Novel Characterization Of Thermal Temporal Summation Response By Analysis Of Continuous Pain Vs Time Curves And Exploratory Modeling.

BACKGROUND: Temporal summation (TS) refers to the increased perception of pain with repetitive noxious stimuli. While thermal TS is generally considered a behavioral correlate of spinal windup, noxious heat pulses also trigger additional sensory processes which were modeled in this study. METHODS: Nineteen healthy volunteers (9 females, mean age 29.2, SD 10.5) underwent two identical TS experiments, spaced a week apart. The TS paradigm consisted of 10 identical heat pulses with individualized temperatures at the thenar eminence (0.5Hz). We extracted 3 features from continuous TS response curves: Lag, time to first feel pain; Slope, the rate of pain increase between the first and most painful heat pulse; and Delta, the maximum drop in pain after peak pain is reached. We then examined the within-individual stability of these features, followed by the Pearson's correlations among these features and between the features and negative affect. RESULTS: All 3 features were stable over 1 week. Lag and Delta were negatively correlated (r = -0.5, p = 0.042). Slope did not correlate with Lag or Delta, but strongly correlated with a traditional TS measure, first pulse pain and peak pain difference (r = 0.91, p < 0.0001). Negative affects such as trait and state anxiety were negatively correlated with baseline (r = -0.49, p = 0.031) and peak stimulating temperature (r = -0.48, p = 0.039), respectively, suggesting an association between anxiety and greater pain sensitivity. CONCLUSION: We were able to decouple spinal windup from other perceptual processes generated by phasic thermal TS paradigms and demonstrate temporal stability of these curve features. These curve features may help better characterize the complex sensory response to noxious heat pulses and serve as biomarkers to profile patients with chronic pain.

Predicting complication risk in spine surgery: a prospective analysis of a novel risk assessment tool.

OBJECTIVE The ability to assess the risk of adverse events based on known patient factors and comorbidities would provide more effective preoperative risk stratification. Present risk assessment in spine surgery is limited. An adverse event prediction tool was developed to predict the risk of complications after spine surgery and tested on a prospective patient cohort. METHODS The spinal Risk Assessment Tool (RAT), a novel instrument for the assessment of risk for patients undergoing spine surgery that was developed based on an administrative claims database, was prospectively applied to 246 patients undergoing 257 spinal procedures over a 3-month period. Prospectively collected data were used to compare the RAT to the Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator. Study end point was occurrence and type of complication after spine surgery. RESULTS The authors identified 69 patients (73 procedures) who experienced a complication over the prospective study period. Cardiac complications were most common (10.2%). Receiver operating characteristic (ROC) curves were calculated to compare complication outcomes using the different assessment tools. Area under the curve (AUC) analysis showed comparable predictive accuracy between the RAT and the ACS NSQIP calculator (0.670 [95% CI 0.60-0.74] in RAT, 0.669 [95% CI 0.60-0.74] in NSQIP). The CCI was not accurate in predicting complication occurrence (0.55 [95% CI 0.48-0.62]). The RAT produced mean probabilities of 34.6% for patients who had a complication and 24% for patients who did not (p = 0.0003). The generated predicted values were stratified into low, medium, and high rates. For the RAT, the predicted complication rate was 10.1% in the low-risk group (observed rate 12.8%), 21.9% in the medium-risk group (observed 31.8%), and 49.7% in the high-risk group (observed 41.2%). The ACS NSQIP calculator consistently produced complication predictions that underestimated complication occurrence: 3.4% in the low-risk group (observed 12.6%), 5.9% in the medium-risk group (observed 34.5%), and 12.5% in the high-risk group (observed 38.8%). The RAT was more accurate than the ACS NSQIP calculator (p = 0.0018). CONCLUSIONS While the RAT and ACS NSQIP calculator were both able to identify patients more likely to experience complications following spine surgery, both have substantial room for improvement. Risk stratification is feasible in spine surgery procedures; currently used measures have low accuracy.

Predicting Occurrence of Spine Surgery Complications Using "Big Data" Modeling of an Administrative Claims Database.

BACKGROUND: Postoperative metrics are increasingly important in determining standards of quality for physicians and hospitals. Although complications following spinal surgery have been described, procedural and patient variables have yet to be incorporated into a predictive model of adverse-event occurrence. We sought to develop a predictive model of complication occurrence after spine surgery. METHODS: We used longitudinal prospective data from a national claims database and developed a predictive model incorporating complication type and frequency of occurrence following spine surgery procedures. We structured our model to assess the impact of features such as preoperative diagnosis, patient comorbidities, location in the spine, anterior versus posterior approach, whether fusion had been performed, whether instrumentation had been used, number of levels, and use of bone morphogenetic protein (BMP). We assessed a variety of adverse events. Prediction models were built using logistic regression with additive main effects and logistic regression with main effects as well as all 2 and 3-factor interactions. Least absolute shrinkage and selection operator (LASSO) regularization was used to select features. Competing approaches included boosted additive trees and the classification and regression trees (CART) algorithm. The final prediction performance was evaluated by estimating the area under a receiver operating characteristic curve (AUC) as predictions were applied to independent validation data and compared with the Charlson comorbidity score. RESULTS: The model was developed from 279,135 records of patients with a minimum duration of follow-up of 30 days. Preliminary assessment showed an adverse-event rate of 13.95%, well within norms reported in the literature. We used the first 80% of the records for training (to predict adverse events) and the remaining 20% of the records for validation. There was remarkable similarity among methods, with an AUC of 0.70 for predicting the occurrence of adverse events. The AUC using the Charlson comorbidity score was 0.61. The described model was more accurate than Charlson scoring (p < 0.01). CONCLUSIONS: We present a modeling effort based on administrative claims data that predicts the occurrence of complications after spine surgery. CLINICAL RELEVANCE: We believe that the development of a predictive modeling tool illustrating the risk of complication occurrence after spine surgery will aid in patient counseling and improve the accuracy of risk modeling strategies.

Diversification of the antigen-specific T cell receptor repertoire after varicella zoster vaccination.

Diversity and size of the antigen-specific T cell receptor (TCR) repertoire are two critical determinants for successful control of chronic infection. Varicella zoster virus (VZV) that establishes latency during childhood can escape control mechanisms, in particular with increasing age. We examined the TCR diversity of VZV-reactive CD4 T cells in individuals older than 50 years by studying three identical twin pairs and three unrelated individuals before and after vaccination with live attenuated VZV. Although all individuals had a small number of dominant T cell clones, the breadth of the VZV-specific repertoire differed markedly. A genetic influence was seen for the sharing of individual TCR sequences from antigen-reactive cells but not for repertoire richness or the selection of dominant clones. VZV vaccination favored the expansion of infrequent VZV antigen-reactive TCRs, including those from naïve T cells with lesser boosting of dominant T cell clones. Thus, vaccination does not reinforce the in vivo selection that occurred during chronic infection but leads to a diversification of the VZV-reactive T cell repertoire. However, a single-booster immunization seems insufficient to establish new clonal dominance. Our results suggest that repertoire analysis of antigen-specific TCRs can be an important readout to assess whether a vaccination was able to generate memory cells in clonal sizes that are necessary for immune protection.

High-throughput sequencing insights into T-cell receptor repertoire diversity in aging.

Decline in T-cell generation leading to T-cell receptor repertoire contraction is a cornerstone of immune system aging, and consequent disorders. High-throughput sequencing enables in-depth immune repertoire characterization, but blood samples are too small to capture its total diversity. New computational models could enable accurate estimation of this diversity.

Risk of cardiovascular events associated with current exposure to HIV antiretroviral therapies in a US veteran population.

BACKGROUND: To characterize the association of antiretroviral drug combinations on risk of cardiovascular events. METHODS: Certain antiretroviral medications for human immunodeficiency virus (HIV) have been implicated in increasing risk of cardiovascular disease. However, antiretroviral drugs are typically prescribed in combination. We characterized the association of current exposure to antiretroviral drug combinations on risk of cardiovascular events including myocardial infarction, stroke, percutaneous coronary intervention, and coronary artery bypass surgery. We used the Veterans Health Administration Clinical Case Registry to analyze data from 24 510 patients infected with HIV from January 1996 through December 2009. We assessed the association of current exposure to 15 antiretroviral drugs and 23 prespecified combinations of agents on the risk of cardiovascular event by using marginal structural models and Cox models extended to accommodate time-dependent variables. RESULTS: Over 164 059 person-years of follow-up, 934 patients had a cardiovascular event. Current exposure to abacavir, efavirenz, lamivudine, and zidovudine was significantly associated with increased risk of cardiovascular event, with odds ratios ranging from 1.40 to 1.53. Five combinations were significantly associated with increased risk of cardiovascular event, all of which involved lamivudine. One of these-efavirenz, lamivudine, and zidovudine-was the second most commonly used combination and was associated with a risk of cardiovascular event that is 1.60 times that of patients not currently exposed to the combination (odds ratio = 1.60, 95% confidence interval, 1.25-2.04). CONCLUSIONS: In the VA cohort, exposure to both individual drugs and drug combinations was associated with modestly increased risk of a cardiovascular event.

Diversity and clonal selection in the human T-cell repertoire.

T-cell receptor (TCR) diversity, a prerequisite for immune system recognition of the universe of foreign antigens, is generated in the first two decades of life in the thymus and then persists to an unknown extent through life via homeostatic proliferation of naïve T cells. We have used next-generation sequencing and nonparametric statistical analysis to estimate a lower bound for the total number of different TCR beta (TCRB) sequences in human repertoires. We arrived at surprisingly high minimal estimates of 100 million unique TCRB sequences in naïve CD4 and CD8 T-cell repertoires of young adults. Naïve repertoire richness modestly declined two- to fivefold in healthy elderly. Repertoire richness contraction with age was even less pronounced for memory CD4 and CD8 T cells. In contrast, age had a major impact on the inequality of clonal sizes, as estimated by a modified Gini-Simpson index clonality score. In particular, large naïve T-cell clones that were distinct from memory clones were found in the repertoires of elderly individuals, indicating uneven homeostatic proliferation without development of a memory cell phenotype. Our results suggest that a highly diverse repertoire is maintained despite thymic involution; however, peripheral fitness selection of T cells leads to repertoire perturbations that can influence the immune response in the elderly.

Insulin resistance: regression and clustering.

In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.

Assessing gene-level translational control from ribosome profiling.

MOTIVATION: The translational landscape of diverse cellular systems remains largely uncharacterized. A detailed understanding of the control of gene expression at the level of messenger RNA translation is vital to elucidating a systems-level view of complex molecular programs in the cell. Establishing the degree to which such post-transcriptional regulation can mediate specific phenotypes is similarly critical to elucidating the molecular pathogenesis of diseases such as cancer. Recently, methods for massively parallel sequencing of ribosome-bound fragments of messenger RNA have begun to uncover genome-wide translational control at codon resolution. Despite its promise for deeply characterizing mammalian proteomes, few analytical methods exist for the comprehensive analysis of this paired RNA and ribosome data. RESULTS: We describe the Babel framework, an analytical methodology for assessing the significance of changes in translational regulation within cells and between conditions. This approach facilitates the analysis of translation genome-wide while allowing statistically principled gene-level inference. Babel is based on an errors-in-variables regression model that uses the negative binomial distribution and draws inference using a parametric bootstrap approach. We demonstrate the operating characteristics of Babel on simulated data and use its gene-level inference to extend prior analyses significantly, discovering new translationally regulated modules under mammalian target of rapamycin (mTOR) pathway signaling control.

Risk of cardiovascular disease from antiretroviral therapy for HIV: a systematic review.

BACKGROUND: Recent studies suggest certain antiretroviral therapy (ART) drugs are associated with increases in cardiovascular disease. PURPOSE: We performed a systematic review and meta-analysis to summarize the available evidence, with the goal of elucidating whether specific ART drugs are associated with an increased risk of myocardial infarction (MI). DATA SOURCES: We searched Medline, Web of Science, the Cochrane Library, and abstract archives from the Conference on Retroviruses and Opportunistic Infections and International AIDS Society up to June 2011 to identify published articles and abstracts. STUDY SELECTION: Eligible studies were comparative and included MI, strokes, or other cardiovascular events as outcomes. DATA EXTRACTION: Eligibility screening, data extraction, and quality assessment were performed independently by two investigators. DATA SYNTHESIS: Random effects methods and Fisher's combined probability test were used to summarize evidence. FINDINGS: Twenty-seven studies met inclusion criteria, with 8 contributing to a formal meta-analysis. Findings based on two observational studies indicated an increase in risk of MI for patients recently exposed (usually defined as within last 6 months) to abacavir (RR 1.92, 95% CI 1.51-2.42) and protease inhibitors (PI) (RR 2.13, 95% CI 1.06-4.28). Our analysis also suggested an increased risk associated with each additional year of exposure to indinavir (RR 1.11, 95% CI 1.05-1.17) and lopinavir (RR 1.22, 95% CI 1.01-1.47). Our findings of increased cardiovascular risk from abacavir and PIs were in contrast to four published meta-analyses based on secondary analyses of randomized controlled trials, which found no increased risk from cardiovascular disease. CONCLUSION: Although observational studies implicated specific drugs, the evidence is mixed. Further, meta-analyses of randomized trials did not find increased risk from abacavir and PIs. Our findings that implicate specific ARTs in the observational setting provide sufficient evidence to warrant further investigation of this relationship in studies designed for that purpose.

Persistence versus reversion of 3TC resistance in HIV-1 determine the rate of emergence of NVP resistance.

When HIV-1 is exposed to lamivudine (3TC) at inhibitory concentrations, resistant variants carrying the reverse transcriptase (RT) substitution M184V emerge rapidly. This substitution confers high-level 3TC resistance and increased RT fidelity. We established a novel in vitro system to study the effect of starting nevirapine (NVP) in 3TC-resistant/NNRTI-naïve clinical isolates, and the impact of maintaining versus dropping 3TC pressure in this setting. Because M184V mutant HIV-1 seems hypersusceptible to adefovir (ADV), we also tested the effect of ADV pressure on the same isolates. We draw four conclusions from our experiments simulating combination therapy in vitro. (1) The presence of low-dose (1 µM) 3TC prevented reversal to wild-type from an M184V mutant background. (2) Adding low-dose 3TC in the presence of NVP delayed the selection of NVP-associated mutations. (3) The presence of ADV, in addition to NVP, led to more rapid reversal to wild-type at position 184 than NVP alone. (4) ADV plus NVP selected for greater numbers of mutations than NVP alone. Inference about the "selection of mutation" is based on two statistical models, one at the viral level, more telling, and the other at the level of predominance of mutation within a population. Multidrug pressure experiments lend understanding to mechanisms of HIV resistance as they bear upon new treatment strategies.

Significance analysis of xMap cytokine bead arrays.

Highly multiplexed assays using antibody coated, fluorescent (xMap) beads are widely used to measure quantities of soluble analytes, such as cytokines and antibodies in clinical and other studies. Current analyses of these assays use methods based on standard curves that have limitations in detecting low or high abundance analytes. Here we describe SAxCyB (Significance Analysis of xMap Cytokine Beads), a method that uses fluorescence measurements of individual beads to find significant differences between experimental conditions. We show that SAxCyB outperforms conventional analysis schemes in both sensitivity (low fluorescence) and robustness (high variability) and has enabled us to find many new differentially expressed cytokines in published studies.

Successive Standardization of Rectangular Arrays.

In this note we illustrate and develop further with mathematics and examples, the work on successive standardization (or normalization) that is studied earlier by the same authors in [1] and [2]. Thus, we deal with successive iterations applied to rectangular arrays of numbers, where to avoid technical difficulties an array has at least three rows and at least three columns. Without loss, an iteration begins with operations on columns: first subtract the mean of each column; then divide by its standard deviation. The iteration continues with the same two operations done successively for rows. These four operations applied in sequence completes one iteration. One then iterates again, and again, and again, … In [1] it was argued that if arrays are made up of real numbers, then the set for which convergence of these successive iterations fails has Lebesgue measure 0. The limiting array has row and column means 0, row and column standard deviations 1. A basic result on convergence given in [1] is true, though the argument in [1] is faulty. The result is stated in the form of a theorem here, and the argument for the theorem is correct. Moreover, many graphics given in [1] suggest that except for a set of entries of any array with Lebesgue measure 0, convergence is very rapid, eventually exponentially fast in the number of iterations. Because we learned this set of rules from Bradley Efron, we call it "Efron's algorithm". More importantly, the rapidity of convergence is illustrated by numerical examples.

SNPs and other features as they predispose to complex disease: genome-wide predictive analysis of a quantitative phenotype for hypertension.

Though recently they have fallen into some disrepute, genome-wide association studies (GWAS) have been formulated and applied to understanding essential hypertension. The principal goal here is to use data gathered in a GWAS to gauge the extent to which SNPs and their interactions with other features can be combined to predict mean arterial blood pressure (MAP) in 3138 pre-menopausal and naturally post-menopausal white women. More precisely, we quantify the extent to which data as described permit prediction of MAP beyond what is possible from traditional risk factors such as blood cholesterol levels and glucose levels. Of course, these traditional risk factors are genetic, though typically not explicitly so. In all, there were 44 such risk factors/clinical variables measured and 377,790 single nucleotide polymorphisms (SNPs) genotyped. Data for women we studied are from first visit measurements taken as part of the Atherosclerotic Risk in Communities (ARIC) study. We begin by assessing non-SNP features in their abilities to predict MAP, employing a novel regression technique with two stages, first the discovery of main effects and next discovery of their interactions. The long list of SNPs genotyped is reduced to a manageable list for combining with non-SNP features in prediction. We adapted Efron's local false discovery rate to produce this reduced list. Selected non-SNP and SNP features and their interactions are used to predict MAP using adaptive linear regression. We quantify quality of prediction by an estimated coefficient of determination (R(2)). We compare the accuracy of prediction with and without information from SNPs.

Parent-specific copy number in paired tumor-normal studies using circular binary segmentation.

MOTIVATION: High-throughput techniques facilitate the simultaneous measurement of DNA copy number at hundreds of thousands of sites on a genome. Older techniques allow measurement only of total copy number, the sum of the copy number contributions from the two parental chromosomes. Newer single nucleotide polymorphism (SNP) techniques can in addition enable quantifying parent-specific copy number (PSCN). The raw data from such experiments are two-dimensional, but are unphased. Consequently, inference based on them necessitates development of new analytic methods. METHODS: We have adapted and enhanced the circular binary segmentation (CBS) algorithm for this purpose with focus on paired test and reference samples. The essence of paired parent-specific CBS (Paired PSCBS) is to utilize the original CBS algorithm to identify regions of equal total copy number and then to further segment these regions where there have been changes in PSCN. For the final set of regions, calls are made of equal parental copy number and loss of heterozygosity (LOH). PSCN estimates are computed both before and after calling. RESULTS: The methodology is evaluated by simulation and on glioblastoma data. In the simulation, PSCBS compares favorably to established methods. On the glioblastoma data, PSCBS identifies interesting genomic regions, such as copy-neutral LOH. AVAILABILITY: The Paired PSCBS method is implemented in an open-source R package named PSCBS, available on CRAN (http://cran.r-project.org/).

Five blood pressure loci identified by an updated genome-wide linkage scan: meta-analysis of the Family Blood Pressure Program.

BACKGROUND: A preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension. METHODS: We performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226 African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican-American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups. RESULTS: Five quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score ≥3) in at least one meta-analysis and lod scores ≥1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses. CONCLUSIONS: The new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance.

SUCCESSIVE NORMALIZATION OF RECTANGULAR ARRAYS.

Standard statistical techniques often require transforming data to have mean 0 and standard deviation 1. Typically, this process of "standardization" or "normalization" is applied across subjects when each subject produces a single number. High throughput genomic and financial data often come as rectangular arrays, where each coordinate in one direction concerns subjects, who might have different status (case or control, say); and each coordinate in the other designates "outcome" for a specific feature, for example "gene," "polymorphic site," or some aspect of financial profile. It may happen when analyzing data that arrive as a rectangular array that one requires BOTH the subjects and features to be "on the same footing." Thus, there may be a need to standardize across rows and columns of the rectangular matrix. There arises the question as to how to achieve this double normalization. We propose and investigate the convergence of what seems to us a natural approach to successive normalization, which we learned from colleague Bradley Efron. We also study the implementation of the method on simulated data and also on data that arose from scientific experimentation.

Th17 and Th1 T-cell responses in giant cell arteritis.

BACKGROUND: In giant cell arteritis (GCA), vasculitic damage of the aorta and its branches is combined with a syndrome of intense systemic inflammation. Therapeutically, glucocorticoids remain the gold standard because they promptly and effectively suppress acute manifestations; however, they fail to eradicate vessel wall infiltrates. The effects of glucocorticoids on the systemic and vascular components of GCA are not understood. METHODS AND RESULTS: The immunoprofile of untreated and glucocorticoid-treated GCA was examined in peripheral blood and temporal artery biopsies with protein quantification assays, flow cytometry, quantitative real-time polymerase chain reaction, and immunohistochemistry. Plasma interferon-gamma and interleukin (IL)-17 and frequencies of interferon-gamma-producing and IL-17-producing T cells were markedly elevated before therapy. Glucocorticoid treatment suppressed the Th17 but not the Th1 arm in the blood and the vascular lesions. Analysis of monocytes/macrophages in the circulation and in temporal arteries revealed glucocorticoid-mediated suppression of Th17-promoting cytokines (IL-1beta, IL-6, and IL-23) but sparing of Th1-promoting cytokines (IL-12). In human artery-severe combined immunodeficiency mouse chimeras, in which patient-derived T cells cause inflammation of engrafted human temporal arteries, glucocorticoids were similarly selective in inhibiting Th17 cells and leaving Th1 cells unaffected. CONCLUSIONS: Two pathogenic pathways mediated by Th17 and Th1 cells contribute to the systemic and vascular manifestations of GCA. IL-17-producing Th17 cells are sensitive to glucocorticoid-mediated suppression, but interferon-gamma-producing Th1 responses persist in treated patients. Targeting steroid-resistant Th1 responses will be necessary to resolve chronic smoldering vasculitis. Monitoring Th17 and Th1 frequencies can aid in assessing disease activity in GCA.

Associations among multiple markers and complex disease: models, algorithms, and applications.

This chapter is a report on collaborations among its authors and others over many years. It devolves from our goal of understanding genes, their main and epistatic effects combined with interactions involving demographic and environmental features also, as together they predict genetically complex diseases. Thus, our goal is "association." Particular phenotypes of interest to us are hypertension, insulin resistance, angina, and myocardial infarction. Prediction of complex disease is notoriously difficult, though it would be made easier were we given strand-specific information on genotype. Unfortunately, with current technology, genotypic information comes to us "unphased." While obviously we have strand-specific information when genotype is homozygous, we do not have such information when genotype is heterozygous. To summarize, the ultimate goals of approaches we provide is to predict phenotype, typically untoward or not, within a specific window of time. Our approach is neither through linkage nor from finding haplotype frequencies per se.