Mechanistic Phenotypes: An Aggregative Phenotyping Strategy to Identify Disease Mechanisms Using GWAS Data

A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with “mechanistic phenotypes”, comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher''s p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10−5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10−6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.     

Leukemic histiocytic sarcoma in a captive common squirrel monkey (Saimiri sciureus) with Saimiriine Gammaherpesvirus 2 (Rhadinovirus), Saimiri sciureus lymphocryptovirus 2 (Lymphocryptovirus) and Squirrel monkey retrovirus (β-Retrovirus) coinfection

Hematopoietic neoplasia other than lymphoma and leukemia is uncommon among non-human primates. Herein, we provide the first evidence of occurrence of leukemic histiocytic sarcoma in a captive common squirrel monkey with Saimiriine Gammaherpesvirus 2 (Rhadinovirus), Saimiri sciureus lymphocryptovirus 2 (Lymphocryptovirus), and Squirrel monkey retrovirus (β-Retrovirus) coinfection.     

Somatoform disorders among patients attending walk-in clinics in Trinidad: prevalence and association with depression and anxiety

Objectives Somatoform disorders are common in international primary care settings, but have been little studied in the developing world. The objective of this study was to determine the prevalence of severe undifferentiated somatoform disorder, and its relationship to depression and anxiety, among patients attending walk-in clinics in Trinidad.Methods The study participants, who were all aged 18 years or older and attending walk-in clinics at 16 randomly selected health centres, were surveyed between May and August 2007 using the PRIME-MD questionnaire.Results There were 594 participants (the response rate was 92%), of whom 72.7% were female. Their ages ranged from 18 to 93 years, and 54.5% were over 50 years of age. In total, 37.2% were married and 25.9% were single. Indo-Trinidadians represented 43.1% and Afro-Trinidadians represented 36% of the study sample; 56.5% of the participants reported that their income was less than US$ 400 per month, and 65.7% were unemployed. At walk-in clinics in Trinidad, the estimated prevalence of severe undifferentiated somatoform disorder was 10.3% (95% CI: 7.86–12.74), that of hypochondriasis was 28.5% (95% CI: 24.9–32.1), and that of body dysmorphic disorder was 15.8% (95% CI: 11.9–18.7). Severe undifferentiated somatoform disorder was statistically significantly associated with gender and ethnicity but not with age, level of education, employment status or income. Chi-square testing found significant associations between the presence of severe undifferentiated somatoform disorder and both depression and anxiety (P < 0.05), between hypochondriasis and both anxiety and depression (P < 0.05), and between body dysmorphic disorder and depression (P < 0.05) but not anxiety. Regression analysis suggested that the demographic features that predicted severe undifferentiated somatoform disorder were being female or Indo-Trinidadian.Conclusions Walk-in clinics in Trinidad that serve older patients on a lower income have a high proportion of patients with somatoform disorders as measured by the PRIME-MD scale. These patients exhibit many features of anxiety and depression. These findings have implications for medical training and service delivery.     

Clinical Characteristics,Etiology and Antimicrobial Susceptibility among Overweight and Obese Individuals with Diarrhea: Observed at a Large Diarrheal Disease Hospital,Bangladesh

Background

The present study aimed to determine the clinical characteristics and etiology of overweight and obese (OO) individuals with diarrhea attending an urban Dhaka Hospital, International Centre for Diarrheal Disease Research (icddr,b), Bangladesh.

Methods

Total of 508 under-5 children, 96 individuals of 5–19 years and 1331 of >19 years were identified as OO from the Diarrheal Disease Surveillance System (DDSS) between 1993–2011. Two comparison groups such as well-nourished and malnourished individuals from respective age stratums were selected.

Results

Isolation rate of rotavirus was higher among OO under-5 children compared to malnourished group (46% vs. 28%). Rotavirus infection among OO individuals aged 5–19 years (9% vs. 3%) (9% vs. 3%) and >19 years (6% vs. 4%) (6% vs. 3%) was higher compared to well-nourished and malnourished children. Conversely, Vibrio cholerae was lower among all OO age groups compared to well-nourished and malnourished ones. Shigella (4% vs. 6%) (4% vs. 8%), and Campylobacter (3% vs. 5%) (3% vs. 5%) were lower only among OO in >19 years individuals compared to their counterparts of the same age stratum. Salmonella was similarly isolated in all age strata and nutritional groups. In multinomial logistic regression among under-5 children, significant association was observed only with use of antimicrobials at home [OR-1.97] and duration of hospital stay [OR-0.68]. For individuals aged 5–19 years, use of antimicrobials at home (OR-1.83), some or severe dehydration (OR-3.12), having received intravenous saline (OR-0.46) and rotavirus diarrhea (OR-2.96) were found to be associated with OO respectively. Moreover, significant associations were also found for duration of diarrhea before coming to hospital (>24 hours) (OR-1.24), Shigella (OR-0.46), and Campylobacter (OR-0.58) among >19 years OO individuals along with other associated co-variates in 5–19 years group (all p<0.05).

Conclusion and significance

Higher proportion of OO were infected with rotavirus and a greater proportion of them used antimicrobials before coming to the hospital.     

Fusing Data Mining,Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

Background

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

Methods

The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

Results

After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

Conclusion

The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.     

Leaf wax n‐alkane patterns of six tropical montane tree species show species‐specific environmental response

It remains poorly understood how the composition of leaf wax n‐alkanes reflects the local environment. This knowledge gap inhibits the interpretation of plant responses to the environment at the community level and, by extension, inhibits the applicability of n‐alkane patterns as a proxy for past environments. Here, we studied the n‐alkane patterns of five Miconia species and one Guarea species, in the Ecuadorian Andes (653–3,507 m a.s.l.). We tested for species‐specific responses in the average chain length (ACL), the C₃₁/(C₃₁ + C₂₉) ratio (ratio), and individual odd n‐alkane chain lengths across an altitudinally driven environmental gradient (mean annual temperature, mean annual relative air humidity, and mean annual precipitation). We found significant correlations between the environmental gradients and species‐specific ACL and ratio, but with varying magnitude and direction. We found that the n‐alkane patterns are species‐specific at the individual chain length level, which could explain the high variance in metrics like ACL and ratio. Although we find species‐specific sensitivity and responses in leaf n‐alkanes, we also find a general decrease in “shorter” (<C₂₉) and an increase in “longer” (>C₃₁) chain lengths with the environmental gradients, most strongly with temperature, suggesting n‐alkanes are useful for reconstructing past environments.     

Proteomic and microarray analyses of the Dictyostelium Zak1-GSK-3 signaling pathway reveal a role in early development

GskA, the Dictyostelium GSK-3 orthologue, is modified and activated by the dual-specificity tyrosine kinase Zak1, and the two kinases form part of a signaling pathway that responds to extracellular cyclic AMP. We identify potential cellular effectors for the two kinases by analyzing the corresponding null mutants. There are proteins and mRNAs that are altered in abundance in only one or the other of the two mutants, indicating that each kinase has some unique functions. However, proteomic and microarray analyses identified a number of proteins and genes, respectively, that are similarly misregulated in both mutant strains. The positive correlation between the array data and the proteomic data is consistent with the Zak1-GskA signaling pathway's functioning by directly or indirectly regulating gene expression. The discoidin 1 genes are positively regulated by the pathway, while the abundance of the H5 protein is negatively regulated. Two of the targets, H5 and discoidin 1, are well-characterized markers for early development, indicating that the Zak1-GskA pathway plays a role in development earlier than previously observed.     

A novel in vitro propagation system for West Indian elm [Guazuma ulmifolia Lam. (Malvaceae)]: a valuable medicinal woody species

In Vitro Cellular & Developmental Biology - Plant - The aim of this study was to establish a system of in vitro germination and propagation of Guazuma ulmifolia Lam. microcuttings (Malvaceae)....