The role of parametric linkage methods in complex trait analyses using microsatellites

Many investigators of complexly inherited familial traits bypass classical segregation analysis to perform model-free genome-wide linkage scans. Because model-based or parametric linkage analysis may be the most powerful means to localize genes when a model can be approximated, model-free statistics may result in a loss of power to detect linkage. We performed limited segregation analyses on the electrophysiological measurements that have been collected for the Collaborative Study on the Genetics of Alcoholism. The resulting models are used in whole-genome scans. Four genomic regions provided a model-based LOD > 2 and only 3 of these were detected (p < 0.05) by a model-free approach. We conclude that parametric methods, using even over-simplified models of complex phenotypes, may complement nonparametric methods and decrease false positives

Multiple genome-wide analyses of smoking behavior in the Framingham Heart Study

BACKGROUND: Cigarette smoking behavior may have a genetic basis. We assessed evidence for quantitative trait loci (QTLs) affecting the maximum number of cigarettes smoked per day, a trait meant to quantify this behavior, using data collected over 40 years as part of the Framingham Heart Study's original and offspring cohorts. RESULTS: Heritability was estimated to be approximately 21% using variance components (VC) methods (SOLAR), while oligogenic linkage and segregation analysis based on Bayesian Markov chain Monte Carlo (MCMC) methods (LOKI) estimated a mean of two large QTLs contributing approximately 28% and 20%, respectively, to the trait's variance. Genome-wide parametric (FASTLINK) and VC linkage analyses (SOLAR) revealed several LOD scores greater than 1.0, with peak LOD scores using both methods on chromosomes 2, 17, and 20; multi-point MCMC methods followed up on these chromosomes. The most robust linkage results were for a QTL between 65 and 84 cM on chromosome 20 with signals from multiple sex- and age-adjusted analyses including two-point LOD scores of 1.30 (parametric) and 1.07 (heritability = 0.17, VC) at 70.51 cM, a multi-point LOD score of 1.50 (heritability = 0.20, VC) at 84 cM, and an intensity ratio of 12.0 (MCMC) at 65 cM. CONCLUSION: Familial aggregation of the maximum number of cigarettes smoked per day was consistent with a genetic component to this behavior, and oligogenic segregation analyses using MCMC suggested two important QTLs. Linkage signals on chromosome 20 between 65 and 84 cM were seen using multiple analytical methods. No linkage result, however, met genome-wide statistical significance criteria, and the true relationship between these regions and smoking behavior remains unclear

Comparison of tagging single-nucleotide polymorphism methods in association analyses

Several methods to identify tagging single-nucleotide polymorphisms (SNPs) are in common use for genetic epidemiologic studies; however, there may be loss of information when using only a subset of SNPs. We sought to compare the ability of commonly used pairwise, multimarker, and haplotype-based tagging SNP selection methods to detect known associations with quantitative expression phenotypes. Using data from HapMap release 21 on unrelated Utah residents with ancestors from northern and western Europe (CEPH-Utah, CEU), we selected tagging SNPs in five chromosomal regions using ldSelect, Tagger, and TagSNPs. We found that SNP subsets did not substantially overlap, and that the use of trio data did not greatly impact SNP selection. We then tested associations between HapMap genotypes and expression phenotypes on 28 CEU individuals as part of Genetic Analysis Workshop 15. Relative to the use of all SNPs (n = 210 SNPs across all regions), most subset methods were able to detect single-SNP and haplotype associations. Generally, pairwise selection approaches worked extremely well, relative to use of all SNPs, with marked reductions in the number of SNPs required. Haplotype-based approaches, which had identified smaller SNP subsets, missed associations in some regions. We conclude that the optimal tagging SNP method depends on the true model of the genetic association (i.e., whether a SNP or haplotype is responsible); unfortunately, this is often unknown at the time of SNP selection. Additional evaluations using empirical and simulated data are needed

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

Generating a taxonomy for genetic conditions relevant to reproductive planning

As genome or exome sequencing (hereafter genome-scale sequencing) becomes more integrated into standard care, carrier testing is an important possible application. Carrier testing using genome-scale sequencing can identify a large number of conditions, but choosing which conditions/genes to evaluate as well as which results to disclose can be complicated. Carrier testing generally occurs in the context of reproductive decision-making and involves patient values in a way that other types of genetic testing may not. The Kaiser Permanente Clinical Sequencing Exploratory Research program is conducting a randomized clinical trial of preconception carrier testing that allows participants to select their preferences for results from among broad descriptive categories rather than selecting individual conditions. This paper describes 1) the criteria developed by the research team, the return of results committee (RORC), and stakeholders for defining the categories; 2) the process of refining the categories based on input from patient focus groups and validation through a patient survey; and, 3) how the RORC then assigned specific gene-condition pairs to taxonomy categories being piloted in the trial. The development of four categories (serious, moderate/mild, unpredictable, late onset) for sharing results allows patients to select results based on their values without separately deciding their interest in knowing their carrier status for hundreds of conditions. A fifth category, lifespan limiting, was always shared. The lessons learned may be applicable in other results disclosure situations, such as incidental findings

Association of early imaging for back pain with clinical outcomes in older adults

IMPORTANCE: In contrast to the recommendations for younger adults, many guidelines allow for older adults with back pain to undergo imaging without waiting 4 to 6 weeks. However, early imaging may precipitate interventions that do not improve outcomes. OBJECTIVE: To compare function and pain at the 12-month follow-up visit among older adults who received early imaging with those who did not receive early imaging after a new primary care visit for back pain without radiculopathy. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort of 5239 patients 65 years or older with a new primary care visit for back pain (2011-2013) in 3 US health care systems. We matched controls 1:1 using propensity score matching of demographic and clinical characteristics, including diagnosis, pain severity, pain duration, functional status, and prior resource use. EXPOSURES: Diagnostic imaging (plain films, computed tomography [CT], magnetic resonance imaging [MRI]) of the lumbar or thoracic spine within 6 weeks of the index visit. PRIMARY OUTCOME: back or leg pain-related disability measured by the modified Roland-Morris Disability Questionnaire (score range, 0-24; higher scores indicate greater disability) 12 months after enrollment. RESULTS: Among the 5239 patients, 1174 had early radiographs and 349 had early MRI/CT. At 12 months, neither the early radiograph group nor the early MRI/CT group differed significantly from controls on the disability questionnaire. The mean score for patients who underwent early radiography was 8.54 vs 8.74 among the control group (difference, -0.10 [95% CI, -0.71 to 0.50]; mixed model, P = .36). The mean score for the early MRI/CT group was 9.81 vs 10.50 for the control group (difference,-0.51 [-1.62 to 0.60]; mixed model, P = .18). CONCLUSIONS AND RELEVANCE: Among older adults with a new primary care visit for back pain, early imaging was not associated with better 1-year outcomes. The value of early diagnostic imaging in older adults for back pain without radiculopathy is uncertain

Patients' ratings of genetic conditions validate a taxonomy to simplify decisions about preconception carrier screening via genome sequencing

Advances in genome sequencing and gene discovery have created opportunities to efficiently assess more genetic conditions than ever before. Given the large number of conditions that can be screened, the implementation of expanded carrier screening using genome sequencing will require practical methods of simplifying decisions about the conditions for which patients want to be screened. One method to simplify decision making is to generate a taxonomy based on expert judgment. However, expert perceptions of condition attributes used to classify these conditions may differ from those used by patients. To understand whether expert and patient perceptions differ, we asked women who had received preconception genetic carrier screening in the last 3 years to fill out a survey to rate the attributes (predictability, controllability, visibility, and severity) of several autosomal recessive or X-linked genetic conditions. These conditions were classified into one of five taxonomy categories developed by subject experts (significantly shortened lifespan, serious medical problems, mild medical problems, unpredictable medical outcomes, and adult-onset conditions). A total of 193 women provided 739 usable ratings across 20 conditions. The mean ratings and correlations demonstrated that participants made distinctions across both attributes and categories. Aggregated mean attribute ratings across categories demonstrated logical consistency between the key features of each attribute and category, although participants perceived little difference between the mild and serious categories. This study provides empirical evidence for the validity of our proposed taxonomy, which will simplify patient decisions for results they would like to receive from preconception carrier screening via genome sequencing

Genome sequencing and carrier testing: decisions on categorization and whether to disclose results of carrier testing

We are investigating the use of genome sequencing for preconception carrier testing. Genome sequencing could identify one or more of thousands of X-linked or autosomal recessive conditions that could be disclosed during preconception or prenatal counseling. Therefore, a framework that helps both clinicians and patients understand the possible range of findings is needed to respect patient preferences by ensuring that information about only the desired types of genetic conditions are provided to a given patient