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PubMed2004

Assignment of canine MSS1 microsatellite markers to chromosomes by linkage data.

Recent advances in mapping the canine genome have led to an increase in the number of linkage studies aimed at dissecting the genetic causes of many hereditary diseases that affect the domestic dog. The first step in developing molecular tools for a whole genome scan was the characterization of a set of microsatellite markers, termed minimal screening set 1 (MSS1), that provided an estimated coverage of 10 cM. A limiting factor in use of the MSS1 is not all of the 172 MSS1 markers have been localized to specific chromosomes. Seventy-five of the markers were positioned on a total of 15 chromosomes with the original publication of the MSS1. The localization based on linkage data of 14 additional MSS1 markers to chromosomes using CRIMAP v. 2.4 to build a linkage map of 113 MSS1 markers that were polymorphic in a kindred of Dalmatians is reported here.

Animals↗
PubMed1989

Linkage data on affective disorders in an epidemiologic context.

Recent data on chromosomal linkage markers in affective disorders indicate that single locus inheritance is involved in these disorders. The presence of a single locus has not been detectable using segregation analysis on family study data from large populations, possibly because of both heterogeneity and birth cohort and sex differences in diagnostic frequencies.

Affective Disorders, Psychotic↗
PubMed2006

Data linkage enables evaluation of long-term survival after intensive care.

Outcomes of intensive care are important to the patient and for assessment of benefit. Short-term outcomes after critical illness are well described, but less is known about long-term outcomes. This study describes the use of data linkage, combining intensive care unit (ICU) clinical data with administrative morbidity and mortality data, to assess long-term outcomes after treatment in ICU. The hospital-based cohort study was conducted in a 22-bed general ICU in a metropolitan teaching hospital. All patient admissions admitted to ICU from 1 January 1987 to 31 December 2002 were included. The prospective ICU clinical database with patient demographics, ICU diagnoses, severity of illness, daily assessment of organ failures and common daily treatments used was linked using probabilistic methods to the state-wide hospital morbidity and mortality databases to describe long-term survival. There were 26,019 ICU admissions (22,980 patients) with 25,972 records (99.8%) linked to a hospitalization event that included the index ICU admission. Unadjusted survival was 84.7% at 1 year decreasing progressively to 50.7% at 15 years. Age, type of admission, severity of illness (measured by Acute Physiologic and Chronic Health Evaluation (APACHE) II and the presence of organ failure), ICU length of stay, comorbidity (Chronic Health Evaluation and Charlson comorbidity index) and ICU admission diagnosis, were all associated with survival at 1, 3, 5, 10, and 15 year follow-up (P<0.001 at all time points). Linkage of clinical and administrative data provides a feasible method for ascertaining long-term survival after critical illness. Age, admission severity of illness, diagnosis and comorbidity influenced long-term unadjusted survival.

APACHE↗
PubMed2000

A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data.

The identification of genes contributing to complex diseases and quantitative traits requires genetic data of high fidelity, because undetected errors and mutations can profoundly affect linkage information. The recent emphasis on the use of the sibling-pair design eliminates or decreases the likelihood of detection of genotyping errors and marker mutations through apparent Mendelian incompatibilities or close double recombinants. In this article, we describe a hidden Markov method for detecting genotyping errors and mutations in multilocus linkage data. Specifically, we calculate the posterior probability of genotyping error or mutation for each sibling-pair-marker combination, conditional on all marker data and an assumed genotype-error rate. The method is designed for use with sibling-pair data when parental genotypes are unavailable. Through Monte Carlo simulation, we explore the effects of map density, marker-allele frequencies, marker position, and genotype-error rate on the accuracy of our error-detection method. In addition, we examine the impact of genotyping errors and error detection and correction on multipoint linkage information. We illustrate that even moderate error rates can result in substantial loss of linkage information, given efforts to fine-map a putative disease locus. Although simulations suggest that our method detects </=50% of genotyping errors, it generally flags those errors that have the largest impact on linkage results. For high-resolution genetic maps, removal of the errors identified by our method restores most or nearly all the lost linkage information and can be accomplished without generating false evidence for linkage by removing incorrectly identified errors.

Alleles↗
PubMed1984

A computer program for constructing a maximum-likelihood map from linkage data and its application to human chromosome 1.

An algorithm is described which attempts to find the maximum likelihood order of the loci on a chromosome using linkage data. It can also use data on locus order if these are available. A computer program which applies this algorithm has been written, and tested on the data for human chromosome 1. The most likely possible order is GDH, PGD, ENO1, Rh, UMPK, Sc, PGM1, AMY, Fy, CAE, 1qh, CMT1, AT3, PEPC.

Chromosome Mapping↗
PubMed2006

Using data linkage to generate 30-day crash-fatality adjustment factors for Taiwan.

Different countries have their own police reporting time standards for counting the number of fatalities in reported crashes. A rapid estimation method (such as adjustment factor) for the comparison is important. The data-linkage technique was used to combine police-reported crash data and vital registration data, in order to generate 30-day fatality adjustment factors for various reporting time standards, which could also shed light on the fatal injury trend over time. The major findings were as follows. Firstly, a conservative 30-day fatality adjustment factor for the first day (or 24 h) would be 1.54 (or 1.35) in an area with a large motorcycle population, like Taiwan. This produced 20-40% higher 30-day fatalities than UK Transport Research Laboratory predicted, and 15-25% higher fatalities than those in Europe/Japan. Secondly, after excluding motorcycle impacts, the Taiwanese factors suggested 8-14% higher fatalities within 30 days than those in Europe/Japan. Third, motorcycle fatalities influenced the overall 30-day fatality trend within 3 days. In the future, both the police under-reporting problem and the motorcycle/overall fatal injury pattern within 3 days after crashing in developing countries like Taiwan merit further investigation.

Accidents, Traffic↗
PubMed1992

Systematic detection of errors in genetic linkage data.

Construction of dense genetic linkage maps is hampered, in practice, by the occurrence of laboratory typing errors. Even relatively low error rates cause substantial map expansion and interfere with the determination of correct genetic order. Here, we describe a systematic method for overcoming these difficulties, based on incorporating the possibility of error into the usual likelihood model for linkage analysis. Using this approach, it is possible to construct genetic maps allowing for error and to identify the typings most likely to be in error. The method has been implemented for F2 intercrosses between two inbred strains, a situation relevant to the construction of genetic maps in experimental organisms. Tests involving both simulated and real data are presented, showing that the method detects the vast majority of errors.

Animals↗
PubMed2000

Monitoring disease burden and preventive behavior with data linkage: cervical cancer among aboriginal people in Manitoba, Canada.

OBJECTIVES: This study sought to estimate rates of cervical cancer and Papanicolaou testing among Aboriginal and non-Aboriginal women in Manitoba, Canada. METHODS: Data were derived through linking of administrative databases. RESULTS: In comparison with non-Aboriginal women, Aboriginal women had 1.8 and 3.6 times the age-standardized incidence rates of in situ and invasive cervical cancer, respectively. With the exception of those aged 15 to 19 years, Aboriginal women were less likely to have had at least 1 Papanicolaou test in the preceding 3 years. CONCLUSIONS: Data linkage provides a rapid and inexpensive means to estimate disease burden and preventive behavior in the absence of registries. There is an urgent need for an organized Papanicolaou test screening program in the Aboriginal population.

Adolescent↗
PubMed1997

Data linkage methods used in maternally-linked birth and infant death surveillance data sets from the United States (Georgia, Missouri, Utah and Washington State), Israel, Norway, Scotland and Western Australia.

In this paper we describe the methods used to link birth and infant mortality and morbidity surveillance data sets into sibships using deterministic or multistage probabilistic linkage methods. We describe nine linked data sets: four in the United States (Georgia, Missouri, Utah and Washington State), and four elsewhere (Scotland, Norway, Israel and Western Australia). Norway and Israel use deterministic methods to link births and deaths into sibships. The deterministic linkage is usually dependent on the availability of national identification numbers. In both countries they assign these numbers at birth. Deterministic linkage is usually highly successful, and the major problem is the validation of linkages. In the United States, Western Australia and UK linkage is multistage and probabilistic. This approach is usually dependent on the calculation linkage weights from sociodemographic variables. The success rates of probabilistic methods are above 80%. Maternally-linked perinatal data open new vistas for epidemiological research. Recurrence of poor perinatal outcomes is more appropriately studied using longitudinally-linked data sets. In addition, the emergence of risk factors and the recurrence of risk factors can be studied.

Epidemiologic Methods↗
PubMed2002

Antibiotic prescribing and admissions with major suppurative complications of respiratory tract infections: a data linkage study.

BACKGROUND: Systematic reviews of antibiotic treatment of common acute respiratory tract infections (RTIs) suggest modest symptomatic benefit, but provide limited evidence that prescribing prevents complications. AIM: To assess the relationship between penicillin prescribing (the most commonly used group of antibiotics for RTIs) and hospital admission with complications. DESIGN OF STUDY: Data linkage study. SETTING: Ninety-six health authorities of England for the year 1997-1998. METHOD: Hospital admissions related to RTIs were linked with prescribing analysis and cost (PACT) data. RESULTS: There was close correlation between items of penicillin use and total antibiotic use (r = 0.96). After controlling for SMR, age, sex, and Townsend score, a one-unit increase in penicillin use (items dispensed per capita) was associated with a reduction in annual incidence per 10,000 of admissions for quinsy (-3.55 admissions, 95% confidence interval [CI] = -6.85 to -0.26), and mastoiditis (square root of incidence of admissions = -1.05, 95% CI = -1.82 to -0.27). This does not represent lower referral thresholds among higher prescribers as higher prescribing was associated with more admissions for tonsillectomy and overall admissions. Increasing prescribing by 2000 items of penicillin for a practice of 10,000 patients could possibly prevent one admission for either mastoiditis or quinsy. CONCLUSION: Higher antibiotic prescribing is associated with significantly fewer admissions with major complications. However, the overall size of the effect is modest and it is difficult to advocate an overall increase in prescribing to prevent complications. Future research should concentrate on finding better methods of targeting antibiotics to individuals at risk of poor outcome.

Acute Disease↗
PubMed1993

Statistical evaluation of multiple-locus linkage data in experimental species and its relevance to human studies: application to nonobese diabetic (NOD) mouse and human insulin-dependent diabetes mellitus (IDDM).

Common, familial human disorders generally do not follow Mendelian inheritance patterns, presumably because multiple loci are involved in disease susceptibility. One approach to mapping genes for such traits in humans is to first study an analogous form in an animal model, such as mouse, by using inbred strains and backcross experiments. Here we describe methodology for analyzing multiple-locus linkage data from such experimental backcrosses, particularly in light of multilocus genetic models, including the effects of epistasis. We illustrate these methods by using data from backcrosses involving nonobese diabetic mouse, which serves as an animal model for human insulin-dependent diabetes mellitus. We show that it is likely that a minimum of nine loci contribute to susceptibility, with strong epistasis effects among these loci. Three of the loci actually confer a protective effect in the homozygote, compared with the heterozygote. Further, we discuss the relevance of these studies for analogous studies of the human form of the trait. Specifically, we show that the magnitude of the gene effect in the experimental backcross is likely to correlate only weakly, at best, with the expected magnitude of effect for a human form, because in humans the gene effect will depend more heavily on disease allele frequencies than on the observed penetrance ratios; such allele frequencies are unpredictable. Hence, the major benefit from animal studies may be a better understanding of the disease process itself, rather than identification of cells through comparison mapping in humans by using regions of homology.

Animals↗
PubMed1990

Genetic counseling in rare syndromes: a resampling method for determining an approximate confidence interval for gene location with linkage data from a single pedigree.

Multipoint linkage analysis is a powerful method for mapping a rare disease gene on the human gene map despite limited genotype and pedigree data. However, there is no standard procedure for determining a confidence interval for gene location by using multipoint linkage analysis. A genetic counselor needs to know the confidence interval for gene location in order to determine the uncertainty of risk estimates provided to a consultant on the basis of DNA studies. We describe a resampling, or "bootstrap," method for deriving an approximate confidence interval for gene location on the basis of data from a single pedigree. This method was used to define an approximate confidence interval for the location of a gene causing nonsyndromal X-linked mental retardation in a single pedigree. The approach seemed robust in that similar confidence intervals were derived by using different resampling protocols. Quantitative bounds for the confidence interval were dependent on the genetic map chosen. Once an approximate confidence interval for gene location was determined for this pedigree, it was possible to use multipoint risk analysis to estimate risk intervals for women of unknown carrier status. Despite the limited genotype data, the combination of the resampling method and multipoint risk analysis had a dramatic impact on the genetic advice available to consultants.

Chromosome Mapping↗
PubMed1969

Patient identification for computer data linkage.

To permit linkage of computerized patient data obtained from different sources, a universal and efficient method of patient identification is necessary. A coding system of 16 characters with a high degree of discrimination is proposed. The first five characters code the individual's family name, the next four his given name; the next six digits are his date of birth expressed in day, month and year; and the last character codes his sex. This system, using readily available patient information, is simple to manipulate and generates codes that are also medically informative. When this method of identification was tested on a list of 18,000 persons, no identical codes were found.

Canada↗
PubMed2004

Organizing population data into complex family pedigrees: application of a second-order data linkage to state birth defects registries.

Researchers and health officials are increasingly using electronic linkage of large-scale health data systems as a tool for assembling a comprehensive picture of birth defects at a population level. Current linkage and database techniques are limited to first-order linkage--linking information on a single individual in one database with information on that same individual in another database. For example, while current strategies may indicate whether a child with a certain birth defect also has a specific metabolic disorder or risk factor, they are unable to readily determine whether he or she also has any siblings or other relatives with the same pattern. In contrast, the current manuscript proposes a second-order linkage--one that organizes data so that individual-level data can readily be organized into families or extended family pedigrees across an entire population. The ability to link and organize population data into family pedigrees can have significant, broad impact upon health research and service delivery. This can lead to large-scale analysis of genetic factors and, with the linking of environmental data, the potential for large-scale studies of gene-environment interactions. In addition, it expands the potential for epidemiological research by readily allowing the examination of familial effects upon population rates of birth defects, and provides valuable information that can assist in applied public health. An example of a second order database incorporating an electronic birth defects registry is presented.

Congenital Abnormalities↗
PubMed1986

Detecting linkage for genetically heterogeneous diseases and detecting heterogeneity with linkage data.

Interest in searching for genetic linkage between diseases and marker loci has been greatly increased by the recent introduction of DNA polymorphisms. However, even for the most well-behaved Mendelian disorders, those with clear-cut mode of inheritance, complete penetrance, and no phenocopies, genetic heterogeneity may exist; that is, in the population there may be more than one locus that can determine the disease, and these loci may not be linked. In such cases, two questions arise: (1) What sample size is necessary to detect linkage for a genetically heterogeneous disease? (2) What sample size is necessary to detect heterogeneity given linkage between a disease and a marker locus? We have answered these questions for the most important types of matings under specified conditions: linkage phase known or unknown, number of alleles involved in the cross at the marker locus, and different numbers of affected and unaffected children. In general, the presence of heterogeneity increases the recombination value at which lod scores peak, by an amount that increases with the degree of heterogeneity. There is a corresponding increase in the number of families necessary to establish linkage. For the specific case of backcrosses between disease and marker loci with two alleles, linkage can be detected at recombination fractions up to 20% with reasonable numbers of families, even if only half the families carry the disease locus linked to the marker. The task is easier if more than two informative children are available or if phase is known. For recessive diseases, highly polymorphic markers with four different alleles in the parents greatly reduce the number of families required.

Alleles↗
PubMed1996

Data linkages for research on outcomes of long-term care.

Medicaid claims were linked with a sample of data gathered for nursing home quality assurance and case mix reimbursement (N = 14,917). This generated patient level records of medical resource use combined with standardized assessments of health and functional status. We describe the linkage process and the characteristics of the combined set of information-its strengths, limitations, and potential uses. The two data sources, one cross-sectional and the other longitudinal, complemented one another and provided a more complete description of patient resource use and health status. However, methodological and ethical issues must be resolved before data linkages are used routinely for research.

Activities of Daily Living↗
PubMed1991

A maximum likelihood method for estimating genome length using genetic linkage data.

The genetic length of a genome, in units of Morgans or centimorgans, is a fundamental characteristic of an organism. We propose a maximum likelihood method for estimating this quantity from counts of recombinants and nonrecombinants between marker locus pairs studied from a backcross linkage experiment, assuming no interference and equal chromosome lengths. This method allows the calculation of the standard deviation of the estimate and a confidence interval containing the estimate. Computer simulations have been performed to evaluate and compare the accuracy of the maximum likelihood method and a previously suggested method-of-moments estimator. Specifically, we have investigated the effects of the number of meioses, the number of marker loci, and variation in the genetic lengths of individual chromosomes on the estimate. The effect of missing data, obtained when the results of two separate linkage studies with a fraction of marker loci in common are pooled, is also investigated. The maximum likelihood estimator, in contrast to the method-of-moments estimator, is relatively insensitive to violation of the assumptions made during analysis and is the method of choice. The various methods are compared by application to partial linkage data from Xiphophorus.

Animals↗
PubMed2006

Increased mortality in rural vehicular trauma: identifying contributing factors through data linkage.

BACKGROUND: Fatality rates from rural vehicular trauma are almost double those found in urban settings. Causes of this difference in rural and urban trauma fatality rates have yet to be fully explored. The purpose of this study is to identify prehospital causes of the higher rural fatality rates by linking, analyzing, and comparing prehospital data for rural and urban vehicular crashes. METHODS: A probabilistic algorithm was developed that permitted linkage of data from police motor vehicle crash reports, and from Emergency Medical Service (EMS), and hospital records. Motor vehicle crashes (MVCs) were defined as rural or urban by location of the crash using the United States Bureau of Census criteria. Areas that fell outside that urban definition were defined as rural. Linked data were analyzed to identify factors that were thought to be associated with the higher mortality rates observed in rural settings. RESULTS: During the 20-month period from November 2001 through May 2003, data were collected from police crash reports and EMS Patient Care Reports (PCRs) within seven counties in southwest Alabama. Using high probability match criteria and join specifications, 4,694 police crash reports were linked to EMS PCRs. Of these, 3,068 patients (65.4%) were injured in rural settings, and 1,626 (34.6%) were injured in urban settings. A total of 164 (3.5%) mortalities were identified. A total of 129 (4.2%) mortalities occurred in a rural setting and 35 (2.1%) were urban (p = 0.0001). Of the 129 rural deaths, 91 (70.5%) were dead on scene (DOS) and of 35 urban deaths, 20 (57.1%) were DOS (p < 0.0001). Mean EMS response time for rural MVCs with survivors was 11.2 minutes versus a mean of 13.9 minutes for rural MVC with survivors (p < 0.0002). When survivors were involved, mean EMS response time for an urban setting was 6.8 minutes versus 13.9 minutes for a rural setting (p < 0.0001). In a rural setting, mean EMS distance to the scene when patients were alive was 7.7 miles versus 10.5 miles when patients were DOS (p < 0.001). For patients who died after transfer from the scene, mean rural EMS time on scene was 16.1 minute versus 11.6 minutes in an urban setting (p < 0.04). CONCLUSION: In a setting of rural MVC, increased EMS response time, time on scene and distance to the scene are associated with higher rural trauma mortality rates.

Accidents, Traffic↗