Research - Revision history

Janr at 13:44, 5 June 2018

2018-06-05T13:44:13Z

Janr at 13:41, 5 June 2018

2018-06-05T13:41:15Z

Janr at 17:15, 24 May 2018

2018-05-24T17:15:07Z

Janr: /* EPIDEMIC SIMULATIONS */

2018-05-10T16:18:41Z

‎EPIDEMIC SIMULATIONS

Janr: /* GENETIC STUDIES */

2018-05-10T16:17:45Z

‎GENETIC STUDIES

Janr: /* Temporal and spatial evolution of the Influenza-A hemagglutinin genes */

2015-02-03T07:47:23Z

‎Temporal and spatial evolution of the Influenza-A hemagglutinin genes

Janr: /* Role of the host genetic variability in the influenza A virus susceptibility (a review) */

2015-02-03T01:12:31Z

‎Role of the host genetic variability in the influenza A virus susceptibility (a review)

Janr at 01:09, 3 February 2015

2015-02-03T01:09:57Z

Janr at 01:07, 3 February 2015

2015-02-03T01:07:59Z

Janr: /* Alignment-free genome sequence analysis by the ISSCOR method */

2013-10-14T12:51:27Z

‎Alignment-free genome sequence analysis by the ISSCOR method

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 === GENETIC STUDIES ===

← Older revision		Revision as of 17:15, 24 May 2018
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 [[Image:PhysA_illness_progression.jpg |frameless|400px|left]]
-The individual agent-based model (IABM) described above was used for studying the effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland. Simple transportation rules were employed to mimic individuals' travels in dynamic route-changing schemes, allowing for the infection spread during their journeys.
+The individual agent-based model (IABM) described above was used for studying the effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland. Simple transportation rules were employed to mimic individuals' travels in dynamic route-changing schemes, allowing for the infection spread during their  journeys.
 Parameter space was checked for stable behavior, especially towards the effective infection transmission rate variability. Following the assumptions employed in this work, a two-dimensional scan of the '''''alpha''''' and '''''f''''' parameters was performed in order to determine feasible scenarios of epidemic evolution. It should be noted, that the same R0 values may be obtained with different sets of '''''alpha''''' and '''''f'''''. In our research the R0 value varies from 1.44 to 2.42, which is a range comparable to other ranges studied in this field. In principle, R0 values are linearly related to '''''alpha''''' for each of the '''''f''''' values (R0 monotonically increases with '''''alpha''''' when other parameters, here f, are fixed), and therefore, the properties of the model system may be analyzed using '''''alpha''''' classification for each of the '''''f''''' ratios used. A series of possible epidemic courses for '''''alpha''''' ranging from 0.1 to 0.2 and for '''''f''''' taking values of 0.2, 0.4, 0.6, 0.8 and 1.0 were obtained by carrying out the simulations. In this parameter range we have encountered several similar R0 values which correspond to different epidemic courses. One can see that the definition of R0 does not fully account for the dynamically changing structure of the contact network or for the dynamic threshold of the "saturation" of the contexts

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 [[Image:occurence_probability.gif |frameless|300px|right]]
-Synonymous codons do not occur at equal frequencies. Codon usage and codon bias have been extensively studied. However, the sequential order in which synonymous codons appear within a gene has not been studied until now. Here we describe an ''in silico'' method, which is the first attempt to tackle this problem: to what extent this sequential order is unique, and to what extent the succession of synonymous codons is important. This method, which we called Intragenic, Stochastic Synonymous Codon Occurrence Replacement (ISSCOR), generates, by a Monte Carlo approach, a set of genes which code for the same amino acid sequence, and display the same codon usage, but have random permutations of the synonymous codons, and therefore different sequential codon orders from the original gene. We analyze the complete genome of the bacterium ''Helicobacter pylori'' (containing 1574 protein coding genes), and show by various, alignment-free computational methods (e.g., frequency distribution of codon-pairs, as well as that of nucleotide bigrams in codon-pairs), that: (i) not only the succession of adjacent synonymous codons is far from random, but also, which is totally unexpected, the occurrences of non-adjacent synonymous codon-pairs are highly constrained, at strikingly long distances of dozens of nucleotides; (ii) the statistical deviations from the random synonymous codon order are overwhelming; and (iii) the pattern of nucleotide bigrams in codon-pairs can be used in a novel way for characterizing and comparing genes and genomes. Our results demonstrate that the sequential order of synonymous codons within a gene must be under a strong selective pressure, which is superimposed on the classical codon usage. This new dimension can be measured by the ISSCOR method, which is simple, robust, and should be useful for comparative and functional genomics. (more: '''http://www.sciencedirect.com/science/article/pii/S1631069108003223''')<br>
+Synonymous codons do not occur at equal frequencies. Codon usage and codon bias have been extensively studied.  However, the sequential order in which synonymous codons appear within a gene has not been studied until now. Here we describe an ''in silico'' method, which is the first attempt to tackle this problem: to what extent this sequential order is unique, and to what extent the succession of synonymous codons is important. This method, which we called Intragenic, Stochastic Synonymous Codon Occurrence Replacement (ISSCOR), generates, by a Monte Carlo approach, a set of genes which code for the same amino acid sequence, and display the same codon usage, but have random permutations of the synonymous codons, and therefore different sequential codon orders from the original gene. We analyze the complete genome of the bacterium ''Helicobacter pylori'' (containing 1574 protein coding genes), and show by various, alignment-free computational methods (e.g., frequency distribution of codon-pairs, as well as that of nucleotide bigrams in codon-pairs), that: (i) not only the succession of adjacent synonymous codons is far from random, but also, which is totally unexpected, the occurrences of non-adjacent synonymous codon-pairs are highly constrained, at strikingly long distances of dozens of nucleotides; (ii) the statistical deviations from the random synonymous codon order are overwhelming; and (iii) the pattern of nucleotide bigrams in codon-pairs can be used in a novel way for characterizing and comparing genes and genomes. Our results demonstrate that the sequential order of synonymous codons within a gene must be under a strong selective pressure, which is superimposed on the classical codon usage. This new dimension can be measured by the ISSCOR method, which is simple, robust, and should be useful for comparative and functional genomics. (more: '''http://www.sciencedirect.com/science/article/pii/S1631069108003223''')<br>
 <!--[[Genetic:isscor | '''More..''']]-->

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 [[Image:Spatial evolution.jpg |frameless|300px|right]]
 Another set '''C''', comprising of 613 orthologous genes of the H5N1 avian flu virus’ hemagglutinin (HA), of 1707 nucleotides each – isolated from avian hosts during the 1996-2009 period – was acquired from NCBI in January 2010. All sequences were unique – in cases when two (or several) sequences were identical, only the earliest one was included. The ISSCOR descriptors were calculated for this set of sequences, using. codon spacer values from 0 to 16. The '''Figure''' on the right shows the PCA scatter plot of PC1 vs. PC2 for this set, divided for twelve territorial regions, characterized by the most numerous populations of isolates. Their plots are presented as separate panels, there are also separate panels showing remaining strains obtained from Africa, Asia and Europe. Already the analogous results for the A/H1N1 have shown some territorial clustering in several regions. In case of H5N1 the groupings are remarkably well defined and in many instances also rather well separated between themselves. This is especially evident for strains isolated in several Far Eastern, and South-East Asian countries: China, Vietnam, Hong Kong, Indonesia, and Thailand. On the other hand, isolates from Europe co-cluster together independently of their country of origin, which is also true for African and Middle-East countries – all of which form the large gathering at around PC1 = -3, and PC2 = 0 position. In roughly the same location there are also points for several Asian countries (all of which are different from the already mentioned five): Afghanistan, Pakistan, Bangladesh, India, Mongolia, Kazakhstan, and Japan. There are also two exceptions from Asia (well separated blue triangles in the panel "Asia") – one sequence from Japan (A/duck/Yokohama/aq10/2003, AB212280), and one from Myanmar (A/chicken/Pyigyitagon/204/2006, AB474081), both of them collocated together within the bottom cluster from China. The former H5N1 strain was isolated from duck meat processed for human consumption, imported to Japan from Shandong Province, China in 2003. That virus was antigenically different from other H5 viruses, including the Hong Kong H5N1 viruses isolated from humans in 1997 and 2003. The latter strain was isolated during the 1-st outbreak of bird flu in Myanmar in March 2006, and it was subsequently found to belong to the clade-7 (the WHO H5N1 evolution nomenclature) of the highly pathogenic avian influenza (HPAI). There is also one, rather unexpected case of the isolate from a Belgian crested eagle (A/crested_eagle/Belgium/01/2004, DQ182483; the green square, shown here for clarity at the edge of the top cluster in the panel "Vietnam"). On a closer examination this highly pathogenic H5N1 strain turned out to have been isolated from smuggled eagles, confiscated at the national airport, after an attempt to illegally enter them into Belgium from Thailand by a traveler.
-Phylogeography of H5N1 viruses was actively researched recently in the regions of Southeast Asia and Far East which were repeatedly subjected to outbreaks of bird flu in poultry, esp. in Vietnam, Thailand, and China, with conclusions rather similar ours, concerning the yearly origins and seasonal spread of the A/H3N2 viruses. Wallace ''et al''. studied the geographic diffusion of H5N1 following the migration paths of the virus, by a way of a genetic phylogeography of H5N1’s HA and NA sequences, and shown that the Chinese province of Guangdong was the source of multiple H5N1 strains spreading at both regional and international scales. In contrast, Indochina appeared to be a regional sink, at the same time demonstrating bidirectional dispersal among localities within the region. They have shown further that the virus migration was filtered out at some international borders, like between China and Vietnam or Thailand, but not at e.g. the one between China and Japan. Their results were recently reanalyzed by Hovmoeller ''et al''. who alleged that using a single tree, and a single optimization path, miss-estimates the frequency of transmission events, and moreover that the use of a single tree can fail to detect possible transmission events.
+Phylogeography of H5N1 viruses was actively researched recently in the regions of Southeast Asia and Far East which were repeatedly subjected to outbreaks of bird flu in poultry, esp. in Vietnam, Thailand, and China, with conclusions rather similar ours, concerning the yearly origins and seasonal spread of the A/H3N2 viruses. Wallace ''et al''. studied the geographic diffusion of H5N1 following the migration paths of the virus, by a way of a genetic phylogeography of H5N1’s HA and NA sequences, and shown that the Chinese province of Guangdong was the source of multiple H5N1 strains spreading at both regional and international scales. In contrast, Indochina appeared to be a regional sink, at the same time demonstrating bidirectional dispersal among localities within the region. They have shown further that the virus migration was filtered out at some international borders, like between China and Vietnam or Thailand, but not at e.g. the one between China and Japan. Their results were recently reanalyzed by Hovmoeller ''et al''. who alleged that using a single tree, and a single optimization path, miss-estimates the frequency of transmission events, and moreover that the use of a single tree can fail to detect possible transmission events (more: <b>http://www.actabp.pl/#File?./html/3_2014/441.html</b>).
 ==== Improving the readability and an ''in silico'' automatic interpretation of Neighbor Joining phylogenetic reconstructions  ====

@@ Line 69: / Line 69: @@
 ==== Role of the host genetic variability in the influenza A virus susceptibility (a review)  ====
-The initial motivation for this review was an open question: Is susceptibility to severe influenza in humans heritable? – hard to answer, but not due to a lack of genotyping or analytic tools, nor because of insufficient evidence from severe influenza cases, but because of the absence of a coordinated effort to define and assemble cohorts of cases. Here we presented an update overview of the host variability of genes associated with flu infection, and discuss the possible influence of this variability on the severity of flu infection. Each virus-host interaction begins with entry of the virus into the host organism, and ends either in death of the individual or in elimination of the virus by the immune system. Evolution of the host–pathogen interactions yields variants in host genes, several of which are ultimately associated with bad or good prognosis following infection, while boosting the host’s future resilience towards given, specific strain subtype of the viral epitopes. Even if the severity of infection was mild and/or asymptomatic, these variants have been shown to be polymorphic in different human populations, which could be correlated with the different rates of morbidity/mortality from the influenza-A infectivity. Therefore, the answer to the initial question is positive, the susceptibility to severe influenza in humans is heritable.
+The initial motivation for this review was an open question: <i><b>Is susceptibility to severe influenza in humans heritable</b></i>? – hard to answer, but not due to a lack of genotyping or analytic tools, nor because of insufficient evidence from severe influenza cases, but because of the absence of a coordinated effort to define and assemble cohorts of cases. Here we presented an update overview of the host variability of genes associated with flu infection, and discuss the possible influence of this variability on the severity of flu infection. Each virus-host interaction begins with entry of the virus into the host organism, and ends either in death of the individual or in elimination of the virus by the immune system. Evolution of the host–pathogen interactions yields variants in host genes, several of which are ultimately associated with bad or good prognosis following infection, while boosting the host’s future resilience towards given, specific strain subtype of the viral epitopes. Even if the severity of infection was mild and/or asymptomatic, these variants have been shown to be polymorphic in different human populations, which could be correlated with the different rates of morbidity/mortality from the influenza-A infectivity. Therefore, the answer to the initial question is positive, the susceptibility to severe influenza in humans is heritable.
 On the other hand, it does not mean that all causes and variance in symptomatology and morbidity of flu infections have been discovered, or that they are only due to host genetic profile, but there are clearly several genes in the human genome that might have a direct impact on the course of influenza-A infections. In particular, when considering the ethnicity-derived genomic variance, some aspects of specific habitats and climates should not be neglected. In temperate regions the peak flu infectivity is felt predominantly during the winter months and epidemics recur with a highly predictable seasonal pattern. The studies using mouse-adapted strains of influenza virus, with experiments performed in the winter months yielded a transmission rate of 58.2%, yet of only 34.1% in summer. It has been hypothesized that possible causes of such seasonality include fluctuations in host immune efficiency mediated by seasonal factors such as melatonin and vitamin D levels; the changes in host behavior (school attendance, indoor crowding, air travel, etc.); but in particular environmental factors, including temperature, relative humidity, and the direction of seasonal winds movement in the upper atmosphere. The role of the South-East Asia region, in particular in countries spanning latitudes from subtropical at the south to high-mountainous at the north through several climactic zones, as spawning grounds of new flu strains is very well known, and a field of intense phylogeographical research. In contrast, the situation differs in the [sub]tropical regions, which experience influenza throughout the year, with somewhat increased incidence during rainy seasons. Such regions, like rainforests of equatorial Africa, or Amazonian regions of Brazil, Venezuela and Ecuador, are still potentially rich areas for a concerted efforts to connect the possible ethnic genomics factors in isolated communities, with the influenza-A prevalence and infectivity patterns.

← Older revision		Revision as of 01:09, 3 February 2015
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	Also, many factors can cause modifications in DNA (epigenetic modifications) that alter gene expression. Several studies support the theory of prenatal/childhood programming as origin of various adult diseases. Epigenetic modifications were described to explain adult disease in response to environmental modifications in prenatal or childhood. For example, Yang and Huffman (2013) showed that individuals who suffer some sort of nutritional privation during gestation tend to become obese adults. It can be thought that if the pattern of methylation that is programmed in one's genome during development can affect the way that individual will react to a diet as an adult, it might possibly affect the way immune-related genes are expressed during infections.		Also, many factors can cause modifications in DNA (epigenetic modifications) that alter gene expression. Several studies support the theory of prenatal/childhood programming as origin of various adult diseases. Epigenetic modifications were described to explain adult disease in response to environmental modifications in prenatal or childhood. For example, Yang and Huffman (2013) showed that individuals who suffer some sort of nutritional privation during gestation tend to become obese adults. It can be thought that if the pattern of methylation that is programmed in one's genome during development can affect the way that individual will react to a diet as an adult, it might possibly affect the way immune-related genes are expressed during infections.

−	Very recently the work of Guihot et al. (2014) demonstrated some curious cases that impose more questions than answers. The authors have found biological markers that can predict whether an individual is more prone to suffer lethal consequences to influenza infection. However, the genetic variability that underlies such markers is not well understood – e.g., some of the markers indicated a "trapping" antibodies in the lungs for the lethal cases, whilst the survivors had the antibodies freed into a blood. In another recent study Worobey et al. (2014) have hypothesized that the high mortality during the 1918 Spanish flu pandemic among adults aged ~20 to ~40 years might have been due primarily to their childhood exposure to a heterosubtypic putative H3N8 virus – estimated as to have been circulating from ~1889–1900. All other age groups (except immunologically naive infants) were likely to be partially protected by childhood exposure to N1 and/or H1-related antigens. Such tenet poses immediate questions. What possible immunological mechanism[s] already described, might explain such an increase of mortality rates? Especially a mechanism of contrasting the H3 non-naïve young-adult Spanish flu victims (but putatively naïve towards H1 serotype), with infants – by definition naïve to all HA subtypes. In effect such a mechanism would require a convincingly plausible pathway[s] of suppressing immunity specifically by an action of H3-derived epitopes. One possible mechanism would be that the exposure to this putative H3N8 virus could have caused a methylation pattern in some genes, especially on some paths of immune response, and as consequence these patients had an extremely severe flu. Also, maybe not all individuals exposed to this virus developed the same methylation patterns and final supressions due to the genetic variability known to exist in human populations. The authors postulate that a mechanism akin to original antigenic sin (OAS, Francis T, 1960) may have interfered with immune responses in some of those infected in 1918, and peaked in those exposed previously to the 1889 virus. However, such hypothesis opens important questions about possible molecular and immunological mechanisms pertaining to the actual OAS phenomena “in action”. It is obvious that many more studies of this type will be necessary to better understand how the environment and host genetic variability affects the susceptibility to the influenza-A virus. The present review shows that both host genetic variability as well as environment are clearly factors of great importance to determine such susceptibility. (more: http://www.actabp.pl/#File?./html/3_2014/403.html) <br>	+	Very recently the work of Guihot et al. (2014) demonstrated some curious cases that impose more questions than answers. The authors have found biological markers that can predict whether an individual is more prone to suffer lethal consequences to influenza infection. However, the genetic variability that underlies such markers is not well understood – e.g., some of the markers indicated a "trapping" antibodies in the lungs for the lethal cases, whilst the survivors had the antibodies freed into a blood. In another recent study Worobey et al. (2014) have hypothesized that the high mortality during the 1918 Spanish flu pandemic among adults aged ~20 to ~40 years might have been due primarily to their childhood exposure to a heterosubtypic putative H3N8 virus – estimated as to have been circulating from ~1889–1900. All other age groups (except immunologically naive infants) were likely to be partially protected by childhood exposure to N1 and/or H1-related antigens. Such tenet poses immediate questions. What possible immunological mechanism[s] already described, might explain such an increase of mortality rates? Especially a mechanism of contrasting the H3 non-naïve young-adult Spanish flu victims (but putatively naïve towards H1 serotype), with infants – by definition naïve to all HA subtypes. In effect such a mechanism would require a convincingly plausible pathway[s] of suppressing immunity specifically by an action of H3-derived epitopes. One possible mechanism would be that the exposure to this putative H3N8 virus could have caused a methylation pattern in some genes, especially on some paths of immune response, and as consequence these patients had an extremely severe flu. Also, maybe not all individuals exposed to this virus developed the same methylation patterns and final supressions due to the genetic variability known to exist in human populations. The authors postulate that a mechanism akin to original antigenic sin (OAS, Francis T, 1960) may have interfered with immune responses in some of those infected in 1918, and peaked in those exposed previously to the 1889 virus. However, such hypothesis opens important questions about possible molecular and immunological mechanisms pertaining to the actual OAS phenomena “in action”. It is obvious that many more studies of this type will be necessary to better understand how the environment and host genetic variability affects the susceptibility to the influenza-A virus. The present review shows that both host genetic variability as well as environment are clearly factors of great importance to determine such susceptibility. (more: <b>http://www.actabp.pl/#File?./html/3_2014/403.html</b>) <br>

← Older revision		Revision as of 01:07, 3 February 2015
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	We argue that tree reconstructions minimizing a number of spurious multiplication of a single “true” G1171A mutation (to the extent possible by the internal contradictions extant in an analyzed sets of sequences) are important for a better estimation of mutation rates. The actual composition of this set determines that there always will be at least one mutation on each of the 1226 positions, irrespective of the tree reconstruction method used. The mutable positions are therefore 72% of the gene length; while 28% are strictly conserved – a proportion in almost exact agreement with Eigen’s estimates for RNA viral evolution. The ratio of variable vs. hypervariable regions, however, depends on the tree reconstruction approach employed – approximately 40% of these 1226 mutations will have an amino acid changing character, although their exact number and the compositions are dependant to some extent on the reconstruction approach employed. Nevertheless, disentangling tree’s branches not only helps to eliminate spurious peaks of overestimated mutation rates, but it also makes possible to trace mutations occurring for the same codons – esp. of non-equivalent amino acid changes subsequent to a previous simple silent nucleotide mutations – both vital factors to consider. Moreover, such accumulation can lead to yet another phenomenon: of co-clustering several mutations within the same sub-clades, like e.g. the T1056C (G352, silent mutation, on 3rd codon position) with the C1656T (F552, silent, on 3rd position), or the T1408C (L470, silent, on 1st position) with the C1437T (N471, silent, on 3rd position). This might lead to forming a possible “foundation” for a subsequent non-reassortant genetic shift event, of the type recently sought experimentally by Imai's or Fouchier's groups, and then mathematically modeled by Russell et al. in a study of probabilistically estimated substitutions, leading possibly to more virulent strains. But even more important for such model predictions would be the ability to use data for time and location resolved evolution pathways with reasonably better levels of confidence, esp. as our estimated substitution rates for H1N1 pandemic, obtained through the disentangled three method, are of at least magnitude order lower than estimated earlier. (more: '''http://dx.doi.org/10.1016/j.ympev.2013.08.020''')<br>		We argue that tree reconstructions minimizing a number of spurious multiplication of a single “true” G1171A mutation (to the extent possible by the internal contradictions extant in an analyzed sets of sequences) are important for a better estimation of mutation rates. The actual composition of this set determines that there always will be at least one mutation on each of the 1226 positions, irrespective of the tree reconstruction method used. The mutable positions are therefore 72% of the gene length; while 28% are strictly conserved – a proportion in almost exact agreement with Eigen’s estimates for RNA viral evolution. The ratio of variable vs. hypervariable regions, however, depends on the tree reconstruction approach employed – approximately 40% of these 1226 mutations will have an amino acid changing character, although their exact number and the compositions are dependant to some extent on the reconstruction approach employed. Nevertheless, disentangling tree’s branches not only helps to eliminate spurious peaks of overestimated mutation rates, but it also makes possible to trace mutations occurring for the same codons – esp. of non-equivalent amino acid changes subsequent to a previous simple silent nucleotide mutations – both vital factors to consider. Moreover, such accumulation can lead to yet another phenomenon: of co-clustering several mutations within the same sub-clades, like e.g. the T1056C (G352, silent mutation, on 3rd codon position) with the C1656T (F552, silent, on 3rd position), or the T1408C (L470, silent, on 1st position) with the C1437T (N471, silent, on 3rd position). This might lead to forming a possible “foundation” for a subsequent non-reassortant genetic shift event, of the type recently sought experimentally by Imai's or Fouchier's groups, and then mathematically modeled by Russell et al. in a study of probabilistically estimated substitutions, leading possibly to more virulent strains. But even more important for such model predictions would be the ability to use data for time and location resolved evolution pathways with reasonably better levels of confidence, esp. as our estimated substitution rates for H1N1 pandemic, obtained through the disentangled three method, are of at least magnitude order lower than estimated earlier. (more: '''http://dx.doi.org/10.1016/j.ympev.2013.08.020''')<br>
		+
		+	==== Role of the host genetic variability in the influenza A virus susceptibility (a review) ====
		+
		+	The initial motivation for this review was an open question: Is susceptibility to severe influenza in humans heritable? – hard to answer, but not due to a lack of genotyping or analytic tools, nor because of insufficient evidence from severe influenza cases, but because of the absence of a coordinated effort to define and assemble cohorts of cases. Here we presented an update overview of the host variability of genes associated with flu infection, and discuss the possible influence of this variability on the severity of flu infection. Each virus-host interaction begins with entry of the virus into the host organism, and ends either in death of the individual or in elimination of the virus by the immune system. Evolution of the host–pathogen interactions yields variants in host genes, several of which are ultimately associated with bad or good prognosis following infection, while boosting the host’s future resilience towards given, specific strain subtype of the viral epitopes. Even if the severity of infection was mild and/or asymptomatic, these variants have been shown to be polymorphic in different human populations, which could be correlated with the different rates of morbidity/mortality from the influenza-A infectivity. Therefore, the answer to the initial question is positive, the susceptibility to severe influenza in humans is heritable.
		+
		+	On the other hand, it does not mean that all causes and variance in symptomatology and morbidity of flu infections have been discovered, or that they are only due to host genetic profile, but there are clearly several genes in the human genome that might have a direct impact on the course of influenza-A infections. In particular, when considering the ethnicity-derived genomic variance, some aspects of specific habitats and climates should not be neglected. In temperate regions the peak flu infectivity is felt predominantly during the winter months and epidemics recur with a highly predictable seasonal pattern. The studies using mouse-adapted strains of influenza virus, with experiments performed in the winter months yielded a transmission rate of 58.2%, yet of only 34.1% in summer. It has been hypothesized that possible causes of such seasonality include fluctuations in host immune efficiency mediated by seasonal factors such as melatonin and vitamin D levels; the changes in host behavior (school attendance, indoor crowding, air travel, etc.); but in particular environmental factors, including temperature, relative humidity, and the direction of seasonal winds movement in the upper atmosphere. The role of the South-East Asia region, in particular in countries spanning latitudes from subtropical at the south to high-mountainous at the north through several climactic zones, as spawning grounds of new flu strains is very well known, and a field of intense phylogeographical research. In contrast, the situation differs in the [sub]tropical regions, which experience influenza throughout the year, with somewhat increased incidence during rainy seasons. Such regions, like rainforests of equatorial Africa, or Amazonian regions of Brazil, Venezuela and Ecuador, are still potentially rich areas for a concerted efforts to connect the possible ethnic genomics factors in isolated communities, with the influenza-A prevalence and infectivity patterns.
		+
		+	Also, many factors can cause modifications in DNA (epigenetic modifications) that alter gene expression. Several studies support the theory of prenatal/childhood programming as origin of various adult diseases. Epigenetic modifications were described to explain adult disease in response to environmental modifications in prenatal or childhood. For example, Yang and Huffman (2013) showed that individuals who suffer some sort of nutritional privation during gestation tend to become obese adults. It can be thought that if the pattern of methylation that is programmed in one's genome during development can affect the way that individual will react to a diet as an adult, it might possibly affect the way immune-related genes are expressed during infections.
		+
		+	Very recently the work of Guihot et al. (2014) demonstrated some curious cases that impose more questions than answers. The authors have found biological markers that can predict whether an individual is more prone to suffer lethal consequences to influenza infection. However, the genetic variability that underlies such markers is not well understood – e.g., some of the markers indicated a "trapping" antibodies in the lungs for the lethal cases, whilst the survivors had the antibodies freed into a blood. In another recent study Worobey et al. (2014) have hypothesized that the high mortality during the 1918 Spanish flu pandemic among adults aged ~20 to ~40 years might have been due primarily to their childhood exposure to a heterosubtypic putative H3N8 virus – estimated as to have been circulating from ~1889–1900. All other age groups (except immunologically naive infants) were likely to be partially protected by childhood exposure to N1 and/or H1-related antigens. Such tenet poses immediate questions. What possible immunological mechanism[s] already described, might explain such an increase of mortality rates? Especially a mechanism of contrasting the H3 non-naïve young-adult Spanish flu victims (but putatively naïve towards H1 serotype), with infants – by definition naïve to all HA subtypes. In effect such a mechanism would require a convincingly plausible pathway[s] of suppressing immunity specifically by an action of H3-derived epitopes. One possible mechanism would be that the exposure to this putative H3N8 virus could have caused a methylation pattern in some genes, especially on some paths of immune response, and as consequence these patients had an extremely severe flu. Also, maybe not all individuals exposed to this virus developed the same methylation patterns and final supressions due to the genetic variability known to exist in human populations. The authors postulate that a mechanism akin to original antigenic sin (OAS, Francis T, 1960) may have interfered with immune responses in some of those infected in 1918, and peaked in those exposed previously to the 1889 virus. However, such hypothesis opens important questions about possible molecular and immunological mechanisms pertaining to the actual OAS phenomena “in action”. It is obvious that many more studies of this type will be necessary to better understand how the environment and host genetic variability affects the susceptibility to the influenza-A virus. The present review shows that both host genetic variability as well as environment are clearly factors of great importance to determine such susceptibility. (more: http://www.actabp.pl/#File?./html/3_2014/403.html) <br>
		+

	<!--[[Genetic:isscor \| '''More..''']]-->		<!--[[Genetic:isscor \| '''More..''']]-->