Multivariate finite mixture latent trajectory models with application to dementia studies

Indiana University-Purdue University Indianapolis (IUPUI)Dementia studies often collect multiple longitudinal neuropsychological measures in order to examine patients' decline across a number of cognitive domains. Dementia patients have shown considerable heterogeneities in individual trajectories of cognitive decline, with some patients showing rapid decline following diagnoses while others exhibiting slower decline or remain stable for several years. In the first part of this dissertation, a multivariate finite mixture latent trajectory model was proposed to identify longitudinal patterns of cognitive decline in multiple cognitive domains with multiple tests within each domain. The expectation-maximization (EM) algorithm was implemented for parameter estimation and posterior probabilities were estimated based on the model to predict latent class membership. Simulation studies demonstrated satisfactory performance of the proposed approach. In the second part, a simulation study was performed to compare the performance of information-based criteria on the selection of the number of latent classes. Commonly used model selection criteria including the Akaike information criterion (AIC), Bayesian information criterion (BIC), as well as consistent AIC (CAIC), sample adjusted BIC (SABIC) and the integrated classification likelihood criteria (ICLBIC) were included in the comparison. SABIC performed uniformly better in all simulation scenarios and hence was the preferred criterion for our proposed model. In the third part of the dissertation, the multivariate finite mixture latent trajectory model was extended to situations where the true latent class membership was known for a subset of patients. The proposed models were used to analyze data from the Uniform Data Set (UDS) collected from Alzheimer's Disease Centers across the country to identify various cognitive decline patterns among patients with dementia

A multivariate finite mixture latent trajectory model with application to dementia studies

Dementia patients exhibit considerable heterogeneity in individual trajectories of cognitive decline, with some patients showing rapid decline following diagnoses while others exhibiting slower decline or remaining stable for several years. Dementia studies often collect longitudinal measures of multiple neuropsychological tests aimed to measure patients’ decline across a number of cognitive domains. We propose a multivariate finite mixture latent trajectory model to identify distinct longitudinal patterns of cognitive decline simultaneously in multiple cognitive domains, each of which is measured by multiple neuropsychological tests. EM algorithm is used for parameter estimation and posterior probabilities are used to predict latent class membership. We present results of a simulation study demonstrating adequate performance of our proposed approach and apply our model to the Uniform Data Set from the National Alzheimer's Coordinating Center to identify cognitive decline patterns among dementia patients

Multi-layered map based navigation and interaction for an intelligent wheelchair

Intelligent wheelchair is a paradigm of assisted living applications for elderly and disabled people. Its autonomous navigation and human-robot interaction is the major challenge. The previous intelligent wheelchair research has been mainly focused on geometric map based navigation, which is computational expensive in a large scale environment. This paper proposes the use of multi-layered maps for navigation and interaction of an intelligent wheelchair. The semantic information can improve the efficiency of path planning and navigation as well as extend the capability of task planning for the wheelchair. Some experimental results are given to demonstrate the feasibility and performance of the proposed approach

Steroid Pathway Genes and Neonatal Respiratory Distress After Betamethasone Use in Anticipated Preterm Birth

Objective: To test several key glucocorticoid genes that are enhanced in lung development for associations with respiratory distress syndrome (RDS) after antenatal corticosteroid use. Methods: A prospective cohort of women received betamethasone to accelerate fetal lung maturity for threatened preterm delivery. DNA was obtained from mothers and newborns. Neonatal RDS was the primary outcome. Genotyping for single-nucleotide polymorphisms (SNPs) in 68 glucocorticoid genes found to be differentially expressed during lung development was performed. Multivariable analysis tested for associations of SNPs in the candidate genes with RDS. Results: Genotypic results for 867 SNPs in 96 mothers and 73 babies were included. Thirty-nine (53.4%) babies developed RDS. Maternal SNPs in the centromeric protein E (CENPE), GLRX, CD9, and AURKA genes provided evidence of association with RDS (P < .01). In newborns, SNPs in COL4A3, BHLHE40, and SRGN provided evidence of association with RDS (P < .01). Conclusion: Single-nucleotide polymorphisms in several glucocorticoid responsive genes suggest association with neonatal RDS after antenatal corticosteroid use

Fine mapping and expression of candidate genes within the chromosome 10 QTL region of the high and low alcohol-drinking rats

The high and low alcohol-drinking (HAD and LAD) rats were selectively bred for differences in alcohol intake. The HAD/LAD rats originated from the N/Nih heterogeneous stock developed from intercrossing eight inbred rat strains. The HAD×LAD F2 were genotyped, and a powerful analytical approach, using ancestral recombination and F2 recombination, was used to narrow a quantitative trait loci (QTL) for alcohol drinking to a 2-cM region on distal chromosome 10 that was in common in the HAD1/LAD1 and HAD2/LAD2 analyses. Quantitative real-time PCR was used to examine mRNA expression of six candidate genes (Crebbp, Trap1, Gnptg, Clcn7, Fahd1, and Mapk8ip3) located within the narrowed QTL region in the HAD1/LAD1 rats. Expression was examined in five brain regions, including the nucleus accumbens, amygdala, caudate putamen, hippocampus, and prefrontal cortex. All six genes showed differential expression in at least one brain region. Of the genes tested in this study, Crebbp and Mapk8ip3 may be the most promising candidates with regard to alcohol drinking

Genome-wide association study of serum iron phenotypes in premenopausal women of European descent

A genome-wide association study was performed in 1,130 premenopausal women to detect common variants associated with three serum iron-related phenotypes. Total iron binding capacity was strongly associated (p=10−14) with variants in and near the TF gene (transferrin), the serum iron transporting protein, and with variants in HFE (p= 4×10−7), which encodes the human hemochromatosis gene. Association was also detected between percent iron saturation (p=10−8) and variants in the chromosome 6 region containing both HFE and SLC17A2, which encodes a phosphate transport protein. No significant associations were detected with serum iron, but variants in HFE were suggestive (p=10−6). Our results corroborate prior studies in older subjects and demonstrate that the association of these genetic variants with iron phenotypes can be detected in premenopausal women

A regulatory variant of CHRM3 is associated with cannabis-induced hallucinations in European Americans

Cannabis, the most widely used illicit drug, can induce hallucinations. Our understanding of the biology of cannabis-induced hallucinations (Ca-HL) is limited. We used the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) to identify cannabis-induced hallucinations (Ca-HL) among long-term cannabis users (used cannabis ≥1 year and ≥100 times). A genome-wide association study (GWAS) was conducted by analyzing European Americans (EAs) and African Americans (AAs) in Yale-Penn 1 and 2 cohorts individually, then meta-analyzing the two cohorts within population. In the meta-analysis of Yale-Penn EAs (n = 1917), one genome-wide significant (GWS) signal emerged at the CHRM3 locus, represented by rs115455482 (P = 1.66 × 10-10), rs74722579 (P = 2.81 × 10-9), and rs1938228 (P = 1.57 × 10-8); signals were GWS in Yale-Penn 1 EAs (n = 1092) and nominally significant in Yale-Penn 2 EAs (n = 825). Two SNPs, rs115455482 and rs74722579, were available from the Collaborative Study on the Genetics of Alcoholism data (COGA; 3630 long-term cannabis users). The signals did not replicate, but when meta-analyzing Yale-Penn and COGA EAs, the two SNPs' association signals were increased (meta-P-values 1.32 × 10-10 and 2.60 × 10-9, respectively; n = 4291). There were no significant findings in AAs, but in the AA meta-analysis (n = 3624), nominal significance was seen for rs74722579. The rs115455482*T risk allele was associated with lower CHRM3 expression in the thalamus. CHRM3 was co-expressed with three psychosis risk genes (GABAG2, CHRNA4, and HRH3) in the thalamus and other human brain tissues and mouse GABAergic neurons. This work provides strong evidence for the association of CHRM3 with Ca-HL and provides insight into the potential involvement of thalamus for this trait

Calcium-Sensing Receptor Genotype and Response to Cinacalcet in Patients Undergoing Hemodialysis

BACKGROUND AND OBJECTIVES: We tested the hypothesis that single nucleotide polymorphisms (SNPs) in the calcium-sensing receptor (CASR) alter the response to the calcimimetic cinacalcet. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We analyzed DNA samples in the Evaluation of Cinacalcet HCl Therapy to Lower Cardiovascular Events (EVOLVE) trial, a randomized trial comparing cinacalcet to placebo on a background of usual care. Of the 3883 patients randomized, 1919 (49%) consented to DNA collection, and samples from 1852 participants were genotyped for 18 CASR polymorphisms. The European ancestry (EA; n=1067) and African ancestry (AfAn; n=405) groups were assessed separately. SNPs in CASR were tested for their association with biochemical measures of mineral metabolism at baseline, percent change from baseline to 20 weeks, and risk of clinical fracture as dependent variables. RESULTS: There were modest associations of CASR SNPs with increased baseline serum parathyroid hormone and bone alkaline phosphatase primarily with the minor allele in the EA group (all P≤0.03), but not in the AfAn sample. In contrast, there was a modest association of decreased baseline serum calcium and FGF23 with CASR SNPs (P=0.04) primarily with the minor allele in the AfAn but not in the EA sample. The minor allele of two SNPs was associated with decreased percent reduction in parathyroid hormone from baseline to 20 weeks in the EA population (P<0.04) and this was not altered with cinacalcet. In both EA and AfAn, the same SNP (rs9740) was associated with decreased calcium with cinacalcet treatment (EA and AfAn P≤0.03). Three SNPs in high linkage disequilibrium were associated with a higher risk of clinical fracture that was attenuated by cinacalcet treatment in the EA sample (P<0.04). CONCLUSIONS: These modest associations, if validated, may provide explanations for differences in CKD-mineral bone disorder observed in EA and AfAn populations, and for differential biochemical responses to calcimimetics

Exome Sequencing Identifies Candidate Genetic Modifiers of Syndromic and Familial Thoracic Aortic Aneurysm Severity

Thoracic aortic aneurysm (TAA) is a genetic disease predisposing to aortic dissection. It is important to identify the genetic modifiers controlling penetrance and expressivity to improve clinical prognostication. Exome sequencing was performed in 27 subjects with syndromic or familial TAA presenting with extreme phenotypes (15 with severe TAA; 12 with mild or absent TAA). Family-based analysis of a subset of the cohort identified variants, genes, and pathways segregating with TAA severity among three families. A rare missense variant in ADCK4 (p.Arg63Trp) segregated with mild TAA in each family. Genes and pathways identified in families were further investigated in the entire cohort using the optimal unified sequence kernel association test, finding significance for the gene COL15A1 (p = 0.025) and the retina homeostasis pathway (p = 0.035). Thus, we identified candidate genetic modifiers of TAA severity by exome-based study of extreme phenotypes, which may lead to improved risk stratification and development of new medical therapies

SIBLING Family Genes and Bone Mineral Density: Association and Allele-specific Expression in Humans

Osteoporosis is a common complex disorder with reduced bone mineral density (BMD) and increased susceptibility to fracture. Peak BMD is one of the primary determinants of osteoporotic fracture risk, and is under substantial genetic control. Extracellular matrix, a major component of bone, influences BMD by regulating mineral deposition and maintaining cellular activity. It contains several SIBLING family proteins, null mutations of which cause mineralization defects in humans. In this study, we tested 59 single-nucleotide polymorphisms (SNPs) located in the 5 SIBLING family genes (DSPP, DMP1, IBSP, MEPE and SPP1) for association with normal variation in peak BMD in healthy men and women. We measured femoral neck (FN) and lumbar spine (LS) areal BMD by dual energy x-ray absorptiometry (DXA) in 1,692 premenopausal European-American women, 512 premenopausal African-American women and 715 European-American men. SNPs were tested for association with FN and LS BMD in the 3 subsamples. In the European-American women, we observed association (p≤0.005) with LS-BMD for SNPs in DSPP, IBSP and MEPE, and for FN-BMD with SNPs in DMP1 and IBSP. Allele specific regulation of gene expression (ASE) is an important mechanism in which an allele giving rise to modest influence in transcript abundance might result in a predisposition to disease. To identify whether there was ASE of SIBLING family genes at these SNPs, we examined 52 human bone samples obtained from the femoral neck during surgical hip replacement (27 female, 25 male; 44 European-American and 8 African-American). We observed unidirectional ASE for the IBSP gene, with lower expression of the G allele compared to the A allele for SNP rs17013181. Our data suggest that SNPs within the SIBLING genes may contribute to normal variation of peak BMD. Further studies are necessary to identify the functional variants and to determine the mechanisms underlying the differences in ASE and how these differences relate to the pathophysiology of osteoporosis