Latent Risk Factor Research Articles

Markov chain Monte Carlo estimation of default and recovery: dependent via the latent systematic factor

It is a well known fact that recovery rates tend to go down when the number of defaults goes up in economic downturns. We demonstrate how the loss given default model with the default and recovery dependent via the latent systematic risk factor can be estimated using Bayesian inference methodology and Markov chain Monte Carlo method. This approach is very convenient for joint estimation of all model parameters and latent systematic factors. Moreover, all relevant uncertainties are easily quantified. Typically available data are annual averages of defaults and recoveries and thus the datasets are small and parameter uncertainty is significant. In this case Bayesian approach is superior to the maximum likelihood method that relies on a large sample limit Gaussian approximation for the parameter uncertainty. As an example, we consider a homogeneous portfolio with one latent factor. However, the approach can be easily extended to deal with non-homogenous portfolios and several latent factors.

Amygdala activation in maltreated children during pre-attentive emotional processing

Childhood adversity is associated with significantly increased risk of psychiatric disorder. To date, functional magnetic resonance imaging (fMRI) studies of children have mainly focused on institutionalisation and investigated conscious processing of affect. To investigate neural response to pre-attentively presented affect cues in a community sample of children with documented experiences of maltreatment in the home. A masked dot-probe paradigm involving pre-attentive presentation of angry, happy and neutral facial expressions was employed. Eighteen maltreated children were compared with 23 carefully matched non-maltreated peers. Increased neural response was observed in the right amygdala for pre-attentively presented angry and happy faces in maltreated v. non-maltreated children. Level of amygdala activation was negatively associated with age at onset for several abuse subtypes. Maltreatment is associated with heightened neural response to positive and negative facial affect, even to stimuli outside awareness. This may represent a latent neural risk factor for future psychiatric disorder.

Reduced orbitofrontal and temporal grey matter in a community sample of maltreated children

Childhood maltreatment is strongly associated with increased risk of psychiatric disorder. Previous neuroimaging studies have reported atypical neural structure in the orbitofrontal cortex, temporal lobe, amygdala, hippocampus and cerebellum in maltreated samples. It has been hypothesised that these structural differences may relate to increased psychiatric vulnerability. However, previous studies have typically recruited clinical samples with concurrent psychiatric disorders, or have poorly characterised the range of maltreatment experiences and levels of concurrent anxiety or depression, limiting the interpretation of the observed structural differences. We used voxel-based morphometry to compare grey matter volume in a group of 18 children (mean age 12.01 years, SD = 1.4), referred to community social services, with documented and well-characterised experiences of maltreatment at home and a group of 20 nonmaltreated children (mean age 12.6 years, SD = 1.3). Both groups were comparable on age, gender, cognitive ability, ethnicity and levels of anxiety, depression and posttraumatic stress symptoms. We examined five a priori regions of interest: the prefrontal cortex, temporal lobes, amygdala, hippocampus and cerebellum. Maltreated children, compared to nonmaltreated peers, presented with reduced grey matter in the medial orbitofrontal cortex and the left middle temporal gyrus. The medial orbitofrontal cortex and the middle temporal gyrus have been implicated in reinforcement-based decision-making, emotion regulation and autobiographical memory, processes that are impaired in a number of psychiatric disorders associated with maltreatment. We speculate that grey matter disturbance in these regions in a community sample of maltreated children may represent a latent neurobiological risk factor for later psychopathology and heightened risk taking.

Missed epidemics and missing links: international birth cohort trends in multiple sclerosis

Many hypotheses on the etiopathogenesis of multiple sclerosis (MS) focus on risk factors occurring early in life. This study examined the variability of birth cohort trends in international MS data by means of age-period-cohort (APC) analysis. The data from 25 countries were taken from the WHO mortality database. Data were encoded according to the International Classification of Diseases and covered slightly varying periods between 1951 and 2009. The APC analyses were based on logit models applied to cohort tables with 5-year age- and period intervals. In most countries, the birth cohort estimates peaked in those born in the first half of the 20th century. In countries from Central and Western Europe, the peak concerned those born before and around 1920. A second group of countries (Denmark, Sweden, Italy, Ireland, Scotland) shared a later peak amongst cohorts born in the 1920s and 1930s. Group 3 included Commonwealth countries, the USA and Norway, with a double or extended peak starting in the 1910s or 1920s, and ending by the 1950s. The fourth group, consisting of Mediterranean countries and Finland, was characterized by a steady increase in the birth cohort estimates until the 1950s. The fifth group with countries from Eastern Europe and Japan showed no particular pattern. Birth cohort trends have influenced the change in MS risk across the 20th century in many Western countries. This silent epidemic points to a most important but unknown latent risk factor in MS.

Heightened neural reactivity to threat in child victims of family violence

Summary Exposure to family violence affects a significant minority of children: estimates of physical abuse range from 4 to 16%, while intimate partner violence affects between 8 and 25% of children [1]. These maltreatment experiences represent a form of environmental stress that significantly increases risk of later psychopathology, including anxiety [1,2]. To date, no functional magnetic resonance imaging (fMRI) studies have probed the neural correlates of emotional processing in children exposed to family violence. Previous psychological and electrophysiological studies indicate a selective hypervigilance to angry cues in physically abused children, which is in turn associated with elevated levels of anxiety [3]. Functional magnetic resonance imaging (fMRI) research has demonstrated increased reactivity of the anterior insula (AI) and amygdala to angry faces in individuals with anxiety disorder [4], and in psychiatrically healthy soldiers exposed to combat [5], making these regions plausible neural candidates for adaptation to threat. We demonstrated that children exposed to family violence (with normative levels of anxiety) show increased AI and amygdala reactivity in response to angry but not sad faces. While such enhanced reactivity to a biologically salient threat cue may represent an adaptive response to sustained environmental danger, it may also constitute a latent neurobiological risk factor increasing vulnerability to psychopathology.

Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor

Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by a linear growth model with random effects. Occasion-specific cognitive function is measured by an item response model for longitudinal scores on the Mini-Mental State Examination, a questionnaire used to screen for cognitive impairment. The illness-death model will be used to identify and to explore the relationship between occasion-specific cognitive function and stroke. Combining a multi-state model with the latent growth model defines a joint model which extends current statistical inference regarding disease progression and cognitive function. Markov chain Monte Carlo methods are used for Bayesian inference. Data stem from the Medical Research Council Cognitive Function and Ageing Study in the UK (1991–2005).

Credit Risk and the Macro Economy in an Affine Term Structure Model

The interrelations between corporate lending conditions and the macro economy are becoming increasingly important, particularly in the context of bank regulation and monetary policy. In this paper, I develop a joint affine macro-finance model of the term structures of US Treasury yields and US corporate bond yields. A model with inflation, industrial production growth and three latent factors is able to explain the dynamics of a wide range of rating classes and maturities. An economy-wide latent credit risk factor is identified to study the role of credit conditions in the business cycle. In-sample model dynamics and out-of-sample macroeconomic forecasts provide evidence that credit conditions contain information about the business cycle that are not contained in the Treasury term structure. Therefore, credit conditions form an integral part of the transmission process of monetary policy and highlight the necessity to integrate credit information into policymakers' theoretical business cycle models.

Association study between GABA receptor genes and anxiety spectrum disorders

Human anxiety disorders are complex diseases with relatively unknown etiology. Dysfunction of the Gamma-aminobutyric acid (GABA) system has been implicated in many neuropsychiatric conditions, including anxiety and depressive disorders. In this investigation, we explored four GABA receptor genes for their possible associations with genetic risk for anxiety disorders and depression. Our study sample consisted of 589 cases and 539 controls selected from a large population-based twin registry based upon a latent genetic risk factor shared by several anxiety disorders, major depression, and neuroticism. We subjected these to a two-stage protocol, in which all candidate genetic markers were screened for association in stage 1 (N=376), the positive results of which were tested for replication in stage 2 (N=752). We analyzed data from 26 single nucleotide polymorphisms (SNPs) from four GABA receptor genes: GABRA2, GABRA3, GABRA6, and GABRG2. Of the 26 SNPs genotyped in stage 1, we identified two markers in GABRA3 that met the threshold (P < or = .1) to be tested in stage 2. Phenotypic associations of these two markers failed to replicate in stage 2. These findings suggest that common variation in the GABRA2, GABRA3, GABRA6, and GABRG2 genes does not play a major role in liability to anxiety spectrum disorders.

Comparison of Screening Procedures for Mycobacterium tuberculosis Infection Among Patients with Inflammatory Diseases

To test if Mycobacterium tuberculosis screening results differ among patients with inflammatory disease depending on whether the QuantiFeron TB-Gold test (QFT) or tuberculin skin test (TST) is used; and to evaluate if a possible difference is influenced by the presence of risk factors or immunosuppression. The interferon-gamma response to in vitro stimulation of M. tuberculosis-specific antigens was measured with QFT and results were compared with TST. Associations to bacillus Calmette-Guerin (BCG) vaccination, risk factors, and immunosuppression were analyzed for both tests. QFT and TST results were available for 294/302 and 241/302 patients, respectively; 234 had results from both tests. Twenty-one (7%) tested positive with QFT and 45 (19%) with TST. A positive QFT was associated with risk factors for M. tuberculosis infection: i.e., birth or upbringing in a TB-endemic area [risk ratio (RR) = 7.8, 95% CI 1.5-18.2, p < 0.001], previous TB treatment (RR 4.7, 95% CI 1.6-13.5, p = 0.005), and any latent TB infection risk factor (RR 4.7, 95% CI 2.1-11.0, p = 0.0002). Treatment with corticosteroids increased the risk for an inconclusive QFT result (RR 4.2, 95% CI 1.6-10.7, p = 0.04) and decreased the risk for a positive TST result (RR 0.4, 95% CI 0.1-1.0, p = 0.04). Agreement between the tests was low (kappa 0.2, 95% CI 0.02-0.3, p = 0.002). The study documented a high degree of discordant positive QFT and TST results. A positive QFT was more closely associated with risk factors for M. tuberculosis infection than the TST. The use of corticosteroids affected test outcome by increasing the risk for an inconclusive QFT result and decreasing the risk for a positive TST result.

AN ADMISSIBLE TERM STRUCTURE MODEL OF SOVEREIGN YIELD SPREADS WITH MACRO FACTORS: THE CASE OF BRAZILIAN GLOBAL BONDS

We study the term structure of Brazilian sovereign bond yield spreads and their links with the domestic economy using a macro‐finance framework. Our model allows Brazilian macroeconomic variables as well as a latent country risk factor to affect sovereign spreads. We find that although the Brazilian sovereign yield spreads are dominated by the risk factor during the high default risk periods of 1999 and 2002, the effects of macro variables are significant during the rest of the estimation period. In addition, the volatility level of the macroeconomic system is driven by the country risk factor.

Association study of CREB1 with Major Depressive Disorder and related phenotypes

Cyclic AMP response element binding protein (CREB) has been implicated in behavioral models of anxiety and depression, antidepressant response in humans, and suicide. One group reported a female-specific association of the CREB1 gene in early-onset Major Depressive Disorder (MDD), while another found no evidence of association with this phenotype. In this study, we sought to examine the evidence for association of the CREB1 gene to MDD and related phenotypes. We used multivariate structural equation modeling to identify and select twin pairs that scored at the extremes of a latent genetic risk factor shared by MDD, neuroticism, and several anxiety disorders from the Virginia Twin Registry. Using one member from each of these pairs, the resulting sample of 589 cases (including 473 subjects with lifetime MDD) and 539 controls were entered into a 2-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2. Eight SNP markers selected to capture the major allelic variation across the haplotype block containing CREB1 were analyzed for differences between cases and controls. Several markers showed criterion differences between cases and controls in the stage 1 sample with some evidence of sex specific effects. However, none of these markers were significant in stage 2 in either sex individually or combined. Our data suggests that common variations in the CREB1 gene do not appear to increase susceptibility for MDD or related phenotypes.

Catechol- O-Methyltransferase Contributes to Genetic Susceptibility Shared Among Anxiety Spectrum Phenotypes

Catechol-O-methyltransferase (COMT) has been investigated for its possible role in a wide range of psychiatric phenotypes. In particular, several studies support association of this gene with panic disorder and other anxiety-related traits. We examined the COMT gene for association with genetic risk across a range of anxiety spectrum phenotypes. We used multivariate structural equation modeling to select twin pairs scoring at the extremes of a latent genetic risk factor shared by neuroticism, several anxiety disorders, and major depression from a large population-based twin sample. With one member from each of these pairs, the resulting sample of 589 cases and 539 control subjects were entered into a two-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2. The functional val158met polymorphism (rs4680) plus nine other single nucleotide polymorphism markers selected to capture the major allelic variation across the COMT locus were analyzed for differences between cases and control subjects. Although the val (G) allele of rs4680 showed marginally significant association in our combined stage 1 plus stage 2 sample, a high-risk haplotype of this allele with the A allele of rs165599 was significantly over-represented in cases (p = 1.97e-5, odds ratio = 1.95). This haplotype also predicted individual differences in neuroticism and risk for several anxiety disorders and major depression. Consistent with prior studies, our findings are female-specific. Variations in the COMT gene contribute to genetic risk shared across a range of anxiety-related phenotypes.

Lack of association between the amiloride-sensitive cation channel 2 (ACCN2) gene and anxiety spectrum disorders

Ion channels are involved in a wide range of central nervous system functions and have been implicated in several neuropsychiatric disorders. Rodent studies suggest that the acid-sensing ion channel, ASIC1, may play a role in fear conditioning, a model for human anxiety disorders. In this study, we examined, for the first time, the human analog of ASIC1, the amiloride-sensitive cation channel 2 (ACCN2) gene, for its association with genetic risk across a range of anxiety spectrum phenotypes. Using multivariate structural equation modeling, we selected twin pairs scoring at the extremes of a latent genetic risk factor that underlies susceptibility to neuroticism, major depression, generalized anxiety disorder, panic disorder, agoraphobia, and social phobia, from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. One member from each selected pair for whom DNA was available was entered into a 2-stage, case-control association study for the ACCN2 gene. In the resulting sample of 589 cases and 539 controls, a total of seven single nucleotide polymorphisms that represented the major allelic variation across the ACCN2 locus were screened in stage 1, the positive results of which were tested for replication in stage 2. Although several markers or haplotypic combinations met threshold significance criteria in stage 1, their association was not replicated in stage 2. Post hoc analyses did not reveal significant association to the specific psychiatric phenotypes. Although the ACCN2 gene may play a role in rodent fear conditioning, we could not detect association with genetic risk shared among human anxiety spectrum disorders.

Association study between the serotonin 1A receptor (HTR1A) gene and neuroticism, major depression, and anxiety disorders

The serotonin neurotransmitter system in general, and the serotonin 1A receptor in particular, has been broadly implicated in the pathophysiology of mood and anxiety disorders, although the results of genetic association studies have been mixed. In this study, we examined the serotonin 1A receptor gene, HTR1A, for its association with shared genetic risk across a range of anxiety and depression-related phenotypes. Using multivariate structural equation modeling, we selected twin pairs from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders scoring at the extremes of a latent genetic risk factor that underlies susceptibility to neuroticism, major depression, and several anxiety disorders. One member from each selected pair was entered into a 2-stage, case-control association study for the HTR1A gene. In the resulting sample of 589 cases and 539 controls, four SNPs spanning the HTR1A locus, including the C(-1019)G functional promoter polymorphism (rs6295), were screened in stage 1, the positive results of which were tested for replication in stage 2. While one marker met threshold significance criteria in stage 1, this association was not replicated in stage 2. Post-hoc analyses did not reveal association to any of the specific psychiatric phenotypes. Our data suggests that the HTR1A gene may not play a major role in the genetic susceptibility underlying depressive and anxiety-related phenotypes.

A study on the association of apolipoprotein E genotypes with primary open-angle glaucoma and primary angle-closure glaucoma in northeast of China

To analysis the association of apolipoprotein E (APOE) genotype with primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG) in northeast of China. The polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) technique were used to detect the distribution of genotype and gene frequency of APOE alleles in 36 patients with POAG, 69 with PACG and 57 healthy subjects as control. The frequency of APOE epsilon 3/epsilon 4 genotype in POAG group (41.7%)and epsilon 2/epsilon 4 in PACG group (43.5%) was significantly (P < 0.05) higher than that in control group (14.0% and 21.1%, respectively). The frequency of APOE epsilon 4 allele in both of POAG (37.5%) and PACG group (39.2%) was significantly (P < 0.05) higher than that in control group (17.5%), whereas the frequency of APOE epsilon 2 allele in POAG group (8.3%) was significantly (P < 0.05) lower than that in control group (15.8%). APOE epsilon 4 allele may be a latent risk factor in the development of primary glaucoma, but APOE epsilon 2 allele may play a protective role in POAG and warrant further investigation.

Book-to-Market and Size Effects: Risk Compensations or Market Inefficiencies?

Are the size and book-to-market effects in US data related to risk factors besides the market risk? Are the portfolios, HML and SMB, proper representations of latent factors? We apply the orthogonal portfolio approach to model the risk premium when not all factors are known. The results show that the size effect is a compensation for a latent risk factor related to relative distress, but the book-to-market effect is mostly non-risk-based. Our results validate SMB as a proper factor-mimicking portfolio, while HML is successful in asset pricing tests since it shares the same non-risk-based components as the test portfolios.

Meshwork pattern is an important risk factor for development of hepatocellular carcinoma in patients with HBV-related chronic hepatitis and cirrhosis

We analyzed the importance of ‘meshwork pattern’, a sign representing severe irregularity on the intra-hepatic echogram, in hepatitis B virus (HBV)-related chronic hepatitis and cirrhosis, as a risk factor for development of hepatocellular carcinoma (HCC). Two hundred and thirty-one patients (143 men and 88 women) with HBV-related chronic hepatitis and cirrhosis who visited our hospital from January 1993 to December 1994 were enrolled in this study. Since enrollment, abdominal ultrasonography had in principle been performed every 3 months for cirrhotic patients and every 4–6 months for patients with chronic hepatitis for HCC screening. Cumulative HCC incidences in patient groups positive or negative for meshwork pattern were calculated by the Kaplan–Meier method. The incidence of HCC was significantly higher in the group positive for meshwork pattern (average incidence per year: 4.4%) than in the group negative for it (average incidence per year: 0.5%) ( P<0.0001, Mantel–Cox test). On regression analysis with Cox's proportional hazards model, sex, α-fetoprotein and meshwork pattern were selected as independent risk factors for HCC. In conclusion, meshwork pattern appears to be an ultrasonographic sign useful for detecting a latent risk factor for HCC in patients with HBV-related chronic hepatitis and cirrhosis.

Vehicle Emission Unit Risk Factors for Transportation Risk Assessments*

When the transportation risk posed by shipments of hazardous chemical and radioactive materials is being assessed, it is necessary to evaluate therisks associated with both vehicle emissions and cargo‐related risks. Diesel exhaust and fugitive dust emissions from vehicles transporting hazardous shipments lead to increased air pollution, which increases the risk of latent fatalities in the affected population along the transport route. The estimated risk from these vehicle‐related sources can often be as large or larger than the estimated risk associated with the material being transported. In this paper, data from the U.S. Environmental Protection Agency's Motor Vehicle‐Related Air Toxics Study are first used to develop latent cancer fatality estimates per kilometer of travel in rural and urban areas forall diesel truck classes. These unit risk factors are based on studies investigating the carcinogenic nature of diesel exhaust. With the same methodology, the current per‐kilometer latent fatality risk factor used in transportation risk assessments for heavy diesel trucks in urban areas is revised and the analysis expanded to provide risk factors for rural areas and all diesel truck classes. These latter fatality estimates may include, but are not limited to, cancer fatalities and are based primarily on the most recent epidemiological data available on mortality rates associated with ambient air PM‐10 concentrations.

Vehicle emission unit risk factors for transportation risk assessments.

When the transportation risk posed by shipments of hazardous chemical and radioactive materials is being assessed, it is necessary to evaluate the risks associated with both vehicle emissions and cargo-related risks. Diesel exhaust and fugitive dust emissions from vehicles transporting hazardous shipments lead to increased air pollution, which increases the risk of latent fatalities in the affected population along the transport route. The estimated risk from these vehicle-related sources can often be as large or larger than the estimated risk associated with the material being transported. In this paper, data from the U.S. Environmental Protection Agency's Motor Vehicle-Related Air Toxics Study are first used to develop latent cancer fatality estimates per kilometer of travel in rural and urban areas for all diesel truck classes. These unit risk factors are based on studies investigating the carcinogenic nature of diesel exhaust. With the same methodology, the current per-kilometer latent fatality risk factor used in transportation risk assessments for heavy diesel trucks in urban areas is revised and the analysis expanded to provide risk factors for rural areas and all diesel truck classes. These latter fatality estimates may include, but are not limited to, cancer fatalities and are based primarily on the most recent epidemiological data available on mortality rates associated with ambient air PM-10 concentrations.

Analyzing twin resemblance in multisymptom data: genetic applications of a latent class model for symptoms of conduct disorder in juvenile boys.

A model based on the latent class model is developed for the effects of genes and environment on multivariate categorical data in twins. The model captures many essential features of dimensional and categorical conceptions of complex behavioral phenotypes and can include, as special cases, a variety of major locus models including those that allow for etiological heterogeneity, differential sensitivity of latent classes to measured covariates, and genotype x environment interaction (G x E). Many features of the model are illustrated by an application to ratings on eight items relating to conduct disorder selected from the Rutter Parent Questionnaire (RPQ). Mothers rated their 8- to 16-year-old male twin offspring [174 monozygotic (MZ) and 164 dizygotic (DZ) pairs]. The impact of age on the frequency of reported symptoms was relatively slight. Preliminary latent class analysis suggests that four classes are required to explain the reported behavioral profiles of the individual twins. A more detailed analysis of the pairwise response profiles reveals a significant association between twins for membership of latent classes and that the association is greater in MZ than DZ twins, suggesting that genetic factors played a significant role in class membership. Further analysis shows that the frequencies of MZ pairs discordant for membership of some latent classes are close to zero, while others are definitely not zero. One possible explanation of this finding is that the items reflect underlying etiological heterogeneity, with some response profiles reflecting genetic categories and others revealing a latent environmental risk factor. We explore two "four-class" models for etiological heterogeneity which make different assumptions about the way in which genes and environment interact to produce complex disease phenotypes. The first model allows for genetic heterogeneity that is expressed only in individuals exposed to a high-risk ("predisposing") environment. The second model allows the environment to differentiate two forms of the disorder in individuals of high genetic risk. The first model fits better than the second, but neither fits as well as the general model for four latent classes associated in twins. The results suggest that a single-locus/two-allele model cannot fit the data on these eight items even when we allow for etiological heterogeneity. The pattern of endorsement probabilities associated with each of the four classes precludes a simple "unidimensional" model for the latent process underlying variation in symptom profile in this population. The extension of the approach to larger pedigrees and to linkage analysis is briefly considered.