process controls variations in extraction yields and efficiency of amplification. The endogenous control allows verifying if amplification variations found with the species-specific primers were due to differences in target species content or to other factors such as (8).
Kesmen et al. [41] conducted the real-time PCR investigation and they concluded that TaqMan probe real-time PCR-based assay can be recommended for the detection of animal tissue by food control agencies or laboratories, and it might be a reliable and practical method for the determination of technically predictable contamination and/or intentional admixtures in complex processed meat products. Table 3 described the application of the PCR-based technology on porcine determination of the commercial sample and Table 4 showed the type of gene, fragment length and sequence of the primer already applied by some researchers.
Species analysis | Issues | References |
---|---|---|
Animal Species | PCR assay for the identification of animal species in feedstuffs | [51] |
Analysis of rat’s meat DNA | Authentication of beef meatball from rat’s meat | [52] |
Analysis of pork DNA in dendeng | Authentication of “dendeng” from pork | [42] |
Analysis of porcine gelatin | Analysis of porcine gelatin in capsule shell | [53] |
Analysis of pork in meatball | Authentication of beef meatball from pork | [34] |
Analysis of pork DNA | Identification of pig species in food product | [1] |
Quantification of bovine, porcine, chicken and turkey species | Contamination and adulteration prohibited component in food and feed | [54] |
Porcine Gelatin | Using gelatin in pharmacy and confectionery | [55] |
Analysis of porcine species-based PCR technology on commercial samples.
Genealogy | Specific primer sequence (5′–3′) | Products size (bp) | References |
---|---|---|---|
Mitochondrial Cyt b | 5′ GCCTAAATCTCCCCTCAATGGTA 3′ 5′ ATGAAAGAGGCAAATAGATTTTCG 3′ | 212 | [55, 56] |
12S rRNA-tRNA | 5′ CTA AAT ATC AAG CAC CAT CAC A 3′ 5′ ACA TTG TGG GAT CTA CTT GG 3′ | 290 | [51] |
cytochrome b | 5′ CGC CTT ACG TTC TAA TGA CAT 3′ 5′ ATC CTA CTC T AG CC C ACC CA 3′ | 500 | [9] |
ND5 gene | 5′ CCATCCCAATTATAATATCCAACTC-3′ 5′ TGATTATTTCTTGGCCTGTGT GT 3′ | 141 | [57] |
12S rRNA | 5′ TGCAGTCTGTCTCCTCCAAA 3′ 5′ CGATAATTGGATCACATTTCTG 3′ | 152 | [58] |
Mitochondrial Dloop 686 | 5′ GTTACGGGACATAACGTGCG −3′ 5′ GGCAAGGCGTTATAGGGTGT −3′ | 114 | [8] |
Various length of specific target DNA primers for porcine detection.
Based on Table 4, the primer design for the application of the specific primer length target depends on the matrix sample. The sample with long period preparation and processing commonlythe DNA degraded into 100–200 bp, consequently if the PCR method applied using more than 300 bp DNA target. Some food matrix need long time preparation, conse.
It is common that food should consider an individual with health, culture, life style, religious faith, budget and choice. Food products without pork samples on the ingredients list, or even labeled ‘pork-free’, obtained from the commercial market and retail stores that could be confirmed by PCR-based methods. Many experiments showed the detection limit of less than 0.1% porcine material level. This data showed that some samples could be considered contaminants of porcine materials. Reviews of these findings showed the value of such an analytical approach to guarantee the commercial products in world free trade. PCR-based method is proposed to be a reliable and sensitive protocol for routine analysis.
Multiple myeloma (MM) is a complex and heterogeneous disease [1, 2, 3], with variable survival. MM is a malignancy of terminally differentiated clonal plasma cells (PC) which are primarily localized in the bone marrow. In most cases, these PC are able to secrete a monoclonal immunoglobulin (Ig) protein (M protein) in the serum and/or urine. About 15–20% of MM patients secrete monoclonal light chains (LC) only, without expression of the normal Ig heavy chain, which constitutes LCMM [4], a subtype of MM-associated to poor outcome [5, 6]. True non-secretory MM represents only about 3% [7, 8].
The current definition of MM is based on the demonstration of 10% or more clonal bone marrow PC (or a biopsy-proven plasmacytoma) and one or more of the so-called myeloma defining events (MDE), including those events that evidence end-organ damage such as hypercalcemia, renal insufficiency, anemia, or osteolytic bone lesions (CRAB), or the presence of a biomarker of malignancy such as 60% or more clonal PC, 100 or more involved/uninvolved serum free light chain ratio (i/u FLCr), or more than one focal lesion on MRI.
Most patients with newly-diagnosed MM (NDMM) are preceded by a precursor disease (PD) [9, 10]. The most frequent PD is the monoclonal gammopathy of undetermined significance (MGUS), which is defined by a low M protein level (<30 g/L in serum or <500 mg/24-hour in urine), <10% of clonal bone marrow PC, and absence of CRAB or amyloidosis. Smoldering MM (SMM) is an asymptomatic plasma cell disorder. It is an intermediate entity between MGUS and MM, characterized by both the absence of MDE or amyloidosis, and a certain level of M protein (Ig G or A ≥ 30 g/L in serum or ≥500 mg in 24-hour urine) and/or 10–60% clonal bone marrow PC. The risk of progression to MM of MGUS and SMM is about 1 and 10% per year, respectively [11, 12].
The outcome of patients with NDMM in terms of overall survival (OS) is highly variable according to the type of study, selection criteria and calendar period. The real improvement in OS over time can be shown using population-based registries in which all incident cases are included with standardized rules and thorough follow-up [13, 14, 15]. Several well-established or emergent prognostic factors in relation to the disease, the host, the stage and the response to therapy are involved. However, the current risk stratification systems [16, 17, 18, 19, 20] cannot accurately predict the outcome in a particular patient.
Multilevel heterogeneity is a common denominator of MM. The epidemiological background [21, 22], the clinical presentation [23, 24], the genetic instability [25, 26] as well as clonal evolution [27, 28], and finally, the response to therapy [29, 30], are the most relevant levels of heterogeneity. All of them have a well-known impact on the outcome. Epidemiology is probably the first level of heterogeneity and its knowledge is key to understand MM outcome. Herein, an updated perspective on the epidemiology of MM will be highlighted.
MM incidence within a geographically determined population can be established by means of population-based cancer registries. The main goal of these registries is the identification of all incident cases of NDMM diagnosed among the residents of a defined geographical area [31]. The International Agency for Research on Cancer and the International Association of Cancer Registries provides high-quality statistics on the incidence of cancer from population-based registries around the world [32].
The incidence of MM is generally higher in more-developed countries. The estimated NDMM incident cases in the United States throughout 2017 is 30,280 (17,490 men and 12,790 women), representing 1.8% of all new cancer, with an incidence rate (per 100,000 inhabitants and age-standardized to the 2000 United States standard population) of 8 and 5.2 respectively, and a male/female ratio of 1.5 [33]. Similar or slightly lower age-standardized incidence rates can be found in European countries [31, 34, 35, 36, 37, 38]. Conversely, in Asian countries, the incidence is particularly low [39, 40]. There is a marked racial disparity in the incidence of MGUS and MM, with a two to threefold increased risk in blacks compared with whites, after adjusting for socioeconomic and other risk factors, suggesting a genetic predisposition [41].
Most population-based cancer registries show a stable or slightly increasing MM incidence over the last decades. In some registries, an improvement in case ascertainment may be the reason for the slight increase trend in the incidence. Based on data from the Surveillance, Epidemiology, and End Results Program [42] approximately 0.8% of the population will be diagnosed with MM at some point during their lifetime. On the other hand, as expected, the prevalence of MM has increased due to progressive improvement in OS.
MM is a multifactorial disease with a wide variety of risk factors including both environmental and genetic. Despite the growing interest in the field, the etiology of MM is poorly understood. However, many risk factors have been implicated, with variable levels of evidence [43, 44]. Herein, the main risk factors will be reviewed. Interestingly, some of these variables such as age, sex, race, and others, have a double behavior, as risk and prognostic factors. Remarkably, only two risk factors are potentially preventable. On the one hand, obesity is an increasingly common comorbidity. On the other hand, the exposition to certain chemical products, such as some herbicides, has been also demonstrated to be associated with the risk of developing MM.
MM has a multistep pathogenesis [2, 45]. All MM patients are virtually preceded by a PD. Several PD can progress to MM, such as MGUS [46], SMM [12] or solitary plasmacytoma [47]. Despite the fact that MGUS is considered the main risk factor for MM, only few MM patients have a prior knowledge of MGUS at the time of the diagnosis of MM. Remarkably, in a Swedish nationwide study of 14,798 patients with MM, only 2.7% had previously diagnosed as having MGUS, but this subgroup showed significantly better OS [48]. Moreover, in the Granada (south of Spain) population-based cancer registry, all MM with any type of previously documented PD had a better outcome and this trend was maintained over the past three decades and it was not associated to diagnostic delay [49].
The incidence of cancer in general and hematologic malignancies increases with age. The median age of MM at diagnosis is about 70 years [14, 38]. 72% of patients included in the Swedish Multiple Myeloma Registry were 65 years or older [38]. The median relative survival was 7.7 years for patients 65 years or younger, in comparison with 3.4 years for those with 66 years or older.
Several studies [50, 51, 52, 53, 54] have demonstrated that the advanced age is predictive of shorter OS. Aging is associated with a decrease in the tolerability to treatment, a higher rate of drug discontinuation due to adverse events and lower cumulative delivered-dose. All these circumstances may have an impact on the outcome. Survival in older adults with MM is also improving, but to a lesser extent than in young patients [14, 55].
Age, along with renal failure and certain comorbidities, is associated with early mortality [56, 57]. The number of comorbidities increases with aging, and this may be one of the reasons why elderly people with MM have a poor outcome.
Most but not all registries show a higher incidence of MM in men. Moreover, in several studies, men have a trend to poorer survival in relation to women [14, 54, 58, 59] although in most cases this is not statistically significant.
The prognostic impact of race in OS is controversial. Racial disparities in outcomes may be related with biologic factors, individual factors, health behaviors, and structural barriers [60]. In a large study from the Surveillance, Epidemiology, and End Results (SEER), with more than 40,000 patients, the differences in OS between patients in the white and black race did not reach statistically significant differences [61]. A recent study from the Mayo Clinic did not found any survival difference by race but it showed considerable variability in MM therapeutics utilization with seeming inequity for racial-ethnic minorities [62]. A comprehensive study analyzing ethnically defined NDMM has shown molecular differences between African and European descent cases [63]. If this fact could have a clinical impact remains to be determined. Overall, the current evidence seems to confirm the conclusion of old studies pointing out that race is not a significant prognostic factor in MM, whereas the socioeconomic status may influence survival [64].
In recent years, the socioeconomic status has been suggested to be a confusing variable in order to analyze more deeply the association between race and survival. However, there was not strong evidence until recently. Fiala et al. [65] showed that low socioeconomic status was independently associated with poorer OS in 562 patients at the Washington University School of Medicine, and this was confirmed in a large cohort of 45,505 patients from the SEER. The most likely hypothesis for this is that this subgroup of patients delay seeking medical attention and thus are farther advanced at presentation. Costa et al. [66] also studied a cohort of 10,161 patients from SEER highlighting the strong impact of social determinants of health, such as marital status (other than married), insurance status, and income. In this study, income and education were reported at the county level, not at the individual level. An important limitation of both studies is that comorbidities are not registered in the SEER database and therefore, its influence could not be explored.
Accordingly, all variables affecting outcomes, including sociodemographic factors, should be taken into account in order to make rigorous comparisons between different therapeutic approaches. A widening gap among socioeconomic status groups have been shown in the last two decades [67]. In this increasingly complex therapeutic scenario, it is imperative to focus on subgroups that may remain disadvantaged [68].
Family history is a well-defined risk factor for cancer. The demonstration of MM in two or more members of the same family is a rare occurrence. However, several reports during the past three decades [69, 70, 71, 72, 73] have analyzed the pattern of aggregation and pointed out a putative autosomal dominant mode of genetic transmission, reporting an excess familial risk for MM of about 2- to 4-fold and supporting a role for germline susceptibility genes, shared environmental influences, or an interaction of both. A variation in the presence of defining clinical features in MM patients according to family history of hematologic malignancy has been described [74, 75]. MM showed an association with breast and prostate cancer, and colorectal cancer families, suggesting that MM shares genetic susceptibility with many cancers [76].
To facilitate international comparisons of occupational statistics, the definitions of all groups of occupations should be standardized [77]. The risk of MM has been associated with several manufacturing occupations and industries [78], such as machine operators and tenders, textile, food and beverage preparation, bakers and pastry cooks [79], printing and cleaning [80], hairdressers [81], and others. A meta-analysis including 5 cohort studies and 13 case–control studies on occupational exposure to dichloromethane, a widespread used solvent, showed an excess risk of MM [82].
Agriculture plays an important economic role in both developed and developing countries. There is a growing body of evidence about the association between farming and the risk of MM [83, 84, 85]. Despite methodological issues in some studies, the exposure to potential or confirmed carcinogens such as herbicides and pesticides commonly used by agricultural workers have been pointed out as key determinants of the cancer risk observed in agricultural populations. Some studies found a different pattern of risk according to sex [86] or even in female spouses of pesticide applicators [87]. Glyphosate is the most commonly used herbicide in the world and recent meta-analysis points out a marginally significant positive association with MM [88].
Obesity is one of the biggest problems in public health throughout the world. According to the WHO definition, obese individuals have a body mass index of 30 Kg/m2 or higher [89]. A causal link between obesity and cancer has been shown. About 20% of cancers are obesity-related, even 40% including overweight [90].
About 32% of NDMM patients are obese [14] Four meta-analysis have shown a positive association between obesity and MM risk [91, 92, 93, 94]. The impact of obesity on the number of obesity-attributable NDMM cases was estimated to be 1.3 as relative risk and about 10% as population attributable risk [95]. On the other hand, the association of obesity with higher all-cause mortality is consistent [96], although the role of obesity as prognostic factor in MM is controversial. However, evidence suggests that obesity could have a negative impact on MM outcome [97].
Obesity and type 2 diabetes share close ties [98]. Approximately one fifth of NDMM have type 2 diabetes. The association between type 2 diabetes and MM has been evaluated in one meta-analysis [99] showing a trend toward significantly increased odds of MM in patients with type 2 diabetes. Moreover, some genetic variants may influence the risk of developing MM [100]. There is increasing evidence regarding the role of type 2 diabetes as an independent prognostic factor in MM at both clinical and genomic level [101, 102].
Alcohol consumption is a major cause of disease and death worldwide. More than 5% of the total number of cancer cases are alcohol-attributable [103]. However, the role of alcohol intake in the MM risk is unclear. Interestingly several studies, including two meta-analyses, have shown a protective effect in terms of MM risk [104, 105, 106, 107].
Smoking is not considered a risk factor for MM [108, 109]. Surprisingly, a recent study shows a potential interaction between certain single nucleotide polymorphisms and smoking associated with increase MM risk [110].
The current evidence about this topic is not strong due to the inherent difficulties and characteristics of the studies. Notwithstanding, some issues can be highlighted. A high consumption of fish is inversely associated with MM risk [111]. The consumption of green tea seems to have a protective effect in some [43] but not all studies [112]. Combined fruit and vegetable consumption has been associated with decreased non-Hodgkin lymphoma risk but it did not reach statistical significance for MM [113]. Remarkably, a diet-induced obesity promotes an MM-like condition [114]. Despite the potentially important role of diet and nutrition in cancer prevention, the current evidence is inconsistent [115].
The literature surrounding MM and physical activity are very limited [116]. Leisure-time physical activity was associated with lower risks of many cancer types, including MM [117, 118]. The effectiveness of participation in exercise programs remains unclear for patients with MM [119].
Little evidence supports the infection with hepatitis B and C viruses [120, 121], environmental factors [122], or the use of drugs [123], as risk factors for MM.
Besides obesity and type 2 diabetes, other conditions such as autoimmune diseases [124], thyroid disease [125], or inflammatory disorders [126], may increase the MM risk.
Autoimmune diseases constitute a heterogeneous group of disorders, which jointly affect 5–10% of the population. In relation to the potential association of autoimmune diseases and MM, an individualized approach must be implemented. A significant increase in MM incidence after ankylosing spondylitis and systemic sclerosis was showed [124]. A few cases of immune thrombocytopenia purpura associated with MM at the time of MM diagnosis have been reported [127]. In a Swedish cohort study, a significant increase of MM was demonstrated in women previously diagnosed with pernicious anemia [128]. A history of the autoimmune disease has been recently associated with impaired OS in MM and MGUS [129].
Host-related immunodeficiency is known to play a role in the development of MM [130]. More than 8% of NDMM have a prior or synchronous malignancy [14]. MM is associated with many other malignancies, including colorectal, breast and prostate cancers, non-thyroid endocrine tumors, leukemia and cancer of unknown primary [76]. The prognosis of patients with a second or third cancer is inferior [131]. Sometimes, NDMM and other hematological neoplasm such as myelodysplastic syndrome are diagnosed at the same time in the same patient [132]. Increased life expectancy has led to renewed concerns about the long-term risk of second primary malignancies [133].
OS remains the key end-point in both clinical trials and real-life patients. Survival in MM is highly variable and depends on prognostic factors, which can be categorized into four groups: host-related, disease-related, staging and therapy. Among host-related factors, comorbidity plays an important role. However, the analysis of prognostic factors is beyond the aim of this chapter. Notwithstanding, it must be emphasized that many of the above-mentioned risk factors can also behave as prognostic factors, as is the case of age. In this regard, less than 3% of patients with MM are younger than 40 years, showing similar clinical features to the whole MM population, except for a higher proportion of LCMM [134]. On the other hand, renal impairment is a common presenting complication of MM with a negative impact on the outcome; despite this, there has been a major improvement in OS in these patients, although the risk of early death remains high [135]. Moreover, the size and type of institution where the patients are treated may have an impact on the outcome in some studies [38, 136, 137]. OS has continuously improved over the past decades due to better supportive care and advances in therapy. Population-based studies are needed to accurately estimate OS in real-life patients [14, 35, 38]. An important gap exists between the outcome of these patients and those included in clinical trials, which have to fulfill specific selection criteria. Although some patients can achieve deep responses and become long-term survivors, being some of them cured, the goal of curing MM in a significant proportion of patients is still far away. In the current scenario, getting and maintaining a minimal residual disease has become the primary objective of therapy before cure [29]. In the meantime, the importance of improving quality of life should be pointed out [138].
Based on data from the SEER Program [42], MM is the fourteenth leading cause of cancer death in the United States. The number of deaths was 3.3 per 100,000 men and women per year (age-adjusted rates), based on 2010–2014 deaths.
Comorbidity has also an impact on mortality, in particular, early mortality [57]. Infection remains as the first cause of death in most studies, frequently associated with aging, renal failure, and relapse. Therefore, every effort to avoid serious infection should be taken into account. In this regard, prophylactic antibiotics [139] and vaccines are key measures.
Little is known about effective measures to avoid the development of MM. Early treatment of asymptomatic patients with high-risk SMM or even high-risk MGUS, now only in the context of clinical trials, may prevent the appearance of MM, increasing the probability of cure [140].
Currently, the potentially preventable risk factors for MM are obesity and the exposure to MM-related carcinogens, particularly in the context of farming. Efforts should be made to fight globally and effectively against these risk factors.
On the other hand, the prevention of treatment-related adverse events is a matter of concern [141].
MM is a very complex and heterogeneous disease. Heterogeneity is largely responsible for the great variability in the outcome of patients and can be stratified in several levels. Epidemiology should be considered the first level of heterogeneity. Therefore, the knowledge of the epidemiological background should be taken into account in both real-life and clinical trials settings to accurately assess the outcome, allowing a precise comparison between studies.
MM epidemiology is an exciting research topic. In the era of precision and personalized medicine, both clinical and molecular epidemiology should be integrated as a mandatory step in the optimized workup of every patient.
MM is a multistep malignancy. Virtually all patients with NDMM had a previous precursor disease. However, the proportion of NDMM patients with a previously known precursor disease is remarkably small. Both MGUS and SMM have also a heterogeneous pattern of risk progression. Early treatment in high-risk SMM is expected to increase the rate of cure.
MM is a multifactorial condition. Many risk factors are involved with variable levels of evidence. The meta-analysis is located at the top of the pyramid of evidence, having largely contributed to highlight the role of potential or plausible risk factors.
MM is a rapidly changing field. In the last decade, the pathogenesis, diagnosis, prognosis, and treatment of MM have dramatically changed. The knowledge of the epidemiological perspective can help to better understand current and future challenges, leading to an optimized MM care.
We believe financial barriers should not prevent researchers from publishing their findings. With the need to make scientific research more publicly available and support the benefits of Open Access, more and more institutions and funders are dedicating resources to assist faculty members and researchers cover Open Access Publishing Fees (OAPFs). In addition, IntechOpen provides several further options presented below, all of which are available to researchers, and could secure the financing of your Open Access publication.
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\\n\\nFor Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
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\\n\\nThe application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
\\n\\nDownload Waiver Request Form
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
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\n\nHowever, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
\n\nPlease consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
\n\nFor Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
\n\nOur mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
\n\nWhile providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
\n\nThe application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
\n\nDownload Waiver Request Form
\n\nFeel free to contact us at oapf@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
\n\nNote: All data represented above was collected by IntechOpen from 2013 to 2017.
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