Gene–environment interaction

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Gene%E2%80%93environment_interaction 

Gene–environment interaction (or genotype–environment interaction or GxE or G×E) is when two different genotypes respond to environmental variation in different ways. A norm of reaction is a graph that shows the relationship between genes and environmental factors when phenotypic differences are continuous. They can help illustrate GxE interactions. When the norm of reaction is not parallel, as shown in the figure below, there is a gene by environment interaction. This indicates that each genotype responds to environmental variation in a different way. Environmental variation can be physical, chemical, biological, behavior patterns or life events.

This norm of reaction shows lines that are not parallel indicating a gene by environment interaction. Each genotype is responding to environmental variation in a different way.

Gene–environment interactions are studied to gain a better understanding of various phenomena. In genetic epidemiology, gene–environment interactions are useful for understanding some diseases. Sometimes, sensitivity to environmental risk factors for a disease are inherited rather than the disease itself being inherited. Individuals with different genotypes are affected differently by exposure to the same environmental factors, and thus gene–environment interactions can result in different disease phenotypes. For example, sunlight exposure has a stronger influence on skin cancer risk in fair-skinned humans than in individuals with darker skin.

These interactions are of particular interest to genetic epidemiologists for predicting disease rates and methods of prevention with respect to public health. The term is also used amongst developmental psychobiologists to better understand individual and evolutionary development.

Nature versus nurture debates assume that variation in a trait is primarily due to either genetic differences or environmental differences. However, the current scientific opinion holds that neither genetic differences nor environmental differences are solely responsible for producing phenotypic variation, and that virtually all traits are influenced by both genetic and environmental differences.

Statistical analysis of the genetic and environmental differences contributing to the phenotype would have to be used to confirm these as gene–environment interactions. In developmental genetics, a causal interaction is enough to confirm gene–environment interactions.

History of the definition

The history of defining gene–environment interaction dates back to the 1930s and remains a topic of debate today. The first instance of debate occurred between Ronald Fisher and Lancelot Hogben. Fisher sought to eliminate interaction from statistical studies as it was a phenomenon that could be removed using a variation in scale. Hogben believed that the interaction should be investigated instead of eliminated as it provided information on the causation of certain elements of development.

A similar argument faced multiple scientists in the 1970s. Arthur Jensen published the study “How much can we boost IQ and scholastic achievement?”, which amongst much criticism also faced contention by scientists Richard Lewontin and David Layzer. Lewontin and Layzer argued that in order to conclude causal mechanisms, the gene–environment interaction could not be ignored in the context of the study while Jensen defended that interaction was purely a statistical phenomenon and not related to development.

Around the same time, Kenneth J. Rothman supported the use of a statistical definition for interaction while researchers Kupper and Hogan believed the definition and existence of interaction was dependent on the model being used.

The most recent criticisms were spurred by Moffitt and Caspi's studies on 5-HTTLPR and stress and its influence on depression. In contrast to previous debates, Moffitt and Caspi were now using the statistical analysis to prove that interaction existed and could be used to uncover the mechanisms of a vulnerability trait. Contention came from Zammit, Owen and Lewis who reiterated the concerns of Fisher in that the statistical effect was not related to the developmental process and would not be replicable with a difference of scale.

Definitions

There are two different conceptions of gene–environment interaction today. Tabery has labeled them biometric and developmental interaction, while Sesardic uses the terms statistical and commonsense interaction.

The biometric (or statistical) conception has its origins in research programs that seek to measure the relative proportions of genetic and environmental contributions to phenotypic variation within populations. Biometric gene–environment interaction has particular currency in population genetics and behavioral genetics. Any interaction results in the breakdown of the additivity of the main effects of heredity and environment, but whether such interaction is present in particular settings is an empirical question. Biometric interaction is relevant in the context of research on individual differences rather than in the context of the development of a particular organism.

Developmental gene–environment interaction is a concept more commonly used by developmental geneticists and developmental psychobiologists. Developmental interaction is not seen merely as a statistical phenomenon. Whether statistical interaction is present or not, developmental interaction is in any case manifested in the causal interaction of genes and environments in producing an individual's phenotype.

Epidemiological models of GxE

In epidemiology, the following models can be used to group the different interactions between gene and environment.

Model A describes a genotype that increases the level of expression of a risk factor but does not cause the disease itself. For example, the PKU gene results in higher levels of phenylalanine than normal which in turn causes mental retardation.

The risk factor in Model B in contrast has a direct effect on disease susceptibility which is amplified by the genetic susceptibility. Model C depicts the inverse, where the genetic susceptibility directly effects disease while the risk factor amplifies this effect. In each independent situation, the factor directly effecting the disease can cause disease by itself.

Model D differs as neither factor in this situation can effect disease risk, however, when both genetic susceptibility and risk factor are present the risk is increased. For example, the G6PD deficiency gene when combined with fava bean consumption results in hemolytic anemia. This disease does not arise in individuals that eat fava beans and lack G6PD deficiency nor in G6PD-deficient people who do not eat fava beans.

Lastly, Model E depicts a scenario where the environmental risk factor and genetic susceptibility can individually both influence disease risk. When combined, however, the effect on disease risk differs.

The models are limited by the fact that the variables are binary and so do not consider polygenic or continuous scale variable scenarios.

Methods of analysis

Traditional genetic designs

Adoption studies

Adoption studies have been used to investigate how similar individuals that have been adopted are to their biological parents with whom they did not share the same environment with. Additionally, adopted individuals are compared to their adoptive family due to the difference in genes but shared environment. For example, an adoption study showed that Swedish men with disadvantaged adoptive environments and a genetic predisposition were more likely to abuse alcohol.

Twin studies

Using monozygotic twins, the effects of different environments on identical genotypes could be observed. Later studies leverage biometrical modelling techniques to include the comparisons of dizygotic twins to ultimately determine the different levels of gene expression in different environments.

Family studies

Family-based research focuses on the comparison of low-risk controls to high risk children to determine the environmental effect on subjects with different levels of genetic risk. For example, a Danish study on high-risk children with schizophrenic mothers depicted that children without a stable caregiver were associated with an increased risk of schizophrenia.

Molecular analyses

Interaction with single genes

The often used method to detect gene–environment interactions is by studying the effect a single gene variation has with respect to a particular environment. Single nucleotide polymorphisms (SNP's) are compared with single binary exposure factors to determine any effects.

Candidate studies such as these require strong biological hypotheses which are currently difficult to select given the little understanding of biological mechanisms that lead to higher risk.

These studies are also often difficult to replicate commonly due to small sample sizes which typically results in disputed results.

The polygenic nature of complex phenotypes suggests single candidate studies could be ineffective in determining the various smaller scale effects from the large number of influencing gene variants.

Interaction with multiple genes

Since the same environmental factor could interact with multiple genes, a polygenic approach can be taken to analyze GxE interactions. A polygenic score is generated using the alleles associated with a trait and their respective weights based on effect and examined in combination with environmental exposure. Though this method of research is still early, it is consistent with psychiatric disorders. As a result of the overlap of endophenotypes amongst disorders this suggests that the outcomes of gene–environment interactions are applicable across various diagnoses.

Genome-wide association studies and genome wide interaction studies

A genome wide interaction scan (GEWIS) approach examines the interaction between the environment and a large number of independent SNP's. An effective approach to this all-encompassing study occurs in two-steps where the genome is first filtered using gene-level tests and pathway based gene set analyses. The second step uses the SNP's with G–E association and tests for interaction.

The differential susceptibility hypothesis has been reaffirmed through genome wide approaches.

Controversies

Lack of replication

A particular concern with gene–environment interaction studies is the lack of reproducibility. Specifically complex traits studies have come under scrutiny for producing results that cannot be replicated. For example, studies of the 5-HTTLPR gene and stress resulting in modified risk of depression have had conflicting results.

A possible explanation behind the inconsistent results is the heavy use of multiple testing. Studies are suggested to produce inaccurate results due to the investigation of multiple phenotypes and environmental factors in individual experiments.

Additive vs multiplicative model

There are two different models for the scale of measurement that helps determine if gene–environment interaction exists in a statistical context. There is disagreement on which scale should be used. Under these analyses, if the combined variables fit either model then there is no interaction. The combined effects must either be greater for synergistic or less than for an antagonistic outcome. The additive model measures risk differences while the multiplicative model uses ratios to measure effects. The additive model has been suggested to be a better fit for predicting disease risk in a population while a multiplicative model is more appropriate for disease etiology.

Epigenetics is an example of an underlying mechanism of gene–environment effects, however, it does not conclude whether environment effects are additive, multiplicative or interactive.

Gene "×" environment "×" environment interactions

New studies have also revealed the interactive effect of multiple environment factors. For example, a child with a poor quality environment would be more sensitive to a poor environment as an adult which ultimately led to higher psychological distress scores. This depicts a three way interaction Gene x Environment x Environment. The same study suggests taking a life course approach to determining genetic sensitivity to environmental influences within the scope of mental illnesses.

Medical significance

Doctors are interested in knowing whether disease can be prevented by reducing exposure to environmental risks. Some people carry genetic factors that confer susceptibility or resistance to a certain disorder in a particular environment. The interaction between the genetic factors and environmental stimulus is what results in the disease phenotype. There may be significant public health benefits in using gene by environment interactions to prevent or cure disease.

An individual's response to a drug can result from various gene by environment interactions. Therefore, the clinical importance of pharmacogenetics and gene by environment interactions comes from the possibility that genomic, along with environmental information, will allow more accurate predictions of an individual's drug response. This would allow doctors to more precisely select a certain drug and dosage to achieve therapeutic response in a patient while minimizing side effects and adverse drug reactions. This information could also help to prevent the health care costs associated with adverse drug reactions and inconveniently prescribing drugs to patients who likely won't respond to them.

In a similar manner, an individual can respond to other environmental stimuli, factors or challenges differently according to specific genetic differences or alleles. These other factors include the diet and specific nutrients within the diet, physical activity, alcohol and tobacco use, sleep (bed time, duration), and any of a number of exposures, including toxins, pollutants, sunlight (latitude north–south of the equator), among any number of others. The diet, for example, is modifiable and has significant impact on a host of cardiometabolic diseases, including cardiovascular disease, coronary artery disease, coronary heart disease, type 2 diabetes, hypertension, stroke, myocardial infarction, and non-alcoholic fatty liver disease. In the clinic, typically assessed risks of these conditions include blood lipids (triglyceride, and HDL, LDL and total cholesterol), glycemic traits (plasma glucose and insulin, HOMA-IR, beta cell function as HOMA-BC), obesity anthropometrics (BMI/obesity, adiposity, body weight, waist circumference, waist-to-hip ratio), vascular measures (diastolic and systolic blood pressure), and biomarkers of inflammation. Gene–environment interactions can modulate the adverse effects of an allele that confers increased risk of disease, or can exacerbate the genotype–phenotype relationship and increase risk, in a manner often referred to as nutrigenetics. A catalog of genetic variants that associate with these and related cardiometabolic phenotypes and modified by common environmental factors is available.

Conversely, a disease study using breast cancer, type 2 diabetes, and rheumatoid arthritis shows that including GxE interactions in a risk prediction model does not improve risk identification.

Examples

Mean bristle number by °C

1. In Drosophila: A classic example of gene–environment interaction was performed on Drosophila by Gupta and Lewontin in 1981. In their experiment they demonstrated that the mean bristle number on Drosophila could vary with changing temperatures. As seen in the graph to the right, different genotypes reacted differently to the changing environment. Each line represents a given genotype, and the slope of the line reflects the changing phenotype (bristle number) with changing temperature. Some individuals had an increase in bristle number with increasing temperature while others had a sharp decrease in bristle number with increasing temperature. This showed that the norms of reaction were not parallel for these flies, proving that gene–environment interactions exist.
2. In plants: One very interesting approach about genotype by environment interaction strategies is its use in the selection of sugarcane cultivars adapted to different environments. In this article, they analyzed twenty sugarcane genotypes grown in eight different locations over two crop cycles to identify mega-environments related to higher cane yield, measured in tons of cane per hectare (TCH) and percentage of sucrose (Pol% cane) using biplot multivariate GEI models. The authors then created a novel strategy to study both yield variables in a two-way coupled strategy even though the results showed a mean negative correlation. Through coinertia analysis, it was possible to determine the best-fitted genotypes for both yield variables in all environments. The use of these novel strategies like coinertia in GEI, proved to be a great complement analysis to AMMI and GGE, especially when the yield improvement implies multiple yield variables. Seven genetically distinct yarrow plants were collected and three cuttings taken from each plant. One cutting of each genotype was planted at low, medium, and high elevations, respectively. When the plants matured, no one genotype grew best at all altitudes, and at each altitude the seven genotypes fared differently. For example, one genotype grew the tallest at the medium elevation but attained only middling height at the other two elevations. The best growers at low and high elevation grew poorly at medium elevation. The medium altitude produced the worst overall results, but still yielded one tall and two medium-tall samples. Altitude had an effect on each genotype, but not to the same degree nor in the same way. A sorghum bi-parental population was repeatedly grown in seven diverse geographic locations across years. A group of genotypes requires similar growing degree-day (GDD) to flower across all environments, while another group of genotypes need less GDD in certain environments, but higher GDD in different environments to flower. The complex flowering time patterns is attributed to the interaction of major flowering time genes (Ma₁, Ma₆, FT, ELF3) and an explicit environmental factor, photothermal time (PTT) capturing the interaction between temperature and photoperiod.
3. Phenylketonuria (PKU) is a human genetic condition caused by mutations to a gene coding for a particular liver enzyme. In the absence of this enzyme, an amino acid known as phenylalanine does not get converted into the next amino acid in a biochemical pathway, and therefore too much phenylalanine passes into the blood and other tissues. This disturbs brain development leading to mental retardation and other problems. PKU affects approximately 1 out of every 15,000 infants in the U.S. However, most affected infants do not grow up impaired because of a standard screening program used in the U.S. and other industrialized societies. Newborns found to have high levels of phenylalanine in their blood can be put on a special, phenylalanine-free diet. If they are put on this diet right away and stay on it, these children avoid the severe effects of PKU. This example shows that a change in environment (lowering Phenylalanine consumption) can affect the phenotype of a particular trait, demonstrating a gene–environment interaction.
4. A single nucleotide polymorphism rs1800566 in NAD(P)H Quinone Dehydrogenase 1 (NQO1) alters the risk of asthma and general lung injury upon interaction with NOx pollutants, in individuals with this mutation.
5. A functional polymorphism in the monoamine oxidase A (MAOA) gene promoter can moderate the association between early life trauma and increased risk for violence and antisocial behavior. Low MAOA activity is a significant risk factor for aggressive and antisocial behavior in adults who report victimization as children. Persons who were abused as children but have a genotype conferring high levels of MAOA expression are less likely to develop symptoms of antisocial behavior. These findings must be interpreted with caution, however, because gene association studies on complex traits are notorious for being very difficult to confirm.
6. In Drosophila eggs:
   

Egg Development Time by Temperature

 

Contrary to the aforementioned examples, length of egg development in Drosophila as a function of temperature demonstrates the lack of gene–environment interactions. The attached graph shows parallel reaction norms for a variety of individual Drosophila flies, showing that there is not a gene–environment interaction present between the two variables. In other words, each genotype responds similarly to the changing environment producing similar phenotypes. For all individual genotypes, average egg development time decreases with increasing temperature. The environment is influencing each of the genotypes in the same predictable manner.

Cultural neuroscience

From Wikipedia, the free encyclopedia

Cultural neuroscience is a field of research that focuses on the interrelation between a human’s cultural environment and neurobiological systems. The field particularly incorporates ideas and perspectives from related domains like anthropology, psychology, and cognitive neuroscience to study sociocultural influences on human behaviors. Such impacts on behavior are often measured using various neuroimaging methods, through which cross-cultural variability in neural activity can be examined.

Cultural neuroscientists study cultural variation in mental, neural and genomic processes as a means of articulating the bidirectional relationship of these processes and their emergent properties using a variety of methods. Researchers in cultural neuroscience are motivated by two fundamentally intriguing, yet still unanswered, questions on the origins of human nature and human diversity: how do cultural traits (e.g., values, beliefs, practices) shape neurobiology (e.g., genetic and neural processes) and behavior, and how do neurobiological mechanisms (e.g., genetic and neural processes) facilitate the emergence and transmission of cultural traits?

The idea that complex behavior results from the dynamic interaction of genes and cultural environment is not new; however, cultural neuroscience represents a novel empirical approach to demonstrating bidirectional interactions between culture and biology by integrating theory and methods from cultural psychology, neuroscience and neurogenetics.

Similar to other interdisciplinary fields such as social neuroscience, cognitive neuroscience, affective neuroscience, and neuroanthropology, cultural neuroscience aims to explain a given mental phenomenon in terms of a synergistic product of mental, neural and genetic events. In particular, cultural neuroscience shares common research goals with social neuroscientists examining how neurobiological mechanisms (e.g., mirror neurons), facilitate cultural transmission, (e.g., imitative learning) and neuroanthropologists examining how embedded culture, as captured by cross-species comparison and ethnography, is related to brain function. Cultural neuroscience also shares intellectual goals with critical neuroscience, a field of inquiry that scrutinizes the social, cultural, economic and political contexts and assumptions that underlie behavioral and brain science research as it is practiced today.

Research in cultural neuroscience has practical relevance to transcultural psychiatry, business and technology as well as broader implications for global public policy issues such as population health disparities, bioethics, globalization, immigration, interethnic ideology and international relations.

Previous cross-cultural research

While the field of cultural neuroscience may still be growing, there are studies conducted by various researchers that have looked at cross-cultural similarities and differences in human attention, visual perception, and the understanding of others and the self. Previous behavioral research has focused on the cultural differences in perception, particularly between people from East Asian and Western regions. The results from these studies have suggested that East Asians focus their visual perception more on the backgrounds and contexts of their environment, while Westerners focus on individual stimuli/objects. To further explore these findings, more research was done to specifically look at the neurological similarities and differences in attention and visual perception of people in East Asian and Western cultures. 

Results from a 2008 study by Hedden et al. support the previous findings by showing how East Asians require more attention than Americans for individually processing objects. Brain regions more focused on attention, such as areas in the parietal and prefrontal lobes as well as the inferior parietal lobule and precentral gyrus, were found to be highly active in East Asian subjects compared to American subjects, during individual object processing. A visual perception study conducted by Gutchess et al. in 2006, also found neurological differences between Chinese and American subjects as they completed tasks of encoding images of individual objects, backgrounds, and objects with backgrounds. The fMRI results from the study presented that during visual processing of objects, there was greater neural activity in the middle temporal gyri, right superior temporal gyri, and superior parietal lobules of the American subjects than that of the Chinese subjects. Such results indicate a focus on object processing among Westerners compared to East Asians. Insignificant differences in neural activity between subjects were found during the visual processing of images with backgrounds.

People from East Asian and Western cultures were also studied to learn more about cross-cultural differences in understanding both the self and other people. Findings from a 1991 study by Markus and Kitayama presented that people from Eastern cultures view the self in relation to others in their community, while people from Western cultures have a more independent perspective of the self. A 2007 fMRI study observed differences in activity in the ventromedial prefrontal cortex, a brain region highly active during self perception, when Western and Chinese subjects were thinking about themselves versus when they were thinking about their mothers. The results interestingly showed that there was still activity in the ventral medial prefrontal cortices of Chinese subjects even when they thought about their mothers, while activity was only detected in American subjects when they thought about themselves. 

A different study conducted by psychologist Joan Chiao found that due to cultural differences, East Asians are more likely to suffer from depression than Americans. She found that East Asians are more likely to carry the short allele of the serotonin transporter gene (STG) which leads to depression while Americans carry the long allele which doesn't lead to depression. Yet due to difference in cultural structure they found that collectivist societies are more likely to find happiness than individual societies.

Another study done by psychologists Nalini Ambady and Jonathan Freeman showed a difference in brain activity between Japanese and Americans when shown different body posture. They found that the reward circuitry in the limbic system would light up when Japanese participants saw submissive body posture while the reward circuitry would activate when Americans saw dominant body posture.

Culture differences in visual stimuli

Cultural differences exist in the ventral visual cortex and many studies have shown this. In a study conducted in 2005 they found that East Asians were more likely to keep their eyes focused on background scenes than westerners who would instead focus more on the central object such as a giraffe in a savanna. In a similar 2006 study it showed that in congruence to the difference in society structure westerners showed more activation in object processing regions, including the bilateral middle temporal gyrus, left superior parietal gyrus, and right superior temporal gyrus, although no activation differences were observed in context-processing regions such as the hippocampus. However, there has been some research contradicting cultural bias in the oculomotor control such as one conducted in 2007 by Rayner, Li, Williams, Cave, and well who failed to find evidence that East Asians focus more on context although they did find evidence that they are more likely to focus less on central objects. In a different study they focused more on difference in attention towards faces. They proved that Americans focus more broadly on the entire face such as both the eyes and mouth while Asians focus more on a single part, such as the mouth. The authors point out that this happens due to gaze avoidance in east Asian culture as a way of politeness. In 2008, another study focusing on context showed that East Asians were more likely to include greater details and background when taking photographs of a model when they were free to set the zoom function of the camera as they saw fit. In 2003, a group of researchers used the Frame-Line Test and asked the participants to draw a line of either exactly the same length as the one showed or one that was proportional in size. Americans were more accurate in the absolute task, suggesting better memory for the exact or absolute size of the focal object, but East Asians were more accurate in the relative (proportional) task, suggesting better memory for contextual relationships. In a later study conducted by the same group they found a pattern within the cultures when processing emotions. East Asians were less likely to know the difference between fear and disgust than Americans when sampling faces.

Many studies conducted proves that constant repetition in a certain skill has an effect on brain activity. For example, in a 2000 study they showed that taxi drivers in London showed larger gray matter in the posterior hippocampi than the average civilian. A different study in 2004 showed that those who know how to juggle have an increase in volume of the cortical tissue in the bilateral midtemporal area and left posterior intraparietal sulcus.

The findings from many neuroimaging studies reflect the behavioral patterns observed in previous anthropological and cultural research. Such comparisons that were made between particular behavioral and neural activity across different cultures, have already provided the scientific community with more insight into the cultural influences on human behavior.

Sensory processing sensitivity

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Sensory_processing_sensitivity 

 

Characteristics of SPS as graphically summarized by Greven et al. (review article, 2019) A person with a high measure of SPS is said to be a highly sensitive person (HSP).

 

Sensory processing sensitivity (SPS) is a temperamental or personality trait involving "an increased sensitivity of the central nervous system and a deeper cognitive processing of physical, social and emotional stimuli". The trait is characterized by "a tendency to 'pause to check' in novel situations, greater sensitivity to subtle stimuli, and the engagement of deeper cognitive processing strategies for employing coping actions, all of which is driven by heightened emotional reactivity, both positive and negative".

A human with a particularly high measure of SPS is considered to have 'hypersensitivity', or be a highly sensitive person (HSP). The terms SPS and HSP were coined in the mid-1990s by psychologists Elaine Aron and her husband Arthur Aron, who developed the Highly Sensitive Person Scale (HSPS) questionnaire by which SPS is measured. Other researchers have applied various other terms to denote this responsiveness to stimuli that is seen in humans and other species.

According to the Arons and colleagues, people with high SPS make up about 15–20% of the population. Although some researchers consistently related high SPS to negative outcomes, other researchers have associated it with increased responsiveness to both positive and negative influences. Aron and colleagues state that the high-SPS personality trait is not a disorder.

Origin and development of the terms

Elaine Aron's book The Highly Sensitive Person was published in 1996. In 1997 Elaine and Arthur Aron formally identified sensory processing sensitivity (SPS) as the defining trait of highly sensitive persons (HSPs). The popular terms hypersensitivity (not to be confused with the medical term hypersensitivity) or highly sensitive are popular synonyms for the scientific concept of SPS. By way of definition, Aron and Aron (1997) wrote that sensory processing here refers not to the sense organs themselves, but to what occurs as sensory information is transmitted to or processed in the brain. They assert that the trait is not a disorder but an innate survival strategy that has both advantages and disadvantages.

Elaine Aron's academic journal articles as well as self-help publications for the lay reader have focused on distinguishing high SPS from socially reticent behavior and disorders with which high SPS can be confused; overcoming the social unacceptability that can cause low self-esteem; and emphasizing the advantages of high SPS to balance the disadvantages emphasized by others.

In 2015, sociologist Elizabeth Bernstein wrote in The Wall Street Journal that HSPs were "having a moment," noting that several hundred research studies had been conducted on topics related to HSPs' high sensitivity. The First International Scientific Conference on High Sensitivity or Sensory Processing Sensitivity was held at the Vrije Universiteit Brussel. By 2015, more than a million copies of The Highly Sensitive Person had been sold.

Earlier research

Research pre-dating the Arons' coining of the term "high sensitivity" includes that of German medicine professor Wolfgang Klages, who argued in the 1970s that the phenomenon of sensitive and highly sensitive humans is "biologically anchored" and that the "stimulus threshold of the thalamus" is much lower in these persons. As a result, said Klages, there is a higher permeability for incoming signals from afferent nerve fibers so that they pass "unfiltered" to the cerebral cortex.

The Arons (1997) recognized psychologist Albert Mehrabian's (1976, 1980, 1991) concept of filtering the "irrelevant", but wrote that the concept implied that the inability of HSPs' (Mehrabian's "low screeners") to filter out what is irrelevant would imply that what is relevant is determined from the perspective of non-HSPs ("high screeners").

Attributes, characteristics and prevalence

Boterberg et al. (2016) describe high SPS as a "temperamental or personality trait which is present in some individuals and reflects an increased sensitivity of the central nervous system and a deeper cognitive processing of physical, social and emotional stimuli".

People with high SPS report having a heightened response to stimuli such as pain, caffeine, hunger, and loud noises. According to Boterberg et al., these individuals are "believed to be easily overstimulated by external stimuli because they have a lower perceptual threshold and process stimuli cognitively deeper than most other people." This deeper processing may result in increased reaction time as more time is spent responding to cues in the environment, and might also contribute to cautious behavior and low risk-taking.

The HSP Scale, initially (1997) a questionnaire designed to measure SPS on a unidimensional scale, was subsequently decomposed into two, three, or four factors or sub-scales. Most components have been associated with traditionally accepted negative psychological outcomes including high stress levels, being easily overwhelmed, increased rates of depression, anxiety, and sleep problems, as well as symptoms of autism; the diathesis-stress model focused on increased vulnerability to negative influences. However, the differential susceptibility theory (DST) and biological sensitivity to context theory (BSCT) and sensory processing sensitivity (SPS) suggest increased plasticity in terms of responsivenessp to both positive and negative influences; and the vantage sensitivity (VS) concept emphasizes increased responsiveness to positive experiences.Researchers such as Smolewska et al. (2006) said positive outcomes were more common in individuals with high aesthetic sensitivity, who tend to experience heightened positive emotions in response to rewarding stimuli and more likely to score high on "openness" on the Big Five factors model.

Research in evolutionary biology provides evidence that the trait of SPS can be observed, under various terms, in over 100 nonhuman species,Aron writing that the SPS trait is meant to encompass what personality psychologists have described under various other names. Conversely, Aron has distinguished SPS from what she considers it is not, explicitly distinguishing high SPS from possibly similar-appearing traits or disorders (such as shyness, sensation-seeking, sensory processing disorder, and autism), and further, that SPS may be a basic variable that may underlie multiple other trait differences (such as introversion versus extraversion). Contrary to common misconception, according to Aron HSPs include both introverts and extroverts, and may be simultaneously high-sensation seeking and cautious.

In humans and other species, responsive and unresponsive individuals coexist and consistently display different levels of responsiveness to environmental stimuli, the different levels of responsiveness having corresponding evolutionary costs and benefits. This observation parallels Aron's assertion that high SPS is not a disorder, but rather a personality trait with attendant advantages and disadvantages. Accordingly, Aron cautions medical professionals against prescribing psychoactive medications to "cure" the trait, which may or may not coexist with an actual disorder.

By 2015 the trait had been documented at various levels of study, including temperament and behavior psychology, brain function and neuronal sensitization, and genetics. For example, genetic studies provide evidence that higher levels of SPS are linked to the serotonin transporter 5-HTTLPR short/short genotype, polymorphisms in dopamine neurotransmitter genes, and the ADRA2b norepinephrine-related gene variant.

HSP Scale score patterns in adults were thought to be distributed as a dichotomous categorical variable with a break point between 10% and 35%, with Aron choosing a cut-off of the highest-scoring 20% of individuals to define the HSP category. A 2019 review article stated that findings suggest people fall into three sensitivity groups along a normal distribution sensitivity continuum.

Sensory processing disorder

From Wikipedia, the free encyclopedia

An SPD nosology proposed by Miller LJ et al. (2007)

 

Sensory processing disorder
Other names	Sensory integration dysfunction
Specialty	Psychiatry Occupational therapy Neurology
Symptoms	Hyper sensitivity and hypo sensitivity to stimuli, and/or difficulties using sensory information to plan movement. Problems discriminating characteristics of stimuli.
Complications	Low school performance, behavioral difficulties, social isolation, employment problems, family and personal stress,
Usual onset	Uncertain
Risk factors	Anxiety, behavioral difficulties,
Diagnostic method	Based on symptoms
Differential diagnosis	Autism, ADHD,
Treatment	Occupational therapy

Sensory processing disorder (SPD; also known as sensory integration dysfunction) is a condition where multisensory integration is not adequately processed in order to provide appropriate responses to the demands of the environment. Sensory processing disorder is present in almost all people with autism spectrum disorders.

Sensory integration was defined by occupational therapist Anna Jean Ayres in 1972 as "the neurological process that organizes sensation from one's own body and from the environment and makes it possible to use the body effectively within the environment". Sensory processing disorder has been characterized as the source of significant problems in organizing sensation coming from the body and the environment and is manifested by difficulties in the performance in one or more of the main areas of life: productivity, leisure and play or activities of daily living.

Sources debate whether SPD is an independent disorder or represents the observed symptoms of various other, more well-established, disorders. SPD is not recognized by the Diagnostic and Statistical Manual of the American Psychiatric Association, and the American Academy of Pediatrics has recommended that pediatricians not use SPD as a stand alone diagnosis.

Signs and symptoms

Sensory processing disorder (SPD) is characterized by persistent challenges with neurological processing of sensory stimuli. Such challenges can appear in one or several sensory systems: Somatosensory system, Vestibular system, Propioceptive system, Interoceptive system, Auditory system, Visual system, Olfactory system, and Gustatory system.

 

While many people can present one or two symptoms, sensory processing disorder has to have a clear functional impact on the person's life:

Signs of over-responsivity, including, for example, dislike of textures such as those found in fabrics, foods, grooming products or other materials found in daily living, to which most people would not react, and serious discomfort, sickness or threat induced by normal sounds, lights, movements, smells, tastes, or even inner sensations such as heartbeat.

Signs of under-responsivity, including sluggishness and lack of responsiveness; and Sensory cravings, including, for example, fidgeting, impulsiveness, and/or seeking or making loud, disturbing noises; Sensorimotor-based problems, including slow and uncoordinated movements or poor handwriting.

Sensory discrimination problems, that might manifest themselves in behaviors such as things constantly dropped.

Symptoms may vary according to the disorder's type and subtype present.

Relationship to other disorders

Sensory processing issues represent a feature of a number of disorders, including anxiety problems, ADHD, food intolerances, behavioral disorders, and particularly, autism spectrum disorders. This pattern of comorbidities poses a significant challenge to those who claim that SPD is an identifiably specific disorder, rather than simply a term given to a set of symptoms common to other disorders.

Two studies have provided preliminary evidence suggesting that there may be measurable neurological differences between children diagnosed with SPD and control children classified as neurotypical or children diagnosed with autism. Despite this evidence, the fact that SPD researchers have yet to agree on a proven, standardized diagnostic tool undermines researchers' ability to define the boundaries of the disease and makes correlational studies, like those on structural brain abnormalities, less convincing.

Causes

The exact cause of SPD is not known. However, it is known that the midbrain and brainstem regions of the central nervous system are early centers in the processing pathway for multisensory integration; these brain regions are involved in processes including coordination, attention, arousal, and autonomic function. After sensory information passes through these centers, it is then routed to brain regions responsible for emotions, memory, and higher level cognitive functions. Damage in any part of the brain involved in multisensory processing can cause difficulties in adequately processing stimuli in a functional way.

Mechanism

Current research in sensory processing is focused on finding the genetic and neurological causes of SPD. EEG, measuring event-related potential (ERP) and magnetoencephalography (MEG) are traditionally used to explore the causes behind the behaviors observed in SPD.

Differences in tactile and auditory overresponsivity show moderate genetic influences, with tactile overresponsivity demonstrating greater heritability. Differences in auditory latency (the time between the input is received and when reaction is observed in the brain), hypersensitivity to vibration in the Pacinian corpuscles receptor pathways and other alterations in unimodal and multisensory processing have been detected in autism populations.

People with sensory processing deficits appear to have less sensory gating than typical subjects, and atypical neural integration of sensory input. In people with sensory over responsivity different neural generators activation, causing the automatic association of causally related sensory inputs that occurs at this early sensory-perceptual stage to not function properly. People suffering from sensory over-responsivity might have increased D2 receptor in the striatum, related to aversion to tactile stimuli and reduced habituation. In animal models, prenatal stress significantly increased tactile avoidance.

Recent research has also found an abnormal white matter microstructure in children with SPD, compared with typical children and those with other developmental disorders such as autism and ADHD.

One hypothesis is that multisensory stimulation may activate a higher-level system in the frontal cortex that involves attention and cognitive processing, rather than the automatic integration of multisensory stimuli observed in typically developing adults in the auditory cortex.

Diagnosis

Sensory processing disorder is accepted in the Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood (DC:0-3R). It is not recognized as a mental disorder in medical manuals such as the ICD-10 or the DSM-5.

Diagnosis is primarily arrived at by the use of standardized tests, standardized questionnaires, expert observational scales, and free-play observation at an occupational therapy gym. Observation of functional activities might be carried at school and home as well.

Though diagnosis in most of the world is done by an occupational therapist, in some countries diagnosis is made by certified professionals, such as psychologists, learning specialists, physiotherapists and/or speech and language therapists. Some countries recommend to have a full psychological and neurological evaluation if symptoms are too severe.

Standardized tests

• Sensory Integration and Praxis Test (SIPT)
• DeGangi-Berk Test of Sensory Integration (TSI)
• Test of Sensory Functions in Infants (TSFI)

Standardized questionnaires

• Sensory Profile, (SP)
• Infant/Toddler Sensory Profile
• Adolescent/Adult Sensory Profile
• Sensory Profile School Companion
• Indicators of Developmental Risk Signals (INDIPCD-R)
• Sensory Processing Measure (SPM)
• Sensory Processing Measure Preeschool (SPM-P)

Classification

Sensory processing disorders have been classified by proponents into three categories: sensory modulation disorder, sensory-based motor disorders and sensory discrimination disorders (as defined in the Diagnostic Classification of Mental Health and Developmental Disorders in Infancy and Early Childhood).

Sensory modulation disorder (SMD)

Sensory modulation refers to a complex central nervous system process by which neural messages that convey information about the intensity, frequency, duration, complexity, and novelty of sensory stimuli are adjusted.

SMD consists of three subtypes:

1. Sensory over-responsivity.
2. Sensory under-responsivity
3. Sensory craving/seeking.

Sensory-based motor disorder (SBMD)

According to proponents, sensory-based motor disorder shows motor output that is disorganized as a result of incorrect processing of sensory information affecting postural control challenges, resulting in postural disorder, or developmental coordination disorder.

The SBMD subtypes are:

1. Dyspraxia
2. Postural disorder

Sensory discrimination disorder (SDD)

Sensory discrimination disorder involves the incorrect processing of sensory information. The SDD subtypes are:

1. Visual 2. Auditory 3. Tactile 4. Gustatory (taste) 5. Olfactory (smell) 6. Vestibular (balance, head position and movement in space) 7. Proprioceptive (feeling of where parts of the body are located in space, muscle sensation) 8.Interoception (inner body sensations).

Treatment

Sensory integration therapy

Vestibular system is stimulated through hanging equipment such as tire swings

A type of occupational therapy that places a child in a room specifically designed to stimulate and challenge all of the senses while demanding functional behavior.

Sensory integration therapy is driven by four main principles:

• Just right challenge (the child must be able to successfully meet the challenges that are presented through playful activities)
• Adaptive response (the child adapts his behavior with new and useful strategies in response to the challenges presented)
• Active engagement (the child will want to participate because the activities are fun)
• Child directed (the child's preferences are used to initiate therapeutic experiences within the session)

Sensory processing therapy

This therapy retains all of the above-mentioned four principles and adds:

• Intensity (person attends therapy daily for a prolonged period of time)
• Developmental approach (therapist adapts to the developmental age of the person, against actual age)
• Test-retest systematic evaluation (all clients are evaluated before and after)
• Process driven vs. activity driven (therapist focuses on the "Just right" emotional connection and the process that reinforces the relationship)
• Parent education (parent education sessions are scheduled into the therapy process)
• "joie de vivre" (happiness of life is therapy's main goal, attained through social participation, self-regulation, and self-esteem)
• Combination of best practice interventions (is often accompanied by integrated listening system therapy, floor time, and electronic media such as Xbox Kinect, Nintendo Wii, Makoto II machine training and others)

While occupational therapists using a sensory integration frame of reference work on increasing a child's ability to adequately process sensory input, other OTs may focus on environmental accommodations that parents and school staff can use to enhance the child's function at home, school, and in the community. These may include selecting soft, tag-free clothing, avoiding fluorescent lighting, and providing ear plugs for "emergency" use (such as for fire drills).

Evaluation of treatment effectiveness

A 2019 review found sensory integration therapy to be effective for autism spectrum disorder. Another study from 2018 backs up the intervention for children with special needs, Additionally, the American Occupational Therapy Association supports the intervention.

In its overall review of the treatment effectiveness literature, AETNA concluded that "The effectiveness of these therapies is unproven.", while the American Academy of Pediatrics concluded that "parents should be informed that the amount of research regarding the effectiveness of sensory integration therapy is limited and inconclusive." A 2015 review concluded that SIT techniques exist "outside the bounds of established evidence-based practice" and that SIT is "quite possibly a misuse of limited resources."

Epidemiology

It has been estimated by proponents that up to 16.5% of elementary school aged children present elevated SOR behaviors in the tactile or auditory modalities. This figure is larger than what previous studies with smaller samples had shown: an estimate of 5–13% of elementary school aged children. Critics have noted that such a high incidence for just one of the subtypes of SPD raises questions about the degree to which SPD is a specific and clearly identifiable disorder.

Proponents have also claimed that adults may also show signs of sensory processing difficulties and would benefit for sensory processing therapies, although this work has yet to distinguish between those with SPD symptoms alone vs adults whose processing abnormalities are associated with other disorders, such as autism spectrum disorder.

Society

The American Occupational Therapy Association (AOTA) supports the use of a variety of methods of sensory integration for those with sensory processing disorder. The organization has supported the need for further research to increase insurance coverage for related therapies. They have also made efforts to educate the public about sensory integration therapy. The AOTA's practice guidelines currently support the use of sensory integration therapy and interprofessional education and collaboration in order to optimize treatment for those with sensory processing disorder. The AOTA provides several resources pertaining to sensory integration therapy, some of which includes a fact sheet, new research, and continuing education opportunities.

Controversy

There are concerns regarding the validity of the diagnosis. SPD is not included in the DSM-5 or ICD-10, the most widely used diagnostic sources in healthcare. The American Academy of Pediatrics (AAP) in 2012 statedd that there is no universally accepted framework for diagnosis and recommends caution against using any "sensory" type therapies unless as a part of a comprehensive treatment plan. The APP has plans to review its policy, though those efforts are still in the early stages.

A 2015 review of research on Sensory Integration Therapy (SIT) concluded that SIT is "ineffective and that its theoretical underpinnings and assessment practices are unvalidated", that SIT techniques exist "outside the bounds of established evidence-based practice", and that SIT is "quite possibly a misuse of limited resources".

Some sources point that sensory issues are an important concern, but not a diagnosis in themselves.

Critics have noted that what proponents claim are symptoms of SPD are both broad and, in some cases, represent very common, and not necessarily abnormal or atypical, childhood characteristics. Where these traits become grounds for a diagnosis is generally in combination with other more specific symptoms or when the child gets old enough to explain that the reasons behind their behavior are specifically sensory.

Manuals SPD is in Stanley Greenspan's Diagnostic Manual for Infancy and Early Childhood and as Regulation Disorders of Sensory Processing part of The Zero to Three's Diagnostic Classification.

Is not recognized as a stand alone diagnosis in the manuals ICD-10 or in the recently updated DSM-5 but, unusual reactivity to sensory input or unusual interest in sensory aspects is included as a possible but not necessary criterion for the diagnosis of autism.

History

Sensory processing disorder as a specific form of atypical functioning was first described by occupational therapist Anna Jean Ayres (1920–1989).

Original model

Ayres's theoretical framework for what she called Sensory Integration Dysfunction was developed after six factor analytic studies of populations of children with learning disabilities, perceptual motor disabilities and normal developing children. Ayres created the following nosology based on the patterns that appeared on her factor analysis:

• Dyspraxia: poor motor planning (more related to the vestibular system and proprioception)
• Poor bilateral integration: inadequate use of both sides of the body simultaneously
• Tactile defensiveness: negative reaction to tactile stimuli
• Visual perceptual deficits: poor form and space perception and visual motor functions
• Somatodyspraxia: poor motor planning (related to poor information coming from the tactile and proprioceptive systems)
• Auditory-language problems

Both visual perceptual and auditory language deficits were thought to possess a strong cognitive component and a weak relationship to underlying sensory processing deficits, so they are not considered central deficits in many models of sensory processing.

In 1998, Mulligan found a similar pattern of deficits in a confirmatory factor analytic study.

Quadrant model

Dunn's nosology uses two criteria: response type (passive vs active) and sensory threshold to the stimuli (low or high) creating 4 subtypes or quadrants:

• High neurological thresholds

1. Low registration: high threshold with passive response. Individuals who do not pick up on sensations and therefore partake in passive behavior.
2. Sensation seeking: high threshold and active response. Those who actively seek out a rich sensory filled environment.

• Low neurological threshold

1. Sensitivity to stimuli: low threshold with passive response. Individuals who become distracted and uncomfortable when exposed to sensation but do not actively limit or avoid exposure to the sensation.
2. Sensation avoiding: low threshold and active response. Individuals actively limit their exposure to sensations and are therefore high self regulators.

Sensory processing model

In Miller's nosology "sensory integration dysfunction" was renamed into "Sensory processing disorder" to facilitate coordinated research work with other fields such as neurology since "the use of the term sensory integration often applies to a neurophysiologic cellular process rather than a behavioral response to sensory input as connoted by Ayres."

The sensory processing model's nosology divides SPD in 3 subtypes: modulation, motor based and discrimination problems.