Biomedical subjects

K Y Liang

Publications and source records attributed to K Y Liang.

At least 37 records · Page 2Linked to original sources

PubMed2001

[Experimental study on effect of zenggu-I, -II, -III on osteoblast in vitro].

OBJECTIVE: To investigate the effect of Zenggu (ZG)-I, -II and -III on osteoblast (OB) cultured in vitro. METHODS: OB was isolated from calvaria of 22-day-old fetal SD rats by means of modified sequential collagenase digestion and incubated in RM1640 medium and the cell morphology was observed by alkaline phosphatase (ALP) staining. Different concentrations of ZG-I, -II and -III were added to the OB and incubated. The effect of ZG on the proliferation and osteogenesis of OB was monitored by MTT analysis, BGP content radioimmunoassay, ALP activity and calcium contents determination. RESULTS: The BGP, ALP, and calcium contents of the cultured OB cells as well as the cell proliferation were higher in ZG-III group than those in the other groups (P < 0.05) in a dose-dependent manner. It suggested that ZG-III could promote the proliferation and osteogenesis of OB, but ZG-I and ZG-II had insignificant influence on OB cultured in vitro. CONCLUSION: ZG-III could promote the OB proliferation and bone formation, ZG-I, -II, -III sequential therapy could effectively prevent and treat osteoporosis and promote the bone formation.

Animals↗

PubMed2000

Complex segregation analysis provides compelling evidence for a major gene underlying obsessive-compulsive disorder and for heterogeneity by sex.

Evidence from twin and family studies supports a genetic etiology for obsessive-compulsive disorder (OCD). The purpose of this study was to test whether a major gene is implicated in a proportion of families with OCD. Complex segregation analyses of 153 families (80 case and 73 control), ascertained in the Johns Hopkins OCD Family Study, provided strong evidence for a major gene. A Mendelian-dominant model, with significant sex effects and with residual familial effects, best explained the observed data. Stratification of the sample by the sex of probands provided further evidence of heterogeneity with respect to familial aggregation. Segregation analyses of 86 families with a female proband and of the 67 families with a male proband suggested that a Mendelian-dominant model with familial residual effects was the most parsimonious model explaining the inheritance of OCD in both subgroups.

Adolescent↗

PubMed2000

The relationship of obsessive-compulsive disorder to possible spectrum disorders: results from a family study.

BACKGROUND: The familial relationship between obsessive-compulsive disorder (OCD) and "obsessive-compulsive spectrum" disorders is unclear. This study investigates the relationship of OCD to somatoform disorders (body dysmorphic disorder [BDD] and hypochondriasis), eating disorders (e.g., anorexia nervosa and bulimia nervosa), pathologic "grooming" conditions (e.g., nail biting, skin picking, trichotillomania), and other impulse control disorders (e.g., kleptomania, pathologic gambling, pyromania) using blinded family study methodology. METHODS: Eighty case and 73 control probands, as well as 343 case and 300 control first-degree relatives, were examined by psychiatrists or Ph.D. psychologists using the Schedule for Affective Disorders and Schizophrenia-Lifetime Anxiety version. Two experienced psychiatrists independently reviewed all diagnostic information and made final consensus diagnoses using DSM-IV criteria. RESULTS: Body dysmorphic disorder, hypochondriasis, any eating disorder, and any grooming condition occurred more frequently in case probands. In addition, BDD, either somatoform disorder, and any grooming condition occurred more frequently in case relatives, whether or not case probands also had the same diagnosis. CONCLUSIONS: These findings indicate that certain somatoform and pathologic grooming conditions are part of the familial OCD spectrum. Though other "spectrum" conditions may resemble OCD, they do not appear to be important parts of the familial spectrum.

Adult↗

PubMed2000

A unified sampling approach for multipoint analysis of qualitative and quantitative traits in sib pairs.

Recent advances in molecular biology have enhanced the opportunity to conduct multipoint mapping for complex diseases. Concurrently, one sees a growing interest in the use of quantitative traits in linkage studies. Here, we present a multipoint sib-pair approach to locate the map position (tau) of a trait locus that controls the observed phenotype (qualitative or quantitative), along with a measure of statistical uncertainty. This method builds on a parametric representation for the expected identical-by-descent statistic at an arbitrary locus, conditional on an event reflecting the sampling scheme, such as affected sib pairs, for qualitative traits, or extreme discordant (ED) sib pairs, for quantitative traits. Our results suggest that the variance about tau&d4;, the estimator of tau, can be reduced by as much as 60%-70% by reducing the length of intervals between markers by one half. For quantitative traits, we examine the precision gain (measured by the variance reduction in tau&d4;) by genotyping extremely concordant (EC) sib pairs and including them along with ED sib pairs in the statistical analysis. The precision gain depends heavily on the residual correlation of the quantitative trait for sib pairs but considerably less on the allele frequency and exact genetic mechanism. Since complex traits involve multiple loci and, hence, the residual correlation cannot be ignored, our finding strongly suggests that one should incorporate EC sib pairs along with ED sib pairs, in both design and analysis. Finally, we empirically establish a simple linear relationship between the magnitude of precision gain and the ratio of the number of ED pairs to the number of EC pairs. This relationship allows investigators to address issues of cost effectiveness that are due to the need for phenotyping and genotyping subjects.

Alleles↗

PubMed2000

A family study of obsessive-compulsive disorder.

BACKGROUND: The causes of obsessive-compulsive disorder (OCD) are as yet unknown. Evidence of familial aggregation is one approach for investigating the role of genetics in the etiology of this condition. The current study was conducted to determine ifOCD is familial and to investigate possible familial subtypes. METHODS: Eighty case probands were identified in 5 specialty OCD clinics and 73 community control probands were identified by random-digit dialing. These probands and their first-degree relatives (343 case and 300 control relatives) were blinded to group and evaluated by psychiatrists and doctoral-level clinical psychologists using semistructured instruments. Final diagnoses were assigned by a blinded-consensus procedure. The results were analyzed using logistic regression by the method of generalized estimating equations. RESULTS: The lifetime prevalence of OCD was significantly higher in case compared with control relatives (11.7% vs 2.7%) (P<.001). Case relatives had higher rates of both obsessions and compulsions; however, this finding is more robust for obsessions. Age at onset of obsessive-compulsive symptoms in the case proband was strongly related to familiality (odds ratio, 0.92; confidence interval, 0.85-0.99) (P = .05); no case of OCD symptoms was detected in the relatives of probands whose age at onset of symptoms was 18 years or older. Probands with tics or obsessive-compulsive personality disorder were not more likely to have relatives with OCD than those without these features. CONCLUSIONS: Obsessive-compulsive disorder is a familial disorder. Obsessions are more specific to the phenotype than are compulsions. Age at onset of OCD is valuable in characterizing a familial subtype.

Adolescent↗

PubMed2000

A study of contemporary levels and temporal trends in inbreeding in the Tangier Island, Virginia, population using pedigree data and isonymy.

In this study we describe inbreeding in a large pedigree from Tangier Island, Virginia, in which we compare two commonly used methods to estimate inbreeding in humans: pedigree and isonymy (identical surnames of spouses). Genealogical data on 3,512 individuals dating back to 1722 were used. Using the pedigree method, we determined an average inbreeding coefficient (F) of 0.00873 for the community as a whole, and 0.018 for inbred individuals. Analysis of temporal trends showed that inbreeding began around 1800 and peaked at 0.0109 in 1824-1849 and 1875-1899. Thereafter, inbreeding steadily declined to 0.00565 in 1975-1997. Analysis of pedigree structure complexity over time showed that close consanguinity contributes to inbreeding in the earlier cohorts, and remote consanguinity accounts for much of the inbreeding in the later cohorts. The number of common ancestors increases over time, as does the number of paths connecting inbred individuals to these common ancestors. Inbreeding estimates based on the isonymy approach yielded a 2.2-fold higher value of F (0.01945) compared to the pedigree method. Total isonymy estimates over 25-year cohorts overestimated inbreeding values from pedigree data between 1. 5-8-fold. We speculate that the overestimation is probably due to the inability of our data to satisfy the method's assumption of monophyletic origin of each surname. In conclusion, inbreeding in the Tangier Island population is consistent with the isolated nature of its population, and temporal trends reflect patterns in emigration and a breakdown in isolation over time.

Adolescent↗

PubMed2000

Genetic heterogeneity in schizophrenia: stratification of genome scan data using co-segregating related phenotypes.

Despite considerable effort to identify susceptibility loci for schizophrenia, none have been localized. Multiple genome scans and collaborative efforts have shown evidence for linkage to regions on chromosomes 1q, 5q, 6q, 8p, 13q, 10p and 22q.(1-9) Heterogeneity is likely. We previously mapped schizophrenia susceptibility loci (SSL) to chromosomes 13q32 (P = 0.00002) and 8p21-22 (P= 0.0001) using 54 multiplex pedigrees and suggested linkage heterogeneity. We have now stratified these families based on co-segregating phenotypes in non-schizophrenic first degree relatives (schizophrenia spectrum personality disorders (SSPD); psychotic affective disorders (PAD)). Genome scans were conducted for these phenotypic subgroups of families and broadened affected phenotypes were tested. The SSPD group provided its strongest genome-wide linkage support for the chromosome 8p21 region (D8S1771) using either narrow (non-parametric lod (NPL) P= 0.000002) or broadened phenotypes (NPL P = 0.0000008) and a new region of interest on 1p was identified (P = 0.006). For PAD families, the peak NPL in the genome scan occurred on chromosome 3p26-p24 (P = 0.008). The identification of multiple susceptibility loci for schizophrenia may be enhanced by stratification of families using psychiatric diagnoses of the non-schizophrenic relatives.

Family Health↗

PubMed2000

Statistical designs for familial aggregation.

In the past two decades, it has become increasingly clear that genetic factors contribute to the aetiology of many common diseases including cancers, coronary disease, allergy and psychiatric disorders. While one goal of genetic epidemiological studies is to locate susceptibility genes for these complex diseases, it is important that strong evidence of familial aggregation be established at an early stage of research. In this paper, we discuss several study designs useful to address some issues such as (1) detecting familial aggregation, (2) testing for gene-environment interaction, (3) identifying homogeneous subgroups and (4) measuring magnitude and patterns of familial correlations. These designs include the conventional case-control design and the family case-control design. For each of these two study designs, we discuss analytical strategies as well as their strengths and weaknesses. Throughout, several examples from real studies are used for illustrative purposes.

Case-Control Studies↗

PubMed2000

Personality disorders and normal personality dimensions in obsessive-compulsive disorder.

BACKGROUND: Little is known about personality disorders and normal personality dimensions in relatives of patients with obsessive-compulsive disorder (OCD). AIMS: To determine whether specific personality characteristics are part of a familial spectrum of OCD. METHOD: Clinicians evaluated personality disorders in 72 OCD case and 72 control probands and 198 case and 207 control first-degree relatives. The selfcompleted Revised NEO Personality Inventory was used for assessment of normal personality dimensions. The prevalence of personality disorders and scores on normal personality dimensions were compared between case and control probands and between case and control relatives. RESULTS: Case probands and case relatives had a high prevalence of obsessive-compulsive personality disorder (OCPD) and high neuroticism scores. Neuroticism was associated with OCPD in case but not control relatives. CONCLUSIONS: Neuroticism and OCPD may share a common familial aetiology with OCD.

Adult↗

PubMed1999

Body weight patterns from 20 to 49 years of age and subsequent risk for diabetes mellitus: the Johns Hopkins Precursors Study.

BACKGROUND: Obesity in middle age is a well-known risk factor for the development of type 2 diabetes mellitus. However, the importance of weight and weight gain at younger ages is less certain. OBJECTIVE: To determine the relationship of body weight patterns from 20 to 49 years of age with the subsequent risk for type 2 diabetes mellitus. SETTING: An ongoing longitudinal study of former medical students. PARTICIPANTS: Nine hundred sixteen white men without diabetes at 50 years of age. MEASUREMENTS: Weight and height measured in medical school, then assessed by mailed questionnaire to 49 years of age. MAIN OUTCOME: Incident type 2 diabetes mellitus based on physician self-report. RESULTS: During 14 255 person-years of follow-up, there were 35 incident cases of type 2 diabetes mellitus (2.5 per 1000 person-years). After simultaneous adjustment for age, physical activity, lifetime maternal history of diabetes, and smoking, body mass indexes (BMIs; calculated as weight in kilograms divided by the square of height in meters) at 25, 35, and 45 years of age were all strongly associated with diabetes risk (relative risks for overweight [BMI> or =25.0] vs. not overweight, >3.0; all Ps<.05), as were maximum and average BMI to 49 years of age. The relationship of BMI at 25 years of age to diabetes risk was substantially attenuated by adjustment for BMI at 45 years of age and average BMI, but was independent of weight change, weight variability, or maximum BMI. CONCLUSION: In men, overweight at 25 years of age strongly predicts diabetes risk in middle age, largely through its association with overweight at 45 years of age and high average BMI to 49 years of age.

Adult↗

PubMed1999

Cannabis use and cognitive decline in persons under 65 years of age.

The purpose of this study was to investigate possible adverse effects of cannabis use on cognitive decline after 12 years in persons under age 65 years. This was a follow-up study of a probability sample of the adult household residents of East Baltimore. The analyses included 1,318 participants in the Baltimore, Maryland, portion of the Epidemiologic Catchment Area study who completed the Mini-Mental State Examination (MMSE) during three study waves in 1981, 1982, and 1993-1996. Individual MMSE score differences between waves 2 and 3 were calculated for each study participant. After 12 years, study participants' scores declined a mean of 1.20 points on the MMSE (standard deviation 1.90), with 66% having scores that declined by at least one point. Significant numbers of scores declined by three points or more (15% of participants in the 18-29 age group). There were no significant differences in cognitive decline between heavy users, light users, and nonusers of cannabis. There were also no male-female differences in cognitive decline in relation to cannabis use. The authors conclude that over long time periods, in persons under age 65 years, cognitive decline occurs in all age groups. This decline is closely associated with aging and educational level but does not appear to be associated with cannabis use.

Adult↗

PubMed1999

Hypothesis testing under mixture models: application to genetic linkage analysis.

In this paper we propose a new class of statistics to test a simple hypothesis against a family of alternatives characterized by a mixture model. Unlike the likelihood ratio statistic, whose large sample distribution is still unknown in this situation, these new statistics have a simple asymptotic distribution to which to refer under the null hypothesis. Simulation results suggest that it has adequate power in detecting the alternatives. Its application to genetic linkage analysis in the presence of the genetic heterogeneity that motivated this work is emphasized.

Biometry↗

PubMed1999

Estimating equations for a latent transition model with multiple discrete indicators.

This paper proposes a two-part model for studying transitions between health states over time when multiple, discrete health indicators are available. The includes a measurement model positing underlying latent health states and a transition model between latent health states over time. Full maximum likelihood estimation procedures are computationally complex in this latent variable framework, making only a limited class of models feasible and estimation of standard errors problematic. For this reason, an estimating equations analogue of the pseudo-likelihood method for the parameters of interest, namely the transition model parameters, is considered. The finite sample properties of the proposed procedure are investigated through a simulation study and the importance of choosing strong indicators of the latent variable is demonstrated. The applicability of the methodology is illustrated with health survey data measuring disability in the elderly from the Longitudinal Study of Aging.

Aged↗

PubMed1999

Back injury in municipal workers: a case-control study.

OBJECTIVES: The purpose of this study was to identify factors associated with acute low back injury among municipal employees of a large city. METHODS: For each of 200 injured case patients, 2 coworker controls were randomly selected, the first matched on gender, job, and department and the second matched on gender and job classification. In-person interviews were conducted to collect data on demographics, work history, work characteristics, work injuries, back pain, psychosocial and work organization, health behaviors, and anthropometric and ergonomic factors related to the job. Psychosocial work organization variables were examined with factor analysis techniques; an aggregate value for job strain was entered into the final model. Risk factors were examined via multivariate logistic regression techniques. RESULTS: High job strain was the most important factor affecting back injury (odds ratio [OR] = 2.12, 95% confidence interval [CI] = 1.28, 3.52), and it showed a significant dose-response effect. Body mass index (OR = 1.54, 95% CI = 1.08, 2.18) and a work movement index (twisting, extended reaching, and stooping) (OR = 1.42, 95% CI = 0.97, 2.08) were also significant factors. CONCLUSIONS: Results suggest that increasing workers' control over their jobs reduces levels of job strain. Ergonomic strategies and worksite health promotion may help reduce other risk factors.

Accidents, Occupational↗

PubMed1998

Inference for odds ratio regression models with sparse dependent data.

Suppose the number of 2 x 2 tables is large relative to the average table size, and the observations within a given table are dependent, as occurs in longitudinal or family-based case-control studies. We consider fitting regression models to the odds ratios using table-level covariates. The focus is on methods to obtain valid inferences for the regression parameters beta when the dependence structure is unknown. In this setting, Liang (1985, Biometrika 72, 678-682) has shown that inference based on the noncentral hypergeometric likelihood is sensitive to misspecification of the dependence structure. In contrast, estimating functions based on the Mantel-Haenszel method yield consistent estimators of beta. We show here that, under the estimating function approach, Wald's confidence interval for beta performs well in multiplicative regression models but unfortunately has poor coverage probabilities when an additive regression model is adopted. As an alternative to Wald inference, we present a Mantel-Haenszel quasi-likelihood function based on integrating the Mantel-Haenszel estimating function. A simulation study demonstrates that, in medium-sized samples, the Mantel-Haenszel quasi-likelihood approach yields better inferences than other methods under an additive regression model and inferences comparable to Wald's method under a multiplicative model. We illustrate the use of this quasi-likelihood method in a study of the familial risk of schizophrenia.

Biometry↗

PubMed1997

Application of transmission disequilibrium tests to nonsyndromic oral clefts: including candidate genes and environmental exposures in the models.

Extensive epidemiological and genetic studies of the cause of oral clefts have demonstrated strong familial aggregation but have failed to yield definitive evidence of any single genetic mechanism. We used the transmission/disequilibrium test (TDT) to investigate the relationship between oral clefts and markers associated with five candidate genes by utilizing 160 parent-offspring trios. Conditional logistic regression models extended the TDT to include covariates as effect modifiers, thus permitting tests for gene-environment interactions. For four of these candidates [transforming growth factor alpha (TGFA), transforming growth factor beta 3 (TGFB3), retinoic acid receptor (RARA), and the proto-oncogene BCL3], we detected modestly elevated odds ratios for the transmission of one marker allele to cleft probands when all the trios were analyzed together. These odds ratios increased when information on type of cleft, race, family history, or maternal smoking were incorporated as effect modifiers. We detected significant interaction between maternal smoking and the transmission of alleles for markers near TGFA and TGFB3; excess transmission of allele 3 at BCL3 was most significant among cleft lip probands; and the odds ratios for transmission of alleles at D19S178 and THRA1 were significant when ethnic group was included in the model. We suggest that utilizing an analytical strategy that allows for stratification of data and incorporating environmental effects into a single analysis may be more effective for detecting genes of small effect.

B-Cell Lymphoma 3 Protein↗

PubMed1997

Analyzing sibship correlations in birth weight using large sibships from Norway.

Data from the Medical Birth Registry of Norway were used to estimate sibship correlations in large sibships (each with > or = 5 infants among singleton live births surviving the first year of life), while adjusting for covariates such as infant gender, gestational age, maternal age, parity, and time since last pregnancy. This sample of 12,356 full sibs in 2,462 sibships born in Norway between 1968 and 1989 was selected to maximize the information on parity, and a robust approach to estimating both regression coefficients and the sibship correlation using generalized estimating equations (GEE) was employed. In concordance with previous studies, these data showed a high overall correlation in birth weight among full sibs (0.48 +/- 0.01), but this sibship correlation was influenced by parity. In particular, the correlation between the firstborn infant and a subsequent infant was slightly lower than between two subsequent sibs (0.44 +/- 0.01 vs. 0.50 +/- 0.01, respectively). The effect of time between pregnancies was statistically significant, but its predicted impact was modest over the period in which most of these large families were completed. While these data cannot discriminate whether factors influencing birth weight are maternal or fetal in nature, this analysis does illustrate how robust statistical models can be used to estimate sibship correlations while adjusting for covariates in family studies.

Birth Certificates↗

PubMed1997

Sample size calculations for studies with correlated observations.

Correlated data occur frequently in biomedical research. Examples include longitudinal studies, family studies, and ophthalmologic studies. In this paper, we present a method to compute sample sizes and statistical powers for studies involving correlated observations. This is a multivariate extension of the work by Self and Mauritsen (1988, Biometrics 44, 79-86), who derived a sample size and power formula for generalized linear models based on the score statistic. For correlated data, we appeal to a statistic based on the generalized estimating equation method (Liang and Zeger, 1986, Biometrika 73, 13-22). We highlight the additional assumptions needed to deal with correlated data. Some special cases that are commonly seen in practice are discussed, followed by simulation studies.

Biometry↗