Salivary amylase where is it produced

Maltose is a sugar that is composed of individual subunits of glucose, the human body's key source of energy. Salivary amylase also has a function in our dental health. It helps to prevent starches from accumulating on our teeth. In addition to salivary amylase, humans also produce pancreatic amylase, which further breaks down starches later in the digestive process.

As a group, kallikreins are enzymes that take high molecular weight HMW compounds, like kininogen, and cleave them to smaller units. Salivary kallikrein breaks down kininogen into bradykinin, a vasodilator. Bradykinin helps to control blood pressure in the body. It causes blood vessels to dilate or expand and causes blood pressure to be lowered. Typically, only trace amounts of salivary kallikrein are found in saliva.

Lingual lipase is an enzyme that breaks down triglycerides into glycerides and fatty acid components, thus catalyzing the digestion of lipids.

The process begins in the mouth where it breaks down the triglycerides into diglycerides. Unlike salivary amylase, which functions best in non-acidic environments, lingual lipase can operate at lower pH values, so its action continues into the stomach. Lingual lipase helps infants digest the fats in their mother's milk. As we get older, the relative proportion of lingual lipase in saliva decreases as other parts of our digestive system help with fat digestion.

Saliva contains other minor enzymes, like salivary acid phosphatase, which frees up attached phosphoryl groups from other molecules. A well-known multi-allelic copy number variant at salivary amylase gene AMY1A ; diploid copy number ranging from one to roughly 20 evolved as an adaptation to dietary habits [ 2 ]. Populations with high starch consumption carry larger number of copies than others that have maintained an ancestral pre-agricultural way of life [ 2 ].

It provided a putative genetic link between complex carbohydrate metabolism in the gut and obesity. This association was replicated in early-onset obese females from Finland [ 4 ] and in prepubertal boys in Italy [ 5 ], and an association with insulin resistance was reported in adult Korean men [ 6 ], where AMY1A copy number was also estimated by qPCR.

On the other hand, using digital PCR, two studies failed to reproduce these findings [ 7 , 8 ]. Usher et al. Recently, however, using digital PCR, we have found that, in Mexican children with high-starch diet, high number of AMY1A copies significantly protects against obesity in this population [ 9 ]. This debate is important for several reasons.

First, chromosome structural variants are increasingly recognized to highly contribute to disease development [ 11 ], and thus the correct genotyping of multi-allelic copy number variant is mandatory [ 12 ].

Second, it was shown that non-obese adults with high salivary amylase activity and putatively high AMY1A copy number present with improved glucose tolerance following liquid starch ingestion [ 13 ]. Furthermore, high serum amylase activity was shown to be associated with decreased risk of metabolic syndrome and type 2 diabetes in a Japanese asymptomatic population [ 14 ].

Finally, in more than different strains of mice fed a high-fat, high-sucrose diet, the Amy1 locus was reported to be significantly associated with weight gain variation and with an enrichment of obesity-associated bacteria of gut microbiota [ 15 ]. Therefore, it is crucial to robustly determine if amylase activities and amylase gene copy number impact energy and glucose homeostasis.

In the present study, we employed a systems biology approach, using genetics, protein activity and metabonomics analyses, to decipher the putative interaction between amylase genes and adiposity in human population. A Mendelian randomization analysis was subsequently performed to assess causality effects explaining the complex relationship between BMI and AMY1 or AMY2 plasma enzymatic activity, and actually suggested a bidirectional causal negative effect in the relationship between BMI and AMY1 plasma enzymatic activity.

We subsequently confirmed an association between AMY1A copy number and reduced obesity risk in children. At baseline, we had access to AMY1 plasma enzymatic activity for participants. Among them, we had access to AMY1 plasma enzymatic activity after 9 years of follow-up for individuals, to BMI after 9 years of follow-up for individuals, and to the levels of BMI-associated plasma metabolites at baseline for individuals. Moreover, we had access to AMY2 plasma enzymatic activity at baseline for participants.

Among them, we had access to AMY2 plasma enzymatic activity after 9 years of follow-up for individuals, to BMI after 9 years of follow-up for individuals, and to the levels of BMI-associated plasma metabolites at baseline for individuals. Additional file 1 recapitulates all these numbers. Clinical characteristics of study participants are shown in Additional file 2.

These adults were from D. Fluorescence data were analyzed using QuantaSoft software version 1. Only samples with at least droplets were kept for further analyses. The plasma enzymatic activity of AMY1 was calculated by subtracting the activity of AMY2 from the activity of total amylase.

Only individuals presenting with these normal ranges were analyzed. Fasting plasma samples were processed by the Metabolon Durham, NC, USA platform using gas chromatography mass spectrometry and liquid chromatography-tandem mass spectrometry, as previously described [ 21 , 22 ]. In the present study, we only analyzed 36 metabolites previously shown to be associated with BMI [ 23 ], including 1,5-anhydroglucitol, 1-oleoylglycerophosphocholine , 2-hydroxybutyrate, 2-linoleoylglycerophosphocholine, 3- 4-hydroxyphenyl lactate, 3-hydroxyisobutyrate, 3-methyloxobutyrate, 3-methyloxovalerate, 4-methyloxopentanoate, 7-alpha-hydroxyoxocholestenoate, alpha-hydroxyisovalerate, andro steroid monosulfate 2, asparagine, benzoate, butyrylcarnitine, carnitine, gamma-glutamylisoleucine, gamma-glutamyltyrosine, glutamate, glycerol, glycine, hexanoylcarnitine, histidine, isoleucine, isovalerylcarnitine, kynurenine, lactate, lathosterol, leucine, mannose, N-acetylglycine, palmitoyl sphingomyelin, phenylalanine, propionylcarnitine, tyrosine, and valine.

The missing values were imputed with the smallest detected value. We were unable to analyze the BMI-associated metabolite 1-eicosadienoylglycerophosphocholine [ 23 ], as it was undetectable in the present study cohort. Ethnic characterization of each participant was assessed using the iSelect Metabochip DNA microarrays Illumina , as previously described [ 24 ]. We used the same models for the analysis of plasma metabolites, with the same adjustments including or not BMI.

The analysis of BMI was adjusted for age, sex, daily alcohol consumption, smoking status, and the first two principal components for ethnicity. The effect of AMY1 or AMY2 activity at baseline on the change in BMI during the 9-year follow-up was assessed through a linear regression model adjusted for age at baseline, sex, BMI at baseline, daily alcohol consumption, smoking status, and the first two principal components for ethnicity.

The effect of BMI at baseline on the change in AMY1 or AMY2 activity during the 9-year follow-up was assessed through a linear regression model adjusted for age at baseline, sex, AMY1 or AMY2 activity at baseline, daily alcohol consumption, smoking status, and the first two principal components for ethnicity. Association analyses of glucose-related traits were performed in non-diabetic individuals only.

Association analyses of lipid traits were performed in participants who did not use any lipid-lowering drugs at baseline. Association analyses of blood pressure were performed in participants who did not use any drugs against hypertension at baseline. In each regression model, traits were analyzed as dependent variables whilst copy number and enzymatic activities were used as covariates. We used single nucleotide polymorphisms SNPs previously found to be genome-wide significantly associated with BMI [ 27 ] as genetic instruments for this analysis.

We excluded 14 SNPs with known pleiotropic effects on non-anthropometric traits Additional file 3. Standard errors for these causal estimates were derived by replacing in the former calculations each SNP effect size on AMY1 or AMY2 plasma enzymatic activity with its corresponding standard error estimated within D.

The 83 values of causal effects of BMI on AMY1 or AMY2 plasma enzymatic activity were collapsed into single estimates one for each enzymatic activity using inverse-variance weighting [ 25 ]. Since no published genome-wide association studies on amylase activities were available, we used as an alternative approach, the two-stage least-squares TSLS regression to estimate the causal effect of BMI on AMY1 or AMY2 plasma enzymatic activity using D. This analysis used as the instrumental variable the genetic risk score, calculated as the sum of alleles increasing BMI over the 83 selected SNPs.

To ensure that cryptic pleiotropic effects among the 83 SNPs were not influencing our estimates of causal effect of BMI on AMY1 and AMY2 plasma enzymatic activities, we used Egger regression to test for the significance of the intercept [ 28 ]. The association between obesity and AMY1A copy number was assessed by a logistic regression model adjusted for age and sex in the two case-control studies.

All genetic analyses were performed under an additive model. Additional files 7 , 9 and Data are unadjusted Spearman correlations with P values. Next, we took advantage of the prospective D. While the number of amylase genes increases almost linearly with starch consumption, there is no difference in amylase activity in the saliva of species with intermediate or high starch consumption.

Both have much more amylase in their saliva than species with very low or no starch intake, but in species with high starch consumption, the additional copies of the amylase gene do not seem to translate to higher amounts of salivary enzyme Figure 1C. Similarly, some species with very high amylase activity in their saliva, such as baboons or macaques, do not have a corresponding increase in amylase gene copies.

These unexpected findings should encourage research into the other mechanisms that may affect the activity of salivary amylase. Another avenue of study could be to look at the pancreatic activity of the enzyme. Pajic et al. Humans have adapted to efficiently digest new foods such as milk and grains Janiak, , but our dietary habits and our love for starchy carbohydrates might also have shaped the animals that live amongst us.

The new findings by Pajic et al. This article is distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use and redistribution provided that the original author and source are credited.

Article citation count generated by polling the highest count across the following sources: Crossref , PubMed Central , Scopus. The amylase gene AMY , which codes for a starch-digesting enzyme in animals, underwent several gene copy number gains in humans Perry et al.

Here, we present comprehensive evidence for AMY copy number expansions that independently occurred in several mammalian species which consume diets rich in starch. We also provide correlative evidence that AMY gene duplications may be an essential first step for amylase to be expressed in saliva. Our findings underscore the overall importance of gene copy number amplification as a flexible and fast evolutionary mechanism that can independently occur in different branches of the phylogeny.

However, the ecological response of insects—the most diverse group of organisms on Earth—to the EPME remains poorly understood. Here, we analyse beetle evolutionary history based on taxonomic diversity, morphological disparity, phylogeny, and ecological shifts from the Early Permian to Middle Triassic, using a comprehensive new dataset.

These enzymes, known collectively as disaccharidase, are sucrase, maltase, and lactase. Sucrase breaks sucrose into glucose and fructose molecules. Maltase breaks the bond between the two glucose units of maltose, and lactase breaks the bond between galactose and glucose. Once carbohydrates are chemically broken down into single sugar units they are then transported into the inside of intestinal cells.

When people do not have enough of the enzyme lactase, lactose is not sufficiently broken down resulting in a condition called lactose intolerance. The undigested lactose moves to the large intestine where bacteria are able to digest it.

The bacterial digestion of lactose produces gases leading to symptoms of diarrhea, bloating, and abdominal cramps. Lactose intolerance usually occurs in adults and is associated with race. The severity of the symptoms depends on how much lactose is consumed and the degree of lactase deficiency. The cells in the small intestine have membranes that contain many transport proteins in order to get the monosaccharides and other nutrients into the blood where they can be distributed to the rest of the body.

The first organ to receive glucose, fructose, and galactose is the liver. The liver takes them up and converts galactose to glucose, breaks fructose into even smaller carbon-containing units, and either stores glucose as glycogen or exports it back to the blood. How much glucose the liver exports to the blood is under hormonal control and you will soon discover that even the glucose itself regulates its concentrations in the blood.

Glucose levels in the blood are tightly controlled, as having either too much or too little glucose in the blood can have health consequences. Glucose regulates its levels in the blood via a process called negative feedback. An everyday example of negative feedback is in your oven because it contains a thermostat.

The glucose thermostat is located within the cells of the pancreas. After eating a meal containing carbohydrates glucose levels rise in the blood. Insulin-secreting cells in the pancreas sense the increase in blood glucose and release the hormone, insulin, into the blood.

In the case of muscle tissue and the liver, insulin sends the biological message to store glucose away as glycogen. The presence of insulin in the blood signifies to the body that glucose is available for fuel.

As glucose is transported into the cells around the body, the blood glucose levels decrease.