Detection Of High-risk Individuals Research Articles

Identification of high-risk patients for referral through machine learning assisting the decision making to manage minor ailments in community pharmacies.

Background: Data analysis techniques such as machine learning have been used for assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used yet to assist community pharmacists with services such as the Minor Ailment Services These services have been implemented to reduce the burden of primary care consultations in general medical practitioners (GPs) and to allow a better utilization of community pharmacists' skills. However, there is a need to refer high-risk patients to GPs. Aim: To develop a predictive model for high-risk patients that need referral assisting community pharmacists' triage through a minor ailment service. Method: An ongoing pragmatic type 3 effectiveness-implementation hybrid study was undertaken at a national level in Spanish community pharmacies since October 2020. Pharmacists recruited patients presenting with minor ailments and followed them 10days after the consultation. The main outcome measured was appropriate medical referral (in accordance with previously co-designed protocols). Nine machine learning models were tested (three statistical, three black box and three tree models) to assist pharmacists in the detection of high-risk individuals in need of referral. Results: Over 14'000 patients were included in the study. Most patients were female (68.1%). With no previous treatment for the specific minor ailment (68.0%) presented. A percentage of patients had referral criteria (13.8%) however, not all of these patients were referred by the pharmacist to the GP (8.5%). The pharmacists were using their clinical expertise not to refer these patients. The primary prediction model was the radial support vector machine (RSVM) with an accuracy of 0.934 (CI95 = [0.926,0.942]), Cohen's kappa of 0.630, recall equal to 0.975 and an area under the curve of 0.897. Twenty variables (out of 61 evaluated) were included in the model. radial support vector machine could predict 95.2% of the true negatives and 74.8% of the true positives. When evaluating the performance for the 25 patient's profiles most frequent in the study, the model was considered appropriate for 56% of them. Conclusion: A RSVM model was obtained to assist in the differentiation of patients that can be managed in community pharmacy from those who are at risk and should be evaluated by GPs. This tool potentially increases patients' safety by increasing pharmacists' ability to differentiate minor ailments from other medical conditions.

The potential of fecal microbiota and amino acids to detect and monitor patients with adenoma

ABSTRACT The risk of recurrent dysplastic colonic lesions is increased following polypectomy. Yield of endoscopic surveillance after adenoma removal is low, while interval colorectal cancers occur. To longitudinally assess the dynamics of fecal microbiota and amino acids in the presence of adenomatous lesions and after their endoscopic removal. In this longitudinal case–control study, patients collected fecal samples prior to bowel preparation before scheduled colonoscopy and 3 months after this intervention. Based on colonoscopy outcomes, patients with advanced adenomas and nonadvanced adenomas (0.5–1.0 cm) who underwent polypectomy during endoscopy (n = 19) were strictly matched on age, body-mass index, and smoking habits to controls without endoscopic abnormalities (n = 19). Microbial taxa were measured by 16S RNA sequencing, and amino acids (AA) were measured by high-performance liquid chromatography (HPLC). Adenoma patients were discriminated from controls based on AA and microbial composition. Levels of proline (p = .001), ornithine (p = .02) and serine (p = .02) were increased in adenoma patients compared to controls but decreased to resemble those of controls after adenoma removal. These AAs were combined as a potential adenoma-specific panel (AUC 0.79(0.64–0.94)). For bacterial taxa, differences between patients with adenomas and controls were found (Bifidobacterium spp.↓, Anaerostipes spp.↓, Butyricimonas spp.↑, Faecalitalea spp.↑ and Catenibacterium spp.↑), but no alterations in relative abundance were observed after polypectomy. Furthermore, Faecalitalea spp. and Butyricimonas spp. were significantly correlated with adenoma-specific amino acids. We selected an amino acid panel specifically increased in the presence of adenomas and a microbial signature present in adenoma patients, irrespective of polypectomy. Upon validation, these panels may improve the effectiveness of the surveillance program by detection of high-risk individuals and determination of surveillance endoscopy timing, leading to less unnecessary endoscopies and less interval cancer.

Infant delivery and maternal stress during the COVID-19 pandemic: a comparison of the well-baby versus neonatal intensive care environments.

ObjectiveTo describe impact of COVID-19 pandemic on stress and mood of new mothers, in particular in neonatal intensive care unit (NICU); a secondary objective was to assess whether customary social gender distancing practiced by ultra-religious Jews and Muslims offers built-in anti-stress protection.MethodsCross-sectional, observational survey of mothers of 52 normal newborn nursery (NNB) and 52 NICU infants. In all, 86 filled all the 6 questionnaires (Demographics, COVID-19 virus experience, Mental Health Inventory, Neonatal Satisfaction Survey, Parental Stressor Scale, and Questionnaire of Coping Strategies).ResultsMost mothers stated that COVID-19 pandemic had hurt social and family relationships, maternal role, and expressed stress and loneliness. Mothers of NICU infants had higher degree of helplessness. Religious social distancing was not protective. Background tendency to coping poorly with stress and depression most highly predicted stress.ConclusionCOVID-19 pandemic harms psychosocial well-being of most mothers. Detection of high-risk individuals is necessary to provide appropriate support.

Measurement of Homocysteine Levels in Pregnant Women with and Without Preeclampsia

Introduction: Homocysteine is associated with endothelial dysfunction and cardiovascular disease, and elevated concentrations of homocysteine have been found in preeclampsia. The aim of this study was to determine homocysteine levels in pregnant women with and without preeclampsia.
 Methods: This descriptive study conducted on pregnant women with preeclampsia (n = 39) and controls (n = 43) was evaluated by the convenience sampling and data were collected through a questionnaire and paraclinical findings. In the present study, 5cc blood samples were taken from the patients after 8 hours of fasting and sent to the laboratory to determine homocysteine and related metabolites levels. Statistical analyses were done using IBM-SPSS 25.0 and Chi-square test was used for data analysis.
 Results: The moderate concentrations of homocysteine and uric acid were significantly higher than the control group in maternal plasma with preeclampsia (0.0001).
 Conclusion: We found that the blood homocysteine levels were significantly higher in the preeclampsia group compared with the Controls group. Measuring uric acid and blood homocysteine levels in pregnancy may be helpful as diagnostic tests in the early detection of high risk individuals.

Abstract P195: Lipoprotein and Metabolite Biomarkers for Coronary and Peripheral Artery Disease: Blood Biomarker Profiling of 32,000 Individuals From Five Prospective Studies

Background: Coronary artery disease (CAD) and peripheral artery disease (PAD) share pathogenesis, but the evidence of metabolic risk factors underlying PAD risk is limited. We conducted detailed metabolic profiling of incident CAD and PAD to identify novel risk factors and clarify pathogenesis for these diseases. Methods: We measured circulating blood biomarkers using an NMR metabolomics in four large prospective studies from Finland (national FINRISK and Health 2000 studies, total n = 32,607). We used Cox proportional hazard modelling to estimate associations between biomarkers and incident CAD and PAD ( n events = 2010 and 464, respectively, during the median follow-up time of 14 years). Results: High VLDL-C increased the risk for CAD (HR=1.30, 95% CI 1.24-1.35 per SD-change), but not PAD (HR=1.09, 95% CI 0.99-1.21). Moreover, LDL-C and apolipoprotein B were only associated with CAD (HR=1.13, 95% CI 1.08-1.19; HR=1.29, 95% CI 1.23-1.35), whereas high triglycerides in LDL and VLDL increased the risk for both endpoints. Glycolysis-related metabolites (glucose, lactate, pyruvate and glycerol), amino acids (phenylalanine, alanine and glutamine) and inflammation biomarker glycoprotein acetyls (GlycA) showed stronger associations with PAD. Biomarker score showed stronger risk discrimination of high-risk individuals for incident PAD when compared to traditional CVD risk factors, suggesting that measuring these biomarkers could help to detect high-risk individuals better than currently used risk factors. Conclusions: We identified novel biomarkers for cardiovascular endpoints showed that the associations of these biomarkers were actually stronger for PAD compared to the CAD. Novel biomarkers could be used to guide the development of new therapies and improve the detection of high-risk individuals for these diseases. Figure. Associations between metabolic biomarkers and incident PAD and CAD.

Cost-utility analysis of genetic polymorphism universal screening in colorectal cancer prevention by detection of high-risk individuals

BackgroundIn the past 15 years numerous studies have been published on the involvement of low-penetrance susceptibility genes on the risk for developing colorectal cancer (CRC). AimTo perform an economic analysis of blood genetic testing in CRC screening in a population-based nationwide setting using polymorphisms in prostaglandin E2 pathway genes as proof of concept. MethodsA cost-utility analysis was performed from a societal perspective in Portugal comparing two strategies: blood genetic testing by the age of 40 versus no genetic screening under different assumptions of the cost of genetic testing (€10 and €30) and expected risk (1.5 to 5-fold). The adopted threshold was set at €44,870 (USD 50,000). The primary outcome was the incremental cost-effectiveness ratio (ICER) for a base case scenario. ResultsPolymorphism genotyping provided cost-utility only under the assumption of a 5-fold increased risk in the general population, providing ICERs of €44,356 and €30,389 for €30 and €10 tests, respectively. ConclusionBlood genetic screening for colorectal cancer has cost-utility only under specific assumptions of increased CRC risk and conservative cost estimates. Future studies should focus on defining genetic profiles because single-gene approaches are very unlikely to be cost-effective considering their modest predictive value.

What is the best age range to perform coronary artery calcification score in type 2 diabetic patients?

Coronary artery calcification score (CACs) has been shown to be useful for assessment of cardiovascular risk in diabetic patients without known coronary artery disease. CACs can be useful to detect high risk patients (CACs > 400) or low risk patients (CACs < 10). To check if CAC is discriminant to stratify the cardiovascular risk whatever the age is. A CACs was prospectively performed in 460 consecutive type 2 diabetic patients with ≥ 2 additional risk factors (age > 50 for men and > 60 for women, hypertension, current smoking, elevated LDL and albuminuria) but without any known coronary artery disease during a yearly check-up between January 2015 and December 2016. Mean age was 61 ± 10 [30–87] y.o. and 58% were male. Mean duration of diabetes was 15 ± 10 years and 35% were treated with insulin for a mean duration of 10 ± 8 years. Mean CAC score was 287 ± 30 [0–5983]. CACs = 0 was found in 25%, CACs < 10 in 39%, CACs < 100 in 61%, CACs > 400 in 20% and CACs > 1000 in 9% of the population. A significant relationship was found between CACs and duration of diabetes, waist circumference, creatinine level and GFR, albuminuria and LDL levels. CACs level was highly related to age: r = 0.522, P < 0.0001 ( Fig. 1 ). Mean CACs in the different age groups, as proportion of CACs < 10 or > 400 are presented in Table 1 . ROC curve analysis demonstrated that the threshold for detecting a high risk (CACs > 400) with a sensitivity > 95% was 55 y.o. In the other hand, the threshold for detecting a low risk (CACs < 10) with a sensitivity > 95% was 69 y.o. From our study, in type 2 diabetic patients without known coronary artery disease, the detection of high risk individuals (CACs > 400) is probably relevant after 55 y.o. and detection of low risk individuals (CACs < 10) before 69 y.o. We can conclude that the more discriminant age range for performing CAC score in this population of type 2 diabetic patients without known coronary artery disease is probably 55 to 69 y.o.

Abstract 1285: Analysis of esophageal cancer SNPs and gene expression to predict ESCC risk

Abstract Esophageal cancer is one of most common cancers worldwide and its incidence has increased rapidly over the past decades. The majority of esophageal cancers is the esophageal squamous cell carcinoma (ESCC), which is particularly prevalent in Asian and South African areas. Most cases of ESCC are diagnosed at advanced stages, with an overall 5-year survival rate of 10–20%. Currently, genome-wide association studies (GWAS) are used to identify high risk individuals for the development of ESCC. Many SNPs have been identified to associate with a risk of ESCC. However, the effect size attributable to individual SNPs was typically modest, suggesting that genetic variants may only account for a very small amount of genetic risk and heritability of ESCC. The combined effect of multi genetic variants with altered mRNA expression play critical roles in ESCC. In this study, we used several existing bioinformatics databases (HaploReg, GTEx Portal and cBio Portal). We first selected 450 potential ESCC risk SNPs from HaploReg and then defined which SNPs caused gene expression alterations in the esophagus through expression quantitative trait loci (eQTL). Nine SNPs in eight genes (MUC1, ALS2CR12, ADHB1, TMEM173, XBP1, PLCE1, HEATR3 and SMG6) were identified as having altered mRNA expression. The altered mRNA expression of these seventeen genes are: MUC1, THBS3, GBAP1, EFNA1, SCAMP3, CASP8, CASP10, ALS2CR12, STRADB, ADH4, TMEM173, CYCTM1, DNAJC18, DNAJC20, NOC3L, HEATR3 and SRR. These altered gene expressions in the mucosal layer of the esophagus metabolize enzymes, repair DNA, and prevent cell death and inflammation, all of which may indicate that the existing altered esophageal mRNA levels plus the predisposition of normal esophageal epithelial cells can lead to harmful environmental carcinogens, thus attributing to ESCC development. In order to validate these gene alterations related to ESCC SNPs in screening and early detection of high risk individuals, DNA genotyping of this group of SNPs with a prospective cohort (n=5451) in a high risk area of ESCC will be tested in future studies. Citation Format: Lilly A. Ding, Molly P. Ding, Xin Song, Lidong Wang, Liang Wang. Analysis of esophageal cancer SNPs and gene expression to predict ESCC risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1285. doi:10.1158/1538-7445.AM2017-1285

Acute phase proteins and diabetes microvascular complications

The association of serum high-sensitivity C-reactive protein and ferritin with diabetes microvascular complications has not been examined concurrently in people with type 2 diabetes. So, we carried out this study in order to investigate this association in a group of type 2 diabetic patients. In a prospective cross-sectional study, 242 people with type 2 diabetes were enrolled. All of the participants were evaluated for diabetes microvascular complications. Retinal status was evaluated by retinal color photography and indirect ophthalmoscopy exam with dilated pupils. Michigan neuropathy screening instrument was used for detection of peripheral neuropathy, and albumin/creatinine ratio in a spot urine sample was considered to diagnose diabetic nephropathy. High-sensitivity C-reactive protein and ferritin were measured as indicators of acute phase proteins. The mean for high-sensitivity C-reactive protein was 5.3 ± 13.02 mg/L, and for ferritin was 126.9 ± 114.4 ng/mL. Statistically significant difference was found between the high-sensitivity C-reactive protein levels and diabetic nephropathy. Spearman’s correlation coefficients test revealed that high-sensitivity C-reactive protein was positively correlated with diabetic nephropathy (P = 0.05, r = 0.14). However, such a correlation was not found for diabetic neuropathy and retinopathy. Using binary logistic regression analysis, a significant odds ratio was defined for nephropathy and high-sensitivity C-reactive protein level (OR = 2.62; CI = 1.13–6.06; P = 0.025). Our findings suggest that low-grade inflammation is an independent predictor of diabetic nephropathy and measurement of high-sensitivity C-reactive protein can be useful for early detection of high-risk individuals.

Abstract P234: Cardiovascular Risk Prediction With Minimal Physiologic Variables

Introduction: Cardiovascular risk prediction relies on physiologic parameters, limiting the utility of tools such as the Pooled Cohort Risk Equation (PCRE) for self-administration outside clinical contexts. Tools that can be widely administered in places such as stores or pharmacies that offer blood pressure (BP) assessment could increase detection of high risk individuals and motivate care seeking. We developed a risk prediction approach that relies only on BP and otherwise self-reported variables and compared it with the PCRE. Methods: We identified 16,833 in the REasons for Geographic AND Racial Differences in Stroke (REGARDS) study without coronary heart disease (CHD) and &lt;80 years of age at baseline. CHD and stroke were expert adjudicated. Data included variables required to calculate the PCRE, as well as variables for the BP-self-report models (sociodemographics, medical history, and items assessed by validated questionnaires [e.g., Short Form-12]). We developed two predictive models for the composite endpoint of incident CHD or stroke using 1) survival trees (Tree) and 2) generalized additive models (GAM). For 5 iterations the cohort was randomly partitioned into equal training and testing subsets. Tree models and GAM were fit using the training subset and predicted risks calculated for the testing subset using the PCRE, Tree and GAM methods. C-statistics were calculated overall and stratified by age dichotomized at 65 for each model. Results: For the overall cohort, the mean C-statistics over the 5 iterations were PCRE: 0.69 (Range 0.65-0.74); GAM BP-self-report: 0.70 (0.67-0.72); Tree BP-self-report: 0.59 (0.55-0.66). For participants aged over 65 years the GAM had the highest mean of 0.64 vs. 0.58 (PCRE) and 0.54 (Tree). See Figure. Conclusion: A predictive statistical model using only self-reported data and systolic BP can have similar predictive performance to the PCRE, with potential marginal improvement noted for subjects over age 65 years.

Cortisol response to stress in caregivers of offspring with autism spectrum disorder is associated with care recipient characteristics

Providing care for people with autism spectrum disorder (ASD) is particularly stressful and frequently associated with disturbances in the hypothalamic–pituitary–adrenal (HPA) axis of the caregiver. This study examined whether the stress response is modulated by factors such as age of the care recipient and number of years spent by the caregiver in providing care for the ASD individual. Caregivers of children (n = 15), adolescents (n = 12), and adults (n = 11) with ASD were exposed to two episodes of acute psychosocial stressor in a 1 day session. Salivary cortisol samples were obtained before, during, and after the stressor episodes. Psychological characteristics (states of anxiety, anger, and mood) were measured before and after the stressor episodes. The characteristics of the ASD individuals (age, degree of autism, global activity, and level of autonomy) were also registered. A difference in stress response was found when caregivers of ASD children were compared with those of ASD adolescents and adults, ε = 0.25, F(2.24,53.65) = 5.82, p < 0.004; ε = 0.23 and F(2.11,48.43) = 4.88, p < 0.01, respectively. Thus, upon acute-stressor exposure, caregivers of ASD individuals presented a stress response that correlated with the age of the patient (the older the patient, the lower the cortisol response). Additional factors, such as number of years spent providing care and level of autonomy of the recipient, also significantly contributed to the stress response. Together, the results demonstrate that recipient characteristics contribute to the detection of high-risk individuals within a caregiver population.

Significance of past history of renal failure for the detection of high-risk individuals for cardiovascular and end-stage renal disease: analysis of data from a nationwide health checkup

Clinical information regarding risk factors may be helpful in the detection of various diseases. This cross-sectional study examined the characteristics of subjects with past history of renal failure, and assessed whether this information would be useful for the efficient detection of high-risk individuals for chronic kidney disease (CKD) and cardiovascular disease (CVD) at health checkup. This study utilized data from a nationwide health checkup, "The Specific Health Check and Guidance in Japan," and data for 250,130 adult subjects were analyzed. Subjects with self-reported history of renal failure and receiving dialysis therapy were defined as having a history of renal failure. Among total participants, there were 1,400 (0.6%) with a history of renal failure. The prevalence of a history of renal failure was higher in subjects with CKD than in those without CKD (1.5 vs. 0.3%, P < 0.001) and increased with progression of the stage of CKD (0.9-43.5%). Subjects with a history of renal failure had a reduced estimated glomerular filtration rate (44.6 ± 20.3 ml/min/1.73 m(2)) and a higher prevalence of CKD (50.5%) and CVD (31.9%), compared with subjects with hypertension, diabetes or metabolic syndrome. Multivariate logistic regression analysis showed an independent association between a history of CVD and renal failure (odds ratio 3.68, 95% confidence interval 3.26-4.15), after adjustment for confounding factors. A history of renal failure was strongly associated with advanced CKD and CVD. Information regarding history of renal failure could be utilized to efficiently detect high-risk individuals at health checkup.

2011 Clinical Practice Guidelines for Type 2 Diabetes in Korea

As in other countries, type 2 diabetes is major health concern in Korea. A dramatic increase in the prevalence of type 2 diabetes and its chronic complications has led to an increase in health costs and economic burdens. Early detection of high risk individuals, hidden diabetic patients, and improvement in the quality of care for the disease are the first steps to mitigate the increase in prevalence. The Committee of Clinical Practice Guidelines of the Korean Diabetes Association revised and updated the '3rd Clinical Practice Guidelines' at the end of 2010. In the guidelines, the committee recommended active screening of high risk individuals for early detection and added the hemoglobin A1c level to the diagnostic criteria for type 2 diabetes based on clinical studies performed in Korea. Furthermore, the committee members emphasized that integrating patient education and self-management is an essential part of care. The drug treatment algorithm based on the degree of hyperglycemia and patient characteristics were also updated.

Clinical and Epidemiological Metabonomics

Metabonomics is an omics approach to identify and monitor metabolic characteristics, changes, and phenotypes with respect to various synergetic factors such as environment, life style, diet, and potential pathophysiological processes. Recently, metabonomics has also opened up a possibility for functional genomics in large genome-wide studies. Mass spectrometry (MS) and proton nuclear magnetic resonance (NMR) spectroscopy are the two key experimental technologies in the field. Recent advancements are numerous, and methodologies currently exist that allow for automated high-throughput experimentation in a very cost-effective manner. Technical developments have evoked an increasing number of metabonomics applications in clinical and epidemiological disciplines to understand the complex molecular foundations of various diseases. Techniques with the aim of assessing large numbers of metabolites that are substrates, intermediates, or products in various metabolic pathways are particularly relevant in the risk assessment of metabolic conditions like diabetes and vascular diseases. It has also been envisioned that metabonomics approaches may overtake standard analytical measurements of individual metabolites and eventually lead to holistic multimetabolic risk phenotyping in the early detection of high-risk individuals for various metabolic diseases. Thus, metabonomics offers potential means to move away from single biomarkers and thresholds in clinical medicine. And, furthermore, even though the current medical biomarkers and thresholds are necessary benchmarks for clinical practice, it will be crucial to let the future diagnostics to follow from new science. Good predictions are necessary for effective prevention; an important step towards this is expected to happen when complex traits will not anymore be limited by clinical diagnoses and definitions but will be handled as multivariate continuous dimensions. Consequently, clinical and epidemiological metabonomics is likely to be one of the key new omics areas to assist translational research in the near future. Here, the Journal of Biomedicine and Biotechnology presents this special issue, 2011. Although only representing a small fraction of the contribution of metabonomics to various biomedical disciplines, the papers presented here show the increasing potential of metabonomics approaches to complement clinical and epidemiological research. To start the special issue, we have five contributions that review several aspects of metabonomics research. M. G. Barderas et al. discuss the concepts of metabolic profiling, fingerprinting, and footprinting focusing on the area of cardiovascular diseases. E. Silvestri and coworkers discuss the timely and relevant issue of integrative analyses of related omics data sets in order to furnish new insights not accessible through one-dimensional data. Further, I. Kouskoumvekaki and G. Panagiotou give an extensive up-to-date overview on the database resources on metabolic pathways and metabolomes and also summarize the statistical tools often used for the analysis of metabonomics data. Y. Kim and S. Milner deal with the challenges related to bioactive food components in cancer research and prevention. Moreover, M. Sofia and coauthors review the potential use of exhaled breath condensate as a suitable matrix for NMR-based metabonomics of airway diseases. This special issue contains two methodology reports. G. Kastenmuller and coworkers have developed a freely accessible methodology to facilitate automated and standardized analysis for quantitative metabolic data, covering the steps from data acquisition to biological interpretation. M. C. Martinez-Bisbal and colleagues, using magnetic resonance microscopy, present a critical and valuable interpretation on the high-resolution magic angle spinning data of human tumor tissues. The six original research papers in this special issue start with the paper by J. Willmann et al. who demonstrate the advantage of combining high-pressure liquid chromatography, MS, and NMR spectroscopy in analyzing three different types of extracts of a common membrane component phosphatidylcholine. Then, D. F. Brougham et al. focus on the use of artificial neural networks in classifying proton NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, displaying different drug-resistance patterns. In a mouse study, D. Otter et al. apply MS-based nontargeted urinary metabolite profiling to identify biomarkers of colon inflammation. In another mouse study, J. Zhou et al. provide evidence that NMR metabonomics may be sensitive enough to detect small differences in the composition of maternal plasma and thus be helpful for identifying biomarkers of birth defects. Additionally, in low-birth weight and high-birth weight piglets P. M. Nissen and coworkers combine NMR and MS to reveal a relationship between birth weight and plasma inositols, suggesting their potential role in fetal programming of type 2 diabetes. L. Guo et al. end this special issue in providing the latest epidemiologic information on the etiology distribution of neurodevelopmental disabilities in Chinese, and by demonstrating, on the basis of 8-year clinical experience, that MS-based pediatric metabonomics is clinically helpful. Overall, we hope that this special issue hints at the rising potential of metabonomics approaches in clinical and epidemiological research and translational medicine. Mika Ala-Korpela Veikko Salomaa Olav M. Kvalheim

Introducing the shape of globe as a predisposing factor for glaucoma

Glaucoma is a common blinding disease worldwide with a number of risk factors such as intraocular pressure, myopia, gender, race and hyperopia. Here we introduce eyeball's shape as a predisposing factor for glaucoma. If the eyeball is a sphere, the stress distribution is homogenous. We assume the eyeball as a non sphere. Then, the distribution of stress will not be homogenous. Different individuals have different eyeball's shapes and different patterns of stress distribution in their eyes. So based on the eyeball's shape deviation from a sphere they will have different risks for glaucoma. The eyeball is routinely considered as a sphere, but some evidences show that the globe is not a sphere. Two empirical observations are consistent with the hypothesis. The first is that ethnicity and sex are established risk factors for glaucoma. On the other hand there are several morphological differences in the body structure among individuals. According to these anatomical differences, eye's shape is different among different races and between two sexes. Secondly, there are some conditions such as myopia and hyperopia in them the shape of the globe has been changed. These conditions are risk factors for glaucoma too. Glaucoma screening program for early detection of high risk individuals is very important. Current diagnostic procedures of glaucoma do not take the shape of eyeball into account. We suggest using eyeball's shape for early glaucoma detection. There are three other factors in addition to eyeball's shape, including thickness of the globe's wall, intraocular pressure, and inner radius that should be measured together for each individual and stress load should be calculated in different points of the globe. Then eyes with more stress load in site of injury are more prone for glaucoma. More accurate measurements of the factors which are contributing in stress value for each case, lead us toward better glaucoma screening.

The role of psychosocial stressors, personality and coping in the multifactorial origin, initiation and clinical course of neoplastic disease and in host-deffense

Retrospective and prospective biobehavioral cancer studies have revealed that psychosocial stressors may play a pivotal role in the initiation and progression of malignant neoplasia. In recent research, a pattern has emerged, which in analogy to the coronary prone pattern (type A) has been labelled type C, encompassing suppression of emotional responses, such as anger and hostility, rationality and antiemotionality, as well as high social conformity and a lack of self-assertiveness. There is growing evidence in both infrahuman and human research that specific coping styles (repressive coping) with stress may be associated with specific biologic responses, including neuroendocrine, immunologic and other bodily functions. The application of this model appears to be of importance for further research, as well as for the detection of high risk individuals, but also in regard to therapy, rehabilitation, early detection and possibly also prevention of malignant disease. This concept suggests also new directions and modifications of stress research, as stressors are to be viewed not necessarily as pathological, but in some instances as quite possibly salutary, depending on the nature of the stressor, the psychophysiologic state of the individual and his or her ability to cope with adverse life situations. Quite naturally, the development of this concept is still in its initial stages, there remain a number of open questions, and it needs hardly to be pointed out in this connection that further and painstaking clinical and laboratory work is warranted in order to clarify the role of stressors, life and coping styles and its biological concomitants in neoplastic disease.

Lack of linkage between HLA and multiple endocrine neoplasia type 2 in a French family.

In this study, linkage between HLA and a dominant gene determining multiple endocrine neoplasia type 2 (MEN 2) in a large pedigree was investigated. All lod scores for recombination fractions ranging from 0 to 0.45 were negative. If we pool data from our family and the families studied by Jackson et al. (1976) and Simpson & Falk (1982), a link between HLA and the locus for MEN 2 can be excluded. Linkage studies with various markers and pooled data should be pursued to permit detection of high risk individuals and to identify a genetic defect.