Genome scale meta analysis of microarrays for biological inferences

Title from PDF of title page (University of Missouri--Columbia, viewed on April 5, 2010).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Dong Xu.Vita.Ph. D. University of Missouri--Columbia 2009.In this present era of high-throughput technologies, meta-analysis is being widely used to integrate multiple similar high throughput studies. Here we propose a novel framework for applying meta-analysis techniques on expression data for gene function characterizations and biological networks construction like the gene regulatory network. In particular, we developed a prototype for gene function annotation using multiple microarray datasets and tested the performance of our model using yeast and human microarray datasets. Our results show significant improvement in functional annotation in general. We further applied the same metaanalysis method on the Arabidopsis plant in a collaborative project with Monsanto Company to construct regulatory network for Arabidopsis. Our method shows significant improvement than any other existing methods for inferring gene regulatory network. Beside meta-analysis, I have invested a great deal of efforts in developing PRIMEGENS, an open source software, which could be used for large-scale primers and probe design for PCR, DNA synthesis, qRT-PCR (gene expression), and targeted next-generation sequencing (454, Solexa, Agilent sure-select technology etc.) for normal or bisulfite-treated genome. We recently extended its functionality including microarray probe design to cover genome-wide CpG islands in human, Taqman probes and discriminating transcripts from its multiple homologs or splice variants based on gene-specific unique fragment in soybean genome.Includes bibliographical reference

ArrayD: A general purpose software for Microarray design

BACKGROUND: Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted. RESULTS: We have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot. CONCLUSIONS: ArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at

Trials of Improved Practices (TIPs) to Enhance the Dietary and Iron-Folate Intake during Pregnancy- A Quasi Experimental Study among Rural Pregnant Women of Varanasi, India.

BACKGROUND: Behavior Change Communications (BCC) play a decisive role in modifying socio-cultural norms affecting the perception and nutritional practices during pregnancy. OBJECTIVE: To examine the effectiveness of 'Trials of Improved Practices' (TIPs) on dietary and iron-folate intake during pregnancy. DESIGN: Community based quasi experimental study with a control group. SETTING: Four villages of Chiraigaon Community Development Block of Varanasi, India from May 2010 and recruited from August 2010. End line assessment, after 12 weeks of intervention, was completed in April 2011. PARTICIPANTS: Pregnant women in 13-28 weeks of gestation. INTERVENTION: TIPs was implemented in addition to ongoing essential obstetric care services in two villages through 3 home (assessment, negotiation and evaluation) visits and only assessment and evaluation visits in the other two control villages. Interpersonal communication, endorsing the active participation of family members and home based reminder materials were the TIPs based strategies. The effect of TIPs was assessed by comparing key outcome variables at baseline and after 12 weeks of intervention. OUTCOME MEASURES: Hemoglobin%, anemia prevalence, weight gain, compliance for iron-folate supplementation and dietary intake of calorie, protein, calcium and iron. RESULTS: A total of 86 participants completed the study. At the end, mean hemoglobin levels were 11.5±1.24 g/dl and 10.37±1.38 g/dl in the TIPs and control groups, respectively. The prevalence of anemia reduced by half in TIPs group and increased by 2.4% in the control group. Weight gain (grams/week) was significantly (p<0.01) higher in TIPs group (326.9±91.8 vs. 244.6±97.4). More than 85% of the PW in TIPs group were compliant for Iron-folate and only 38% were compliant among controls. The mean intake of protein increased by 1.78gm in intervention group and decreased by 1.81 gm in controls (p<0.05). More than two thirds of PW in TIPs group were taking one extra meal and only one third of controls were doing the same. CONCLUSION: TIPs found to be an effective approach to improve the nutritional status of pregnant women in the study area. TIPs strategy could be further explored on larger sample representing different socio-cultural and geographical areas. TRIAL REGISTRATION: Clinical Trial Registry of India CTRI/2015/02/005517

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Hemoglobin level and weight of the pregnant women in both the study groups before and after the intervention (n = 86).

<p>^†Hemoglobin,</p><p>^‡weight change: grams per week</p><p>^§Highly significant</p><p>^¶Significant</p><p>Hemoglobin level and weight of the pregnant women in both the study groups before and after the intervention (n = 86).</p

CONSORT flow diagram of the study participants.

<p>CONSORT flow diagram of the study participants.</p

Dietary intake of calorie, protein, Iron and Calcium by 24 hour recall method in both the study groups before and after the intervention (N = 86).

<p>^†Highly Significant</p><p>Dietary intake of calorie, protein, Iron and Calcium by 24 hour recall method in both the study groups before and after the intervention (N = 86).</p