Transcriptomic Analysis of Alzheimer's Disease Pathways in a Pakistani Population.

Background: Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder that is most prevalent in elderly individuals, especially in developed countries, and its prevalence is now increasing in developing countries like Pakistan. Objective: Our goal was to characterize key genes and their levels of expression and related molecular transcriptome networks associated with AD pathogenesis in a pilot case-control study in a Pakistani population. Methods: To obtain the spectrum of molecular networks associated with pathogenesis in AD patients in Pakistan (comparing cases and controls), we used high-throughput qRT-PCR (TaqMan Low-Density Array; n = 33 subjects) coupled with Affymetrix Arrays (n = 8) and Ingenuity Pathway Analysis (IPA) to identify signature genes associated with Amyloid processing and disease pathways. Results: We confirmed 16 differentially expressed AD-related genes, including maximum fold changes observed in CAPNS2 and CAPN1. The global gene expression study observed that 61% and 39% of genes were significantly (p-value 0.05) up- and downregulated, respectively, in AD patients compared to healthy controls. The key pathways include, e.g., Amyloid Processing, Neuroinflammation Signaling, and ErbB4 Signaling. The top-scoring networks in Diseases and Disorders Development were Neurological Disease, Organismal Injury and Abnormalities, and Psychological Disorders. Conclusions: Our pilot study offers a non-invasive and efficient way of investigating gene expression patterns by combining TLDA and global gene expression method in AD patients by utilizing whole blood. This provides valuable insights into the expression status of genes related to Amyloid Processing, which could play potential role in future studies to identify sensitive, early biomarkers of AD in general.

Gene expression signatures in PCB-exposed Slovak children in relation to their environmental exposures and socio-physical characteristics.

Our previous gene expression studies in a PCB-exposed cohort of young children in Slovakia revealed that early-life exposures to PCBs and other organochlorine compounds were associated with significant alterations across several pathogenetic pathways. The present study was undertaken to further explore the high-throughput qRT-PCR-based gene expression effects by using TaqMan low-density array (TLDA) for selected genes in a sample of 55 children from the cohort. We analyzed the transcriptional changes of 11 genes in relation to PCB and organochlorine pesticide exposure levels (including DDT, DDE, HCH, and HCB), and to BMI and ethnicity in this cohort. The results indicated an overall downregulation of expression of these genes. Maximum downregulation (in fold change) was observed in the ENTPD3 gene, and the minimum level of downregulation was in CYP2D6. As per our multinomial regression model study, downregulation of LEPR gene was significantly directly correlated with all the exposure variables. Downregulation of APC, ARNT, CYP2D6, LEPR, LRP12, and MYC genes was directly correlated with BMI (kg/m2) of the individuals. Gender-specific differences in gene expression were observed in CYP2D6 (p-value 0.0001) and LEPR (p-value 0.028), while downregulation of CYP2D6 (p-value 0.01), LEPR (p-value 0.02), LRP12 (p-value 0.04), and MYC (p-value 0.02) genes was consistently observed in Roma children compared to Caucasians. The investigation of such health disparities must be emphasized in future research, together with interventions to reduce the health consequences of PCB exposures. In this context, we emphasize the importance of biomarker-based approaches to future research on genetic susceptibility to the effects of these compounds.

Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population.

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson's Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.