My selection for Paper of the Week for 16 March 2012 is by Joel Dudley, et al. and published as a letter in Molecular Biology & Evolution. Its title is "Evolutionary meta-analysis of association studies reveals ancient constraints affecting disease marker discovery."
The authors examined over 5800 disease-associating variants, comparing the genomic neighborhood across a panel of species. This covered 230 different disease and disease risk phenotypes. Importantly, the authors demonstrate that there is a propensity to discover such disease SNPs at "conserved genomic positions, because the effect size (odds ratio) and allelic P-value of genetic association of a SNP relates strongly to the evolutionary conservation of their genomic position." This then allowed them to develop a new means to rank such association SNPs in which a conservation score, based on the evolutionary analysis, is incorporated into the P-value of the genotype-phenotype association.
As many GWAS SNPs alter gene expression - either through altered transcription factor binding or microRNA-mRNA interaction, and as such evolutionary mechanisms most likely involve a sensing or monitoring of the environment with concomitant changes in gene expression, this makes sense. In fact, the role of such types of SNPs (those under selective pressure) and their role in heart disease, was a topic on which we published in 2010.
The article by Dudley, et al. is really nice work and one whose insight we will use to inform our GWAS analysis.
Friday, March 16, 2012
POTW: Exercise and gene methylation
The Paper of the Week for 9 March 2012 was entitled "Acute Exercise Remodels Promoter Methylation in Human Skeletal Muscle" by Barres, et al. It appeared in Cell Metabolism as a Short Article.
The exercise test was performed on a stationary bicycle. One cohort of subjects were exercised until reaching either 40% or 80% of VO2 peak. A second cohort was exercised until 1,674 kJ were expended. These were acute interventions, making the findings all the more remarkable.
I found the following to be key points of this paper:
1. In both healthy, sedentary women and men, it was observed that whole genome methylation was decreased in skeletal muscle.
2. While exercise induced expression of PPARGC1A (PGC-1α), PDK4, and PPARD, the authors also noted reduced methylation at each of the promoters for these genes.
PPARGC1A is a key transcriptional regulator of OXPHOS (oxidative phosphorylation) genes. It is also an important type 2 diabetes gene.
The exercise test was performed on a stationary bicycle. One cohort of subjects were exercised until reaching either 40% or 80% of VO2 peak. A second cohort was exercised until 1,674 kJ were expended. These were acute interventions, making the findings all the more remarkable.
I found the following to be key points of this paper:
1. In both healthy, sedentary women and men, it was observed that whole genome methylation was decreased in skeletal muscle.
2. While exercise induced expression of PPARGC1A (PGC-1α), PDK4, and PPARD, the authors also noted reduced methylation at each of the promoters for these genes.
PPARGC1A is a key transcriptional regulator of OXPHOS (oxidative phosphorylation) genes. It is also an important type 2 diabetes gene.
Friday, March 2, 2012
POTW: Epigenetics and cognitive function
This weeks Paper of the Week adds some detail to connections between cognitive function and epigenetics as histone modifications. The paper is "An epigenetic blockade of cognitive functions in the neurodegenerating brain" by Gräff, et al. The paper was published in Nature on 29 Feb 2012.
What makes this a noteworthy paper, in my opinion, is the link between Alzheimer disease and lifestyle choices. The lifestyle choices of smoking, diet and physical activity (and likely others) have the ability to affect epigenetic patterns of either DNA methylation or histone acetylation. The authors demonstrate that cognitive abilities in a brain with developing neurodegeneration are held in check by an epigenetic-based restriction of gene transcription, and this is potentially reversible. This repression of mRNA synthesis is mediated by histone deacetylase 2 (or HDAC2). Furthermore, this repression is increased by Alzheimer’s-disease-related neurotoxic insults in vitro, in two mouse models of neurodegeneration and in patients with Alzheimer’s disease.
Imagine if something in the diet or something like exercise could reduce or repress the built-up activity of HDAC2 that occurs as a result of the neurotoxic insults described in the paper. That would be exciting. Thus, I see this work as important in showing, again, how environment and epigenetics can affect disease state. It is certainly likely that certain lifestyle choices would have greater or lesser impact on neurodegenerative processes and either augment or enhance the genetic risk of disease. Although not demonstrated in this article, it could be that an APOE epsilon 4 (E4) genotype, with its increased risk of Alzheimer disease could be partially ameliorated via those lifestyle choices that inhibit or curtail excessive HDAC2 activity. That woud indeed be quite exciting.
What makes this a noteworthy paper, in my opinion, is the link between Alzheimer disease and lifestyle choices. The lifestyle choices of smoking, diet and physical activity (and likely others) have the ability to affect epigenetic patterns of either DNA methylation or histone acetylation. The authors demonstrate that cognitive abilities in a brain with developing neurodegeneration are held in check by an epigenetic-based restriction of gene transcription, and this is potentially reversible. This repression of mRNA synthesis is mediated by histone deacetylase 2 (or HDAC2). Furthermore, this repression is increased by Alzheimer’s-disease-related neurotoxic insults in vitro, in two mouse models of neurodegeneration and in patients with Alzheimer’s disease.
Imagine if something in the diet or something like exercise could reduce or repress the built-up activity of HDAC2 that occurs as a result of the neurotoxic insults described in the paper. That would be exciting. Thus, I see this work as important in showing, again, how environment and epigenetics can affect disease state. It is certainly likely that certain lifestyle choices would have greater or lesser impact on neurodegenerative processes and either augment or enhance the genetic risk of disease. Although not demonstrated in this article, it could be that an APOE epsilon 4 (E4) genotype, with its increased risk of Alzheimer disease could be partially ameliorated via those lifestyle choices that inhibit or curtail excessive HDAC2 activity. That woud indeed be quite exciting.
Friday, February 24, 2012
Proteomics of fasting
It was with keen interest that I read the article by Bouwman, et al. entitled “2D-electrophoresis and multiplex immunoassay proteomic analysis of different body fluids and cellular components reveal known and novel markers for extended fasting,” which appeared in BMC Medical Genomics last week. As we are interested in the genetic basis for the differential response to diet, we view perturbations to the system, either by a high-fat intervention or fasting/calorie restriction, as instrumental in deciphering this response. Overall, I found this to be nice work and deserving of a wide audience.
The authors report that “[p]rincipal component analysis applied to the multiplex immunoassay (RBM) data set revealed that each of the subjects could be identified based on levels of 89 plasma proteins (see figure 3). It appears that such data can be used to provide a metabolic fingerprint of the individual volunteers participating in this intervention study. However, this demonstrates that the between-subject effects are larger than that of the fasting effect.”
This is not surprising given that of the 44 different proteins identified as responding to extended fasting (see tables 2 & 3, figure 4), nine are encoded by genes harboring variants responding differentially to environmental factors such as dietary intake and physical activity. The dietary component most often modulating the association between those genes (and their variants) and a phenotype pertinent to metabolic syndrome is fat. Physical activity is also a wide-reaching modulator of the association between genetic variation and various phenotypes pertinent to metabolic syndrome. In other words, a combination of genetic variation between study participants in combination with each individual’s lifestyle choices (say, more or less exercise) could indeed influence the levels of certain proteins found to respond to the fasting intervention.
At the same time, I cannot dispute, as the authors write, that the between-subject variation may have arisen from heterogeneity of the study cohort “with regard to various parameters, including gender and BMI.” This is logical, but again other factors such as habitual diet and exercise, even sleep patterns could be at work here. Another source of between-subject variation is certainly genetic.
The authors observe that “[m]ost interesting biomarkers are involved in metabolic pathways, as well as those related to inflammation and oxidative stress.” This is where my quite minor complaint with the work arises – I would have liked to see more interpretation of the results from a biological or even medical perspective. Thus, I note that IL10, IL1B, TNF, SERPINE1, INS and CCL2 respond to extended fasting and are members of the Insulin resistance inflammation network (Olefsky, Glass (2010) in a review of Macrophages, Inflammation and Insulin Resistance (Annu Rev Physiol 72:219-46)). Furthermore, VCAM1, APCS, CRP, IL1B, TNF, IL18 and CCL2 are assigned an inflammation role within the set of PPARA target genes (Rakhshandehroo, Kersten 2010 PPAR Research pii: 612089).
A second comparison I undertook was to look at the number of genes responding to the fasting intervention and to an intervention termed AIDM: Anti-inflammatory dietary mix (Bakker, et al 2010 Am J Clin Nutr 91:1044). Large-scale assays of genes, proteins, and metabolites in plasma, urine, and adipose tissue showed that an intervention with selected dietary components influenced inflammatory processes, oxidative stress and metabolism in humans. Eight genes are in common and we’d expect about one by chance. These eight genes are FABP3, VCAM1, IL12A, AFP, FTH1, IL18, APOA1 and F7. Most of these eight were described in the AIDM article as down-regulated (lower levels) in plasma by the dietary intervention, similar to the response to fasting. This raises the intriguing hypothesis that the AIDM diet at least partially mimics fasting.
Adipokines are signaling proteins that are secreted from adipocytes. It is an interesting observation, then, that four of the altered proteins seen during fasting are described by Rosenow, et al as adipokines. These are SERPINE1, SERPINF1, C3 and TIMP1. Perhaps fasting-induced changes to the signaling potential of adipose tissue should focus on these four proteins.
The authors report that “[p]rincipal component analysis applied to the multiplex immunoassay (RBM) data set revealed that each of the subjects could be identified based on levels of 89 plasma proteins (see figure 3). It appears that such data can be used to provide a metabolic fingerprint of the individual volunteers participating in this intervention study. However, this demonstrates that the between-subject effects are larger than that of the fasting effect.”
This is not surprising given that of the 44 different proteins identified as responding to extended fasting (see tables 2 & 3, figure 4), nine are encoded by genes harboring variants responding differentially to environmental factors such as dietary intake and physical activity. The dietary component most often modulating the association between those genes (and their variants) and a phenotype pertinent to metabolic syndrome is fat. Physical activity is also a wide-reaching modulator of the association between genetic variation and various phenotypes pertinent to metabolic syndrome. In other words, a combination of genetic variation between study participants in combination with each individual’s lifestyle choices (say, more or less exercise) could indeed influence the levels of certain proteins found to respond to the fasting intervention.
At the same time, I cannot dispute, as the authors write, that the between-subject variation may have arisen from heterogeneity of the study cohort “with regard to various parameters, including gender and BMI.” This is logical, but again other factors such as habitual diet and exercise, even sleep patterns could be at work here. Another source of between-subject variation is certainly genetic.
The authors observe that “[m]ost interesting biomarkers are involved in metabolic pathways, as well as those related to inflammation and oxidative stress.” This is where my quite minor complaint with the work arises – I would have liked to see more interpretation of the results from a biological or even medical perspective. Thus, I note that IL10, IL1B, TNF, SERPINE1, INS and CCL2 respond to extended fasting and are members of the Insulin resistance inflammation network (Olefsky, Glass (2010) in a review of Macrophages, Inflammation and Insulin Resistance (Annu Rev Physiol 72:219-46)). Furthermore, VCAM1, APCS, CRP, IL1B, TNF, IL18 and CCL2 are assigned an inflammation role within the set of PPARA target genes (Rakhshandehroo, Kersten 2010 PPAR Research pii: 612089).
A second comparison I undertook was to look at the number of genes responding to the fasting intervention and to an intervention termed AIDM: Anti-inflammatory dietary mix (Bakker, et al 2010 Am J Clin Nutr 91:1044). Large-scale assays of genes, proteins, and metabolites in plasma, urine, and adipose tissue showed that an intervention with selected dietary components influenced inflammatory processes, oxidative stress and metabolism in humans. Eight genes are in common and we’d expect about one by chance. These eight genes are FABP3, VCAM1, IL12A, AFP, FTH1, IL18, APOA1 and F7. Most of these eight were described in the AIDM article as down-regulated (lower levels) in plasma by the dietary intervention, similar to the response to fasting. This raises the intriguing hypothesis that the AIDM diet at least partially mimics fasting.
Adipokines are signaling proteins that are secreted from adipocytes. It is an interesting observation, then, that four of the altered proteins seen during fasting are described by Rosenow, et al as adipokines. These are SERPINE1, SERPINF1, C3 and TIMP1. Perhaps fasting-induced changes to the signaling potential of adipose tissue should focus on these four proteins.
Thursday, February 23, 2012
POTW: January, 2012 choices
Three papers published last month that I found to be of interest are listed here. These are:
The mystery of missing heritability: Genetic interactions create phantom heritability, by Zuk, et al. This addresses the missing heritability question, suggesting that "the total heritability may be much smaller and thus the proportion of heritability explained much larger."
Characterisation and discovery of novel miRNAs and moRNAs in JAK2V617F mutated SET2 cells, by Botoluzzi, et al. What interested me in this article was the generation of novel microRNAs that were induced by the cancerous state triggered by this JAK2 variant. This indicates to me that the microRNA realm is broad and rich with many as yet undiscovered relationships.
The PLoS One paper entitled "Genetic signatures of exceptional longevity in humans," by Sebastiani, et al. We here were very curious how this was different from the version retracted from Science and what findings are now reported. TOMM40 near APOE is indeed interesting.
The mystery of missing heritability: Genetic interactions create phantom heritability, by Zuk, et al. This addresses the missing heritability question, suggesting that "the total heritability may be much smaller and thus the proportion of heritability explained much larger."
Characterisation and discovery of novel miRNAs and moRNAs in JAK2V617F mutated SET2 cells, by Botoluzzi, et al. What interested me in this article was the generation of novel microRNAs that were induced by the cancerous state triggered by this JAK2 variant. This indicates to me that the microRNA realm is broad and rich with many as yet undiscovered relationships.
The PLoS One paper entitled "Genetic signatures of exceptional longevity in humans," by Sebastiani, et al. We here were very curious how this was different from the version retracted from Science and what findings are now reported. TOMM40 near APOE is indeed interesting.
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