With the number of children diagnosed with autism on the rise, the need to find what causes the disorder becomes more urgent every day.
UCF researchers are now a step closer to showing the link between the food pregnant women consume and the effects on a fetus’ developing brain.
Drs. Saleh Naser, Latifa Abdelli and UCF undergraduate research assistant Aseela Samsam have identified the molecular changes that happen when neuro stem cells are exposed to high levels of an acid commonly found in processed foods.
In a study published June 19 in Scientific Reports, a Nature journal, the UCF scientists discovered how high levels of Propionic Acid (PPA), used to increase the shelf life of packaged foods and inhibit mold in commercially processed cheese and bread, reduce the development of neurons in fetal brains.
Dr. Naser, who specializes in gastroenterology research at the College of Medicine’s Burnett School of Biomedical Sciences, began the study after reports showed that autistic children often suffer from gastric issues such as irritable bowel syndrome.
“Studies have shown a higher level of PPA in stool samples from children with autism and the gut microbiome in autistic children is different,” Dr. Naser said. “I wanted to know what the underlying cause was.”
In the lab, the scientists found exposing neural stem cells to excessive PPA damages brain cells in several ways.
First, the acid disrupts the natural balance between brain cells by reducing the number of neurons and over-producing glial cells. While glial cells help develop and protect neuron function, too many glia cells disturb connectivity between neurons.
They also cause inflammation, which has been noted in the brains of autistic children.
Excessive amounts of the acid also shorten and damage pathways that neurons use to communicate with the rest of the body. The combination of reduced neurons and damaged pathways impede the brain’s ability to communicate, resulting in behaviors that are often found in children with autism, including repetitive behavior, mobility issues and inability to interact with others.
Previous studies have proposed links between autism and environmental and genetic factors, but Drs. Naser and Abdelli say their study is the first to discover the molecular link between elevated levels of PPA, proliferation of glial cells, disturbed neural circuitry and autism.
The 18-month study was self-funded by UCF.
PPA occurs naturally in the gut and a mother’s microbiome changes during pregnancy and can cause increases in the acid. But Drs. Naser and Abdelli said eating packaged foods containing the acid can further increase PPA in the woman’s gut, which then crosses to the fetus.
More research needs to be done before drawing clinical conclusions. Next, the research team will attempt to validate its findings in mice models by seeing if a high PPA maternal diet causes autism in mice genetically predisposed to the condition.
There is no cure for autism, which affects about 1 in 59 children, but the scientists hope their findings will advance studies for ways to prevent the disorder.
“This research is only the first step towards better understanding of Autism Spectrum Disorder,” the UCF scientists concluded. “But we have confidence we are on the right track to finally uncovering autism etiology.”
General intellectual functioning is described by the intelligence quotients (IQ), which refers to general cognitive capacity, such as learning ability, reasoning, and problem solving (DSM IV, 1994). The first stage of brain development begins 18 days after fertilisation and continues long after birth; however, the brain’s fastest growth occurs in utero, a vulnerable and critical period. Suboptimal nutrition during brain development may affect cognitive development and behavioural performance over time (Anjos et al., 2013; Rees & Inder, 2005; Thompson & Nelson, 2001).
During pregnancy, important neurologic functions are developing in the fetus (Rees & Inder, 2005). Brain development in the last trimester of gestation is particularly vulnerable to inadequacy in the mother’s diet (Anjos et al., 2013). Specific aspects of maternal diet have long‐term positive associations with offspring neurodevelopment, including cognitive, psychomotor and mental development, IQ scores (verbal, verbal‐executive function, and performance), effects on behavioural status, and others (Anjos et al., 2013; Hibbeln et al., 2007; Gil & Gil, 2015; Starling, Charlton, McMahon, & Lucas, 2015). Intakes of specific food items, such as fish, during pregnancy have shown positive associations with neurodevelopmental outcomes in childhood (Anjos et al., 2013; Gil & Gil, 2015; Starling et al., 2015).
The study of isolated nutrients or food groups is helpful but does not fully capture the impact of nutrient interactions and the net effect of inadequate nutrient intakes in complex combinations. The derivation of dietary patterns is considered an appropriate way to assess dietary intake, as this method allows the evaluation of a combination of different types of foods consumed simultaneously. They can summarise the usual dietary intake of population groups facilitating the assessment of the overall diet effect on particular outcomes (Hu, 2002; Newby & Tucker, 2004). Principal component analysis (PCA) and cluster analysis have both been used to assess diet. Although in PCA, all subjects are included in all dietary patterns, creating food groupings based on correlations of dietary intake; in cluster analysis, individuals are classified into mutually exclusive and nonoverlapping clusters of subjects who consume similar foods (Bailey et al., 2006; Devlin, McNulty, Nugent, & Gibney, 2012; Hu, 2002; Newby & Tucker, 2004; Smith, Emmett, Newby, & Northstone, 2011; Wirfält, Drake, & Wallström, 2013). The ability of cluster analysis to aggregate subjects into exclusive groups aids interpretation of the relationship between the pattern and the outcome of interest (Devlin et al., 2012; Newby & Tucker, 2004) and is particularly helpful in longitudinal analysis. Other methods of assessing whole diet such as reduced rank regression and predefined dietary scores require prior reasonably robust evidence of the relationship between diet and the outcome being studied, which is not available in this case (Hoffmann, Schulze, Schienkiewitz, Nothlings, & Boeing, 2004).
Despite its ability to add insight into the relationship between diet and pregnancy outcomes, there are currently very few studies, which have used cluster analysis to derive dietary patterns during pregnancy (Vilela et al., 2016). Therefore, this study will use it to obtain dietary patterns in pregnancy in the Avon Longitudinal Study of Parents and Children (ALSPAC), which has not been done before (Emmett, Jones, & Northstone, 2015).
Studies have examined cross‐sectional associations between dietary patterns and cognitive outcomes, in childhood, in adolescence, and in the elderly (Gale et al., 2009; Kim et al., 2015; Leventakou et al., 2016; Northstone, Joinson, Emmett, Ness, & Paus, 2012; Nyaradi et al., 2014). These studies have generally shown that higher scores on dietary patterns characterised by healthy foods (such as fruits, vegetables, and fish), measured in these stages of life, are associated with better cognitive outcomes, including higher childhood IQ. In addition, higher scores on unhealthy dietary patterns are generally associated with poorer cognitive outcomes in childhood and adolescence (Gale et al., 2009; Kim et al., 2015; Leventakou et al., 2016; Northstone et al., 2012; Nyaradi et al., 2014; Smithers et al., 2012; Smithers et al., 2013).
These studies highlight the importance of dietary intake at several stages of life. Maternal dietary intakes are clearly a dominant determinant of fetal nutrition in utero. However, the effects of maternal dietary patterns, obtained by cluster analysis or PCA, during pregnancy on neurodevelopmental outcomes in childhood are unknown. Therefore, the purpose of this study was to investigate the associations between maternal dietary patterns obtained by cluster analysis during pregnancy and IQ evaluated among offspring at 8 years of age.
- The children of women in “fruit and vegetables” cluster had the highest mean verbal, performance, and full‐scale IQ scores in childhood compared to children with mothers classified in the “meat and potatoes” and “white bread and coffee” clusters during pregnancy, and children of women in white bread and coffee had the lowest average scores.
- In the current study, controlling for child’s cluster pattern at 7 years of age did not remove the association with maternal diet in pregnancy, suggesting childhood diet did not completely explain the observed associations.
- Imputation of missing data did not change the associations between maternal dietary patterns and IQ at 8 years of age.
Maternal dietary patterns
A total of 47 food items were used to obtain the clusters. All the dietary data were standardised by subtracting the mean and dividing by the range for each variable.
The analyses were performed for two to seven clusters.
The amount of variation explained by the solution, the size and interpretation of each cluster, and the stability of the solution, which was evaluated using linear discriminant analysis, were the criteria to choose the best cluster solution.
Three maternal dietary patterns during pregnancy were obtained by k‐means clustering. The complete cluster derivation methods were described in a previous publication by Vilela et al. (2016).
The k‐means method derives clusters based upon the mean intakes of the input variables, using the squared Euclidian distances between observations to determine cluster position (Newby & Tucker, 2004).
The fruit and vegetables cluster (n = 4,478) women had the highest frequency of consumption of nonwhite bread, fish, cheese, pulses, nuts, pasta, rice, vegetables, salad, fruit, and fruit juice when compared to the other clusters.
The meat and potatoes cluster (n = 2,469) women had the highest frequency of consumption of all types of potatoes, red meat, meat pies, sausages and burgers, pizza, baked beans, peas, and fried foods compared to the other clusters.
In the largest cluster, white bread and coffee (n = 5,248), the most characteristic foods were white bread, coffee, cola, and full‐fat milk; although in contrast, many of the foods associated with the other two clusters were consumed less frequently, especially those that defined the fruit and vegetables cluster.
At 8 years of age, all children enrolled in ALSPAC were invited to attend a research clinic where trained psychologists measured their IQ using an adapted form of the Wechsler Intelligence Scale for Children‐III (Wechsler, Golombok, & Rust, 1992).
The raw scores were age adjusted to determine verbal, performance, and full‐scale IQ (Joinson, Heron, Butler, Emond, & Golding, 2007).
We selected variables that were known to be associated with diet and neurodevelopmental outcomes in childhood (Hibbeln et al., 2007).
The maternal and child characteristics were obtained by self‐completed postal questionnaires answered by the mother at 8, 18, and 32 weeks’ gestation and 6 months postpartum.
Confounding variables included maternal education, housing, crowding at home, partner present, maternal age, maternal smoking in pregnancy, maternal alcohol use in pregnancy, parity, ethnic origin, prepregnancy body mass index (BMI), child’s sex, and age at IQ measurement.
Maternal education was classified as low (no academic examinations or a vocational level training), medium (O level—academic examination usually taken at age 16 years) and high (A level—academic examination usually taken at age 18 years or degree). Prepregnancy BMI [weight (kg)/height (m)2] was calculated from the self‐reported weight and height at 12 weeks gestation.
Breastfeeding, child’s energy intake, and dietary cluster at 7 years—plant‐based, traditional British, and processed (Smith et al., 2011)—were also adjusted for in the analysis because they may directly influence neurodevelopment and be associated with maternal diet.
More information: Latifa S. Abdelli et al, Propionic Acid Induces Gliosis and Neuro-inflammation through Modulation of PTEN/AKT Pathway in Autism Spectrum Disorder, Scientific Reports (2019). DOI: 10.1038/s41598-019-45348-z
Journal information: Scientific Reports
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