Diabetes and bacterial co-infection are two independent risk factors for respiratory syncytial virus disease severity.

Diabetes mellitus (DM) is common among older adults hospitalized with lower respiratory tract infection, yet information on the impact of DM on disease severity is limited. This study retrospectively analyzed 46 Turkish patients infected with respiratory syncytial virus (RSV), with information on their comorbidities, co-infection status, and symptoms. Patients are grouped into four severity levels from mild to severe, according to lung parenchymal infiltration status and oxygen level. Similar to previously published studies, we found that comorbidities of diabetes, heart failure, hypertension, co-infection of any type, bacterial co-infection, and age are associated with the disease severity. Cough is the most common symptom (89%) followed by fever (26%) and myalgia, dyspnea, and weakness (around 20%). Using a second-order analysis (two-variable regression), we identified two independent risks for disease severity, the first is represented by diabetes, and the second is represented by bacterial co-infection. We observed two patients whose more severe symptoms were not associated with an older age, but associated with a combination of diabetes and bacterial co-infection. To confirm the true causality from the statistical correlation, further studies are needed.

Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events.

COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r ) < 0; This relation is a direct consequence of the nature of the two events; and (3) there is a tendency for a reciprocal relation between csHR d and csHR r : csHR d ∼ 1/csHR r . Though an approximate reciprocal trend between the two hazard ratios is in indication that the same factor causing faster death also lead to slow recovery by a similar mechanism, and vice versa, a quantitative relation between csHR d and csHR r in this context is not obvious. These results may help future analyses of data from COVID-19 or other similar diseases, in particular if the deceased patients are lacking, whereas surviving patients are abundant.

Blood-Type-A is a COVID-19 infection and hospitalization risk in a Turkish cohort.

We have shown in an ethnically homogenous Turkey cohort with more than six thousand cases and 25 thousand controls that ABO blood types that contain anti-A antibody (O and B) are protective against COVID-19 infection and hospitalization, whereas those without the anti-A antibody (A and AB) are risks. The A + AB frequency increases from 54.7 % in uninfected controls to 57.6 % in COVID-19 outpatients, and to 62.5 % in COVID-19 inpatients. The odds-ratio (OR) for lacking of anti-A antibody risk for infection is 1.16 (95 % confidence interval (CI) 1.1-1.22, and Fisher test p-value 1.8 × 10-7). The OR for hospitalization is 1.23 (95 %CI 1.06-1.42, Fisher test p-value 0.005). A linear regression treating controls, outpatients, inpatients as three numerical levels over anti-A antibody leads to a p-value of 5.9 × 10-9. All these associations remain to be statistically significant after conditioning over age, even though age itself is a risk for both infection and hospitalization. We also attempted to correct the potential effect from vaccination, even though vaccination information is not available, by using the date of the data collection as a surrogate to vaccination status. Although no significant association between infection/hospitalization with Rhesus blood system was found, forest plots are used to illustrate possible trends.

A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort.

Having a complete and reliable list of risk factors from routine laboratory blood test for COVID-19 disease severity and mortality is important for patient care and hospital management. It is common to use meta-analysis to combine analysis results from different studies to make it more reproducible. In this paper, we propose to run multiple analyses on the same set of data to produce a more robust list of risk factors. With our time-to-event survival data, the standard survival analysis were extended in three directions. The first is to extend from tests and corresponding p-values to machine learning and their prediction performance. The second is to extend from single-variable to multiple-variable analysis. The third is to expand from analyzing time-to-decease data with death as the event of interest to analyzing time-to-hospital-release data to treat early recovery as a meaningful event as well. Our extension of the type of analyses leads to ten ranking lists. We conclude that 20 out of 30 factors are deemed to be reliably associated to faster-death or faster-recovery. Considering correlation among factors and evidenced by stepwise variable selection in random survival forest, 10 ~ 15 factors seem to be able to achieve the optimal prognosis performance. Our final list of risk factors contain calcium, white blood cell and neutrophils count, urea and creatine, d-dimer, red cell distribution widths, age, ferritin, glucose, lactate dehydrogenase, lymphocyte, basophils, anemia related factors (hemoglobin, hematocrit, mean corpuscular hemoglobin concentration), sodium, potassium, eosinophils, and aspartate aminotransferase.

Alpha variant (B.1.1.7) of SARS-CoV-2 increases fatality-rate for patients under age of 70 years and hospitalization risk overall.

The emergence of new SARS-CoV-2 variants is a challenge to the control of this pandemic. It is therefore important to collect and to analyze data related to the infection caused by different variants. We have obtained more than 3,700 COVID-19 patients between April 2020 and March 2021 from Tokat, Turkey (roughly 3,100 outpatients and close to 600 inpatients) where about 30% were infected with Alpha variant (B.1.1.7). Descriptive statistics was used to characterize different subgroups. Both logistic regression and cause-specific Cox survival analysis of competing-risk was run on inpatients, to examine the impact of Alpha variant on hospitalization, on mortality and on other factors. We observed that the Alpha variant is over-represented in inpatients than outpatients so infection by Alpha variant increases the chance for hospitalization. The impact of Alpha variant on mortality seems to depend on the patient's age. For patients under age of 70, the case-fatality-rate was 0.84% (5.3%) for patients without (with) Alpha variant (Fisher's test P-value = 2.4 × 10-10). For patients above age of 70, the trend is opposite: the case-fatality-rate is 31.5% (13.6%) for patients without (with) Alpha variant (Fisher's test P-value = 0.0016). The two opposite trends would cancel each other, making other analyses such as cause-specific Cox regression and logistic regression non-significant. The Alpha variant increases the risk for hospitalization, increases the case-fatality-rate for lower age group, and decreases the case-fatality-rate for the upper age group. If the increase of case-fatality-rate in not the most senior group holds true, it should provide useful information for a vaccination planning to counter the impact of Alpha variants.

Relationship between Thyroid Hormone Levels and Crime Type: A Controlled Study in Prisoners.

Various factors cause aggression, which can be related to imbalance of T3 and T4 hormones, which can act as neurotransmitters and are reported to be elevated during aggression. This indicates changes in the hypothalamic-pituitary-thyroid axis that cause long-term changes in aggressive behaviour, especially in criminals. Moreover, mental and behavioural disorders possibly occur in individuals with impairment in thyroid hormone balance. The main rationale for this study was to asses if high T3, high T4, and low TSH hormones may have an effect on aggression-related crime tendency. Furthermore, the study aimed to measure levels of thyroid hormones in prisoners and to examine relationships of the hormone levels with crime rates. Our study was conducted in Ankara Sincan Closed Prisons. The study group consisted of 208 male volunteers who were imprisoned and the control group included 82 male volunteers who were not imprisoned. Prisoners in the study group were divided into two groups: those who committed aggression-related crime (Group A, n = 96) and prisoners convicted of other crimes (Group B, n = 112). Pulse rates, T3, T4, and thyroid-stimulating hormone (TSH) levels, and theT3/T4 ratio were measured in these prisoners. Data were analysed using the Wilcoxon rank sum test and chi-square Fisher's exact test to test for any statistically significant differences. Results showed that toxic goitre rates, T3 and T4 values, and pulse rates were significantly higher in Group A than in the control group. Significant increase in T3 and T4 levels and the presence of toxic goitre were associated with aggression-related crime. These examinations should be performed on prisoners in general, especially those convicted of violent crimes. Additional rehabilitation and research programs should also be developed for such patients.

Thought Disorder in Schizophrenia and Bipolar Disorder Probands, Their Relatives, and Nonpsychiatric Controls.

Thought disorder (TD) has long been associated with schizophrenia (SZ) and is now widely recognized as a symptom of mania and other psychotic disorders as well. Previous studies have suggested that the TD found in the clinically unaffected relatives of SZ, schizoaffective and bipolar probands is qualitatively similar to that found in the probands themselves. Here, we examine which quantitative measures of TD optimize the distinction between patients with diagnoses of SZ and bipolar disorder with psychotic features (BP) from nonpsychiatric controls (NC) and from each other. In addition, we investigate whether these same TD measures also distinguish their respective clinically unaffected relatives (RelSZ, RelBP) from controls as well as from each other. We find that deviant verbalizations are significantly associated with SZ and are co-familial in clinically unaffected RelSZ, but are dissociated from, and are not co-familial for, BP disorder. In contrast, combinatory thinking was nonspecifically associated with psychosis, but did not aggregate in either group of relatives. These results provide further support for the usefulness of TD for identifying potential non-penetrant carriers of SZ-risk genes, in turn enhancing the power of genetic analyses. These findings also suggest that further refinement of the TD phenotype may be needed in order to be suitable for use in genetic studies of bipolar disorder.

Evidence for a pleiotropic QTL on chromosome 5q13 influencing both time to asthma onset and asthma score in French EGEA families.

Although many genome screens have been conducted for asthma as a binary trait, there is limited information regarding the genetic factors underlying variation of asthma expression. Phenotypes related to variable disease expression include time to asthma onset and variation in clinical expression as measured by an asthma score built from EGEA data. A recent genome scan conducted for this score led to detection of a new region (18p11) not revealed by analysis of dichotomous asthma. Our goal was to characterize chromosomal regions harboring genes underlying time to asthma onset and to search for pleiotropic QTL influencing both time to asthma onset and the asthma score. We conducted a genome-wide linkage screen for time to asthma onset, modeled by martingale residuals from Cox survival model, in EGEA families with at least two asthmatic sibs. This was followed by a bivariate linkage scan of these residuals and asthma score. Univariate linkage analysis was performed using the Maximum Likelihood Binomial method that we extended to bivariate analysis. This screen revealed two regions potentially linked to time to asthma onset, 1p31 (LOD = 1.70, P = 0.003) and 5q13 (LOD = 1.87, P = 0.002). Bivariate linkage analysis led to a substantial improvement of the linkage signal on 5q13 (P = 0.00007), providing evidence for a pleiotropic QTL influencing both variation of time to asthma onset and of clinical expression. Use of quantitative phenotypes of variable disease expression and suitable statistical methodology can improve the power to detect new regions harboring genes which may play an important role in onset and course of disease.

A comparative study of profile changes with 3 different distalization mechanics.

AIM: To compare the effects of 3 molar distalization appliances, the intraoral bodily molar distalizer, the Keles slider, and the acrylic cervical occipital appliance, from the viewpoint of skeletal and soft tissue changes. MATERIAL AND METHODS: Lateral cephalometric films taken before and immediately after distalization of 51 patients comprised the study material of this investigation. The lateral cephalograms were digitized and measured with Dolphin Imaging 9.0. RESULTS: The intraoral bodily molar distalizer showed the most forward movement of the lips, with respect to E-plane. The maxillary incisal proclination presented by the U1-SN angle revealed that the most prominent proclination was caused by the intraoral bodily molar distalizer, followed by the acrylic cervical occipital appliance. The appliance that showed the most vertical opening was the intraoral bodily molar distalizer, followed by the acrylic cervical occipital appliance. ANB is the only sagittal skeletal parameter with a change: an increase with the intraoral bodily molar distalizer. CONCLUSION: The most prominent soft tissue profile changes were observed with the intraoral bodily molar distalizer. The acrylic cervical occipital appliance and the Keles slider generated milder changes on the profile. When selecting the appropriate method for maxillary molar distalization, the initial soft tissue profile should be considered.

Comparing single-nucleotide polymorphism marker-based and microsatellite marker-based linkage analyses.

We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue.

Percentiles of the null distribution of 2 maximum lod score tests.

We here consider the null distribution of the maximum lod score (LOD-M) obtained upon maximizing over transmission model parameters (penetrance values, dominance, and allele frequency) as well as the recombination fraction. Also considered is the lod score maximized over a fixed choice of genetic model parameters and recombination-fraction values set prior to the analysis (MMLS) as proposed by Hodge et al. The objective is to fit parametric distributions to MMLS and LOD-M. Our results are based on 3,600 simulations of samples of n = 100 nuclear families ascertained for having one affected member and at least one other sibling available for linkage analysis. Each null distribution is approximately a mixture p(2)(0) + (1 - p)(2)(v). The values of MMLS appear to fit the mixture 0.20(2)(0) + 0.80chi(2)(1.6). The mixture distribution 0.13(2)(0) + 0.87chi(2)(2.8). appears to describe the null distribution of LOD-M. From these results we derive a simple method for obtaining critical values of LOD-M and MMLS.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

BACKGROUND: We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. RESULTS: We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. CONCLUSION: Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.