G. R. Sridhar

Alzheimer's disease and Type 2 diabetes mellitus: the cholinesterase connection?

Alzheimers disease and type 2 diabetes mellitus tend to occur together. We sought to identify protein(s) common to both conditions that could suggest a possible unifying pathogenic role. Using human neuronal butyrylcholinesterase (AAH08396.1) as the reference protein we used BLAST Tool for protein to protein comparison in humans. We found three groups of sequences among a series of 12, with an E-value between 0–12, common to both Alzheimers disease and diabetes: butyrylcholinesterase precursor K allele (NP_000046.1), acetylcholinesterase isoform E4-E6 precursor (NP_000656.1), and apoptosis-related acetylcholinesterase (1B41|A). Butyrylcholinesterase and acetylcholinesterase related proteins were found common to both Alzheimers disease and diabetes; they may play an etiological role via influencing insulin resistance and lipid metabolism.

Emerging links between type 2 diabetes and Alzheimer's disease.

Type 2 diabetes mellitus and Alzheimers disease are both associated with increasing age, and each increases the risk of development of the other. Epidemiological, clinical, biochemical and imaging studies have shown that elevated glucose levels and diabetes are associated with cognitive dysfunction, the most prevalent cause of which is Alzheimers disease. Cross sectional studies have clearly shown such an association, whereas longitudinal studies are equivocal, reflecting the many complex ways in which the two interact. Despite the dichotomy, common risk and etiological factors (obesity, dyslipidemia, insulin resistance, and sedentary habits) are recognized; correction of these by lifestyle changes and pharmacological agents can be expected to prevent or retard the progression of both diseases. Common pathogenic factors in both conditions span a broad sweep including chronic hyperglycemia per se, hyperinsulinemia, insulin resistance, acute hypoglycemic episodes, especially in the elderly, microvascular disease, fibrillar deposits (in brain in Alzheimers disease and in pancreas in type 2 diabetes), altered insulin processing, inflammation, obesity, dyslipidemia, altered levels of insulin like growth factor and occurrence of variant forms of the protein butyrylcholinesterase. Of interest not only do lifestyle measures have a protective effect against the development of cognitive impairment due to Alzheimers disease, but so do some of the pharmacological agents used in the treatment of diabetes such as insulin (especially when delivered intranasally), metformin, peroxisome proliferator-activated receptors γ agonists, glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors. Diabetes must be recognized as a risk for development of Alzheimers disease; clinicians must ensure preventive care be given to control and postpone both conditions, and to identify cognitive impairment early to manage it appropriately.

Built environment and diabetes.

Development of type 2 diabetes mellitus is influenced by built environment, which is, ‘the environments that are modified by humans, including homes, schools, workplaces, highways, urban sprawls, accessibility to amenities, leisure, and pollution.’ Built environment contributes to diabetes through access to physical activity and through stress, by affecting the sleep cycle. With globalization, there is a possibility that western environmental models may be replicated in developing countries such as India, where the underlying genetic predisposition makes them particularly susceptible to diabetes. Here we review published information on the relationship between built environment and diabetes, so that appropriate modifications can be incorporated to reduce the risk of developing diabetes mellitus.

Butyrylcholinesterase in metabolic syndrome

Butyrylcholinesterase may have a role in a number of metabolic functions and could affect the expression of insulin resistance syndrome. We present our integrated work using clinical, biochemical and bioinformatic approaches to delineate the possible function of this enzyme. Initially, we constructed a phylogenic tree with nucleotides and amino acid sequences and showed the existence of similar sequences in bacteria, plants and in other animals. We also demonstrated a possible pathogenic role for BChE in the common existence of insulin resistance, type 2 diabetes and Alzheimers disease by in silico method and followed it up with a diabetic mouse study where cognition was slowed along with changes in BChE levels. In the next group of in silico studies, we employed THEMATICS method to identify the amino acids at the active site and later performed docking studies with drugs. THEMATICS predicted two clusters of ionisable amino acid residues that are in proximity: one with two residues and another with 11 showed perturbation in the THEMATICS curves. Using ISIS/Draw 2.5SP4, ARGUSLAB 4.0.1 and HEX 5.1. software. 3-D ligands were docked with BChE motif (from PDB). We did not find any of the ligands studied with significant docking distance, indicating they did not have direct interaction with the active site. Subsequently we performed in silico studies to compare the secondary structure and domain of BChE. Protein-protein interaction showed the following intersections with BChE UBE21, CHAT, APOE, AATF, DF ALDH9A1, PDHX, PONI PSME3 and ATP6VOA2. The integrative physiological roles of proteins with poorly known functions can be approached by generating leads in silico, which can be studied in vivo, setting into movement an iterative process.

Cluster analysis and phylogenetic relationship in biomarker identification of type 2 diabetes and nephropathy.

Cluster analysis of DNA microarray data that uses statistical algorithms to arrange the genes according to similarity in patterns of gene expression and the output displayed graphically is described in this article. Hierarchical clustering is a multivariate tool often used in phylogenetics, comparative genomics to relate the evolution of species. The patterns seen in microarray expression data can be interpreted as indications of the status of the genes responsible for nephropathy in peripheral blow cells of type 2 diabetes (T2DN). Out of 415 genes totally expressed in the 3 DNA chips it was concluded that only 116 genes expressed in T2DN and in that only 50 are functional genes. These 50 functional genes are responsible for diabetic nephropathy; of these 50, some of the genes which are more expressed and responsible are AGXT: Alanine-glyoxylate aminotransferase, RHOD: Ras homolog gene family, CAPN6: Calpain 6, EFNB2: Ephrin-B2, ANXA7: Annexin A7, PEG10: Paternally expressed 10, DPP4: Dipeptidyl-peptidase 4 (CD26, adenosine deaminase complexing protein 2), ENSA: Endosulfine alpha, IGFBP2: Insulin-like growth factor binding protein 2, 36kDa, CENPB: Centromere protein B, 80kDa, MLL3: Myeloid/lymphoid or mixed-lineage leukemia 3, BDNF: Brain-derived neurotrophic factor, EIF4A2: Eukaryotic translation initiation factor 4A, isoform 2, PPP2R1A: Protein phosphatase 2 (formerly 2A), regulatory subunit A, alpha isoform. Fifty genes and their nucleotide sequences are taken from NCBI and a phylogenetic tree is constructed using CLUSTAL W and the distances are closer to each other concluding that based on the sequence similarity and evolution the genes are expressed similarly. Literature survey is done for each gene in OMIM and the genes responsible for diabetic nephropathy are listed.

Quality of care: assessment

To translate science into clinical practice we must first assess the quality of care that is being delivered. The resulting information about qualitative and quantitative parameters can then be assessed. Ultimately insights can be obtained into improving the quality of care in diabetes mellitus. The Diabetes Quality Improvement Programme in USA has shown such an exercise is feasible. A similar exercise in India is necessary to improve the quality of diabetes care.

Robust seed selection algorithm for k-means type algorithms

Selection of initial seeds greatly affects the quality of the clusters and in k-means type algorithms. Most of the seed selection methods result different results in different independent runs. We propose a single, optimal, outlier insensitive seed selection algorithm for k-means type algorithms as extension to k-means++. The experimental results on synthetic, real and on microarray data sets demonstrated that effectiveness of the new algorithm in producing the clustering results

Enhanced Butyrylcholinesterase Activity may be the Common Link in Triggering Low-Grade Systemic Inflammation and Decrease in Cognitive Function in Diabetes Mellitus and Alzheimers disease

There is increasing evidence that diabetes mellitus and Alzheimers disease occur more often than by chance. Recently, we proposed that increase in the activity of the enzyme butyrylcholinesterase could be a common link between these two conditions. Acetylcholine is an anti-inflammatory molecule. Butyrylcholinesterase by inactivating acetylcholine may enhance inflammation and induce decline in cognitive function. In the present study, it was noted that streptozotocin- induced diabetic animals showed dyslipidemia, increase in plasma lipid peroxides, decrease in circulating plasma superoxide dismutase activity, decline in cognitive function as assessed by the Morris water maze method, and a significant increase in serum butyrylcholinesterase activity. These results suggest that increased plasma and, possibly, tissue concentrations of butyrylcholinesterase lead to decrease in acetylcholine levels, an anti-inflammatory molecule, which may trigger low-grade systemic inflammation in diabetes mellitus and Alzheimers disease that could account for decline in cognitive function.

Sleep, circadian dysrhythmia, obesity and diabetes

Synchrony of biological processes with environmental cues developed over millennia to match growth, reproduction and senescence. This entails a complex interplay of genetic, metabolic, chemical, light, hormonal and hedonistic factors across life forms. Sleep is one of the most prominent rhythms where such a match is established. Over the past 100 years or so, it has been possible to disturb the synchrony between sleep-wake cycle and environmental cues. Development of electric lights, shift work and continual accessibility of the internet has disrupted this match. As a result, many non-communicable diseases such as obesity, insulin resistance, type 2 diabetes, coronary artery disease and malignancies have been attributed in part to such disruption. In this presentation a review is made of the origin and evolution of sleep studies, the pathogenic mediators for such asynchrony, clinical evidence and relevance and suggested management options to deal with the disturbances.

Bioinformatics approach to extract information from genes

With the widespread availability of nucleotide and amino acid sequences, novel methods for extracting biologically and clinically relevant knowledge are feasible. Data is deposited on the Internet on websites such as GeneCards, available at http://www. genecards.org/mirror.shtml. Further information can be obtained from related sites - UniProt (http://www. uniprot.org) and SwissProt (http://www.expasy.org/ sprot/). Using FASTA and CLUSTAL_X programs, similarity scores can be calculated to choose items of interest. Further information can be obtained by mining text, either manually or increasingly using text-mining tools such as PathBinderH and GENIA corpus.