Testing Mediation Effects in High-Dimensional Microbiome Data with False Discovery Rate Control

Background: Understanding whether and which microbes played a mediating role between an exposure and a disease outcome are essential for researchers to develop clinical interventions to treat the disease by modulating the microbes. Existing methods for mediation analysis of the microbiome are often limited to a global test of community-level mediation or selection of mediating microbes without control of the false discovery rate (FDR). Further, while the null hypothesis of no mediation at each microbe is a composite null that consists of three types of null (no exposure-microbe association, no microbe-outcome association given the exposure, or neither), most existing methods for the global test such as MedTest and MODIMA treat the microbes as if they are all under the same type of null. Results: We propose a new approach based on inverse regression that regresses the (possibly transformed) relative abundance of each taxon on the exposure and the exposure-adjusted outcome to assess the exposure-taxon and taxon-outcome associations simultaneously. Then the association p-values are used to test mediation at both the community and individual taxon levels. This approach fits nicely into our Linear Decomposition Model (LDM) framework, so our new method is implemented in the LDM and enjoys all the features of the LDM, i.e., allowing an arbitrary number of taxa to be tested, supporting continuous, discrete, or multivariate exposures and outcomes as well as adjustment of confounding covariates, accommodating clustered data, and offering analysis at the relative abundance or presence-absence scale. We refer to this new method as LDM-med. Using extensive simulations, we showed that LDM-med always controlled the type I error of the global test and had compelling power over existing methods; LDM-med always preserved the FDR of testing individual taxa and had much better sensitivity than alternative approaches. In contrast, MedTest and MODIMA had severely inflated type I error when different taxa were under different types of null. The flexibility of LDM-med for a variety of mediation analyses is illustrated by the application to a murine microbiome dataset, which identified a plausible mediator.Conclusions: Inverse regression coupled with the LDM is a strategy that performs well and is capable of handling mediation analysis in a wide variety of microbiome studies.

Effect of concomitant diseases on the hemostasis system in the perioperative period of non-cardiac surgery

В данном исследовании изучалось влияние клинических факторов и антитромботической терапии на свертывающую систему крови пациентов в периоперационном периоде. В исследование включено 80 пациентов, которым проводилось плановое некардиальное хирургическое вмешательство. Лабораторный контроль осуществлялся с использованием рутинных методов исследования гемостаза (АЧТВ, МНО) и глобального теста исследования гемостаза (тест тромбодинамики). Использование теста тромбодинамики в данном исследовании оказалось более чувствительным методом по сравнению с рутинными тестами и позволило выявить клинические факторы, ассоциированные с гиперкоагуляционными состояниями и снижением эффективности низкомолекулярных гепаринов в послеоперационном периоде: возраст старше 60 лет, фибрилляция предсердий, хроническая ишемическая болезнь сердца, стентирование коронарных артерий в анамнезе, предшествующий прием антитромботической терапии до оперативного вмешательства. У больных с тромбозом глубоких вен нижних конечностей отмечалась гиперкоагуляция в первые сутки после проведения операции по сравнению с остальными пациентами. Использование теста тромбодинамики за сутки до оперативного вмешательства позволило спрогнозировать увеличение объема интраоперационной кровопотери. Назначение периоперационной мост-терапии низкомолекулярными гепаринами у больных с высоким тромботическим риском достоверно ассоциировалось с увеличением трансфузии эритромассы практически в 2 раза по сравнению с остальными пациентами и было связано с повышением риска геморрагических осложнений. Результаты исследования показали, что тест тромбодинамики потенциально может быть применен в дальнейших исследованиях с целью персонификации ведения пациентов в периоперационном периоде при некардиальной хирургии, а также способен прогнозировать возникновение геморрагических и тромботических осложнений. This study examined the effect of clinical factors and antithrombotic therapy on the blood coagulation system of patients in the perioperative period. The study included 80 patients who underwent elective noncardiac surgery. Laboratory control of hemostasis was carried out using routine tests for studying hemostasis (APTT, INR) and a global test for hemostasis (thrombodynamics test). Usage of the thrombodynamics test in this study was more sensitive compared to routine tests and made it possible to identify clinical factors associated with hypercoagulable states and «decreasing in the effectiveness» of low molecular weight heparins in the postoperative period. These factors are: age over 60 years, chronic ischemic heart disease, a history of coronary artery stenting, prior antithrombotic therapy before surgery. Hypercoagulability was found on the first day after surgery in patients with deep vein thrombosis of the lower extremities compared to other patients. The use of a thrombodynamics test a day before surgery allowed to predict an increase of intraoperative blood loss volume. Perioperative bridge therapy with low molecular weight heparins in high thrombotic risk patients was significantly associated with an increase in packed red blood cells transfusion of almost two times compared with other patients and is associated with an increased risk of hemorrhagic complications. The results of the study showed that thrombodynamics test can potentially be used further with the aim of personalizing patients’ management in the non-cardiac surgery perioperative period. It also helps to predict the occurrence of hemorrhagic and thrombotic complications.

Preventive treatment with CGRP monoclonal antibodies restores brain stem habituation deficits and excitability to painful stimuli in migraine: results from a prospective case-control study

Background & Objectives Calcitonin gene-related peptide ligand/receptor (CGRP) antibodies effectively reduce headache frequency in migraine. It is understood that they act peripherally, which raises the question whether treatment merely interferes with the last stage of headache generation or, alternatively, causes secondary adaptations in the central nervous system and might thus possess disease modifying potential. This study addresses this question by investigating the nociceptive blink reflex (nBR), which is closely tied to central disease activity, before and after treatment with CGRP antibodies. Methods We enrolled 22 patients suffering episodic migraine (21 female, 46.2 ± 13.8 years of age) and 22 age-/gender-matched controls. Patients received assessments of the nBR (R2 component, 10 trials, 6 stimuli/trial) before (V0) and three months (V3) after treatment with CGRP antibodies started, controls were assessed once. The R2 area (R2a) and habituation (R2h; gradient of R2a against stimulus order) of the stimulated/non-stimulated side (_s/_ns) following repeated supraorbital stimulation provide a direct readout of brainstem excitability and habituation as key mechanisms in migraine. Results All patients showed a substantial reduction of headache days/month (V0: 12.4±3.3, V3: 6.6 ± 4.9). R2a_s (Fglobal=5.86, p<0.001; block 1: R2a_s: -28%, p<0.001) and R2a_ns (Fglobal=8.22, p<0.001, block 1: R2a_ns: -22%, p=0.003) were significantly decreased, and R2h_ns was significantly enhanced (Fglobal=3.07, p<0.001; block 6: R2h_ns: r=-1.36, p=0.007) from V0 to V3. The global test for changes of R2h_s was non-significant (Fglobal=1.46, p=0.095). Changes of R2h significantly correlated with improvement of headache frequency (R2h_s, r=0.56, p=0.010; R2h_ns: r=0.45, p=0.045). None of the nBR parameters assessed at baseline predicted treatment response. Discussion We provide evidence that three months of treatment with CGRP antibodies restores brain stem responses to painful stimuli and thus might be considered disease modifying. The nociceptive blink reflex may provide a biomarker to monitor central disease activity. Future studies should evaluate the blink reflex as a clinical biomarker to predict treatment response at baseline and to establish the risk of relapse after treatment discontinuation. Trial registration This trial was prospectively registered at clinicaltrials.gov (ID: NCT04019496, date of registration: July 15, 2019).

Survival Analysis on Time-To-Recovery of Diabetic Patients at Minlik Referral Hospital, Ethiopia: Retrospective Cohort Study

AimThe study aimed to determine the time to recovery of diabetic patients who have been treated in the hospital under follow-up. Subject and MethodsA retrospective cohort study design was carried out. The fast blood glucose level of diabetic patients who are under follow-up in the hospital was measured from 2016 to 2020. One thousand seven hundred diabetic patients were included in the study. Kaplan-Meier, Log-rank test, global test, Schoenfeld residuals, and Cox-PH model were used for statistical analysis.ResultsOut of the total of 1278 patients, 27.4% were censored (withdrawal from follow-up) and 72.6% recovered from the diabetic disease. For sex, the expected hazard is 1.322 times higher in males than female diabetic patients or there is a 32.2% increase in the expected hazard in males relative to female diabetic patients. For Spdrt, The expected hazard is 1.164 times higher in the patients who had taken leute than diabetic patients who took doanied. For regimen, the expected hazard is 1.495 times higher in the patients who had been treated by insulin agent only than diabetic patients who were treated by oral agents only ConclusionThe intensive-therapy regimen, Spdrt, and gender differences were statistically significant and critically contribute to the survival time to recovery of diabetic patients.

Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis

Background: The causal relationship between childhood obesity and stroke remains unclear. Our objective was to elucidate the causal relationship between childhood obesity and the risk of stroke and its subtypes by performing Mendelian randomisation (MR) analyses.Methods: Genetic instruments for childhood obesity were obtained from a genome-wide association study (GWAS) of 13,848 European participants. Summary level data for stroke, intracerebral haemorrhage, ischaemic stroke (IS), and its subtypes were evaluated using the MEGASTROKE GWAS dataset, which included 446,696 European adults. Inverse-variance weighting, weighted-median analysis, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR-Robust Adjusted Profile Score were applied in this MR analysis. The leave-one-out sensitivity test, MR-PRESSO Global test, and Cochran’s Q test were conducted to confirm the accuracy and robustness of our results.Results: Genetic evaluations revealed that childhood obesity was associated with a higher risk of stroke (OR = 1.04, 95%CI: 1.01–1.07, p = 0.005) and IS (OR = 1.05, 95%CI: 1.02–1.08, p = 0.003), but not with intracerebral haemorrhage (ICH, OR = 0.93, 95%CI: 0.80–1.09, p = 0.39). In the subtype analysis, childhood obesity was also associated with large artery stroke (LAS, OR = 1.12, 95%CI: 1.02–1.22, p = 0.016) but not with cardioembolic stroke (OR = 1.06, 95%CI: 0.96–1.18, p = 0.21) and small vessel stroke (OR = 1.06, 95%CI: 0.98–1.15, p = 0.17). These results were stable in the sensitivity analysis and remained significant after Bonferroni correction.Conclusion: Our study provides evidence that childhood obesity is associated with a higher risk of stroke, IS, and LAS. The prevention of stroke, especially IS and LAS, should be promoted in populations with childhood obesity.

A New Approach to Testing Mediation of the Microbiome using the LDM

Background: Understanding whether and which microbes played a mediating role between an exposure and a disease outcome are essential for researchers to develop clinical interventions to treat the disease by modulating the microbes. Existing methods for mediation analysis of the microbiome are often limited to a global test of community-level mediation or selection of mediating microbes without control of the false discovery rate (FDR). Further, while the null hypothesis of no mediation at each microbe is a composite null that consists of three types of null (no exposure-microbe association, no microbe-outcome association given the exposure, or neither), most existing methods for the global test such as MedTest and MODIMA treat the microbes as if they are all under the same type of null. Methods: We propose a new approach based on inverse regression that regresses the (possibly transformed) relative abundance of each taxon on the exposure and the exposure-adjusted outcome to assess the exposure-taxon and taxon-outcome associations simultaneously. Then the association p-values are used to test mediation at both the community and individual taxon levels. This approach fits nicely into our Linear Decomposition Model (LDM) framework, so our new method is implemented in the LDM and enjoys all the features of the LDM, i.e., allowing an arbitrary number of taxa to be tested, supporting continuous, discrete, or multivariate exposures and outcomes as well as adjustment of confounding covariates, accommodating clustered data, and offering analysis at the relative abundance or presence-absence scale. We refer to this new method as LDM-med. Results: Using extensive simulations, we showed that LDM-med always controlled the type I error of the global test and had compelling power over existing methods; LDM-med always preserved the FDR of testing individual taxa and had much better sensitivity than alternative approaches. In contrast, MedTest and MODIMA had severely inflated type I error when different taxa were under different types of null. The flexibility of LDM-med for a variety of mediation analyses is illustrated by the application to a murine microbiome dataset. Availability and Implementation: Our new method has been added to our R package LDM, which is available on GitHub at https://github.com/yijuanhu/LDM.

Clinically Relevant Circulating Protein Biomarkers for Type 1 Diabetes: Evidence From a Two-Sample Mendelian Randomization Study

OBJECTIVE <p>To identify circulating proteins influencing type 1 diabetes susceptibility using Mendelian randomization (MR). </p> <p>RESEARCH DESIGN AND METHODS</p> <p>We employed a large-scale two-sample MR study, using <i>cis</i> genetic determinants (protein quantative trait loci or pQTL) of up to 1,611 circulating proteins from five large genome-wide association studies, to screen for causal associations of these proteins with type 1 diabetes risk in 9,684 cases with type 1 diabetes and 15,743 controls. Further, pleiotropy-robust MR methods were used in sensitivity analyses using both <i>cis </i>and <i>trans</i>-pQTL.</p> <p>RESULTS </p> <p>We found that a genetically predicted a standard deviation increase in Signal Regulatory Protein Gamma (SIRPG) level was associated with increased risk of type 1 diabetes risk (MR OR = 1.66, 95% 1.36- 2.03; P = 7.1 x 10^-7). The risk of type 1 diabetes increased almost two-fold per genetically predicted SD increase in interleukin-27 Epstein-Barr Virus Induced 3 (IL27-EBI3) protein levels (MR OR=1.97, 95% CI = 1.48 – 2.62, P= 3.7 x10^-6). However, a SD increase in chymotrypsinogen B1 (CTRB1) was associated with decreased risk of type 1 diabetes (MR OR=0.84, 95% CI = 0.77 – 0.90, P= 6.1 x10^-6). <a></a></p> <p>Sensitivity analyses using MR methods testing for pleiotropy while including <i>trans</i>-pQTL showed similar results. While the MR-Egger suggested no pleotropic effect (<i>p</i>-value MR-Egger intercept = 0.31) there was evidence of pleiotropy in MR-PRESSO (<i>p</i>-value global test =0.006). </p> <p>CONCLUSIONS</p> <p>We identified three novel circulating protein biomarkers associated with type 1 diabetes risk using a MR approach. These biomarkers are promising targets for development of drugs and/or of screening tools for early prediction of type 1 diabetes. </p>

Clinically Relevant Circulating Protein Biomarkers for Type 1 Diabetes: Evidence From a Two-Sample Mendelian Randomization Study

OBJECTIVE <p>To identify circulating proteins influencing type 1 diabetes susceptibility using Mendelian randomization (MR). </p> <p>RESEARCH DESIGN AND METHODS</p> <p>We employed a large-scale two-sample MR study, using <i>cis</i> genetic determinants (protein quantative trait loci or pQTL) of up to 1,611 circulating proteins from five large genome-wide association studies, to screen for causal associations of these proteins with type 1 diabetes risk in 9,684 cases with type 1 diabetes and 15,743 controls. Further, pleiotropy-robust MR methods were used in sensitivity analyses using both <i>cis </i>and <i>trans</i>-pQTL.</p> <p>RESULTS </p> <p>We found that a genetically predicted a standard deviation increase in Signal Regulatory Protein Gamma (SIRPG) level was associated with increased risk of type 1 diabetes risk (MR OR = 1.66, 95% 1.36- 2.03; P = 7.1 x 10^-7). The risk of type 1 diabetes increased almost two-fold per genetically predicted SD increase in interleukin-27 Epstein-Barr Virus Induced 3 (IL27-EBI3) protein levels (MR OR=1.97, 95% CI = 1.48 – 2.62, P= 3.7 x10^-6). However, a SD increase in chymotrypsinogen B1 (CTRB1) was associated with decreased risk of type 1 diabetes (MR OR=0.84, 95% CI = 0.77 – 0.90, P= 6.1 x10^-6). <a></a></p> <p>Sensitivity analyses using MR methods testing for pleiotropy while including <i>trans</i>-pQTL showed similar results. While the MR-Egger suggested no pleotropic effect (<i>p</i>-value MR-Egger intercept = 0.31) there was evidence of pleiotropy in MR-PRESSO (<i>p</i>-value global test =0.006). </p> <p>CONCLUSIONS</p> <p>We identified three novel circulating protein biomarkers associated with type 1 diabetes risk using a MR approach. These biomarkers are promising targets for development of drugs and/or of screening tools for early prediction of type 1 diabetes. </p>

Relationship Between Serum Amino Acid Levels and Bone Mineral Density: A Mendelian Randomization Study

BackgroundThis study aimed to explore the association between serum amino acids (AAs) levels and bone mineral density (BMD).MethodsWe performed a two-sample Mendelian randomization (MR) analysis to analyze the associations between the levels of eight AAs and BMD values by using summary-level genome-wide association study (GWAS) data. We applied the MR Steiger filtering method and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test to check for and remove single nucleotide polymorphisms (SNPs) that were horizontally pleiotropic. The associations were estimated with the inverse variance weighted (IVW), MR-Egger, weighted median and MR Robust Adjusted Profile Score (MR.RAPS) methods.ResultsOur study found that genetically increased isoleucine (Ile) [IVW: effect = 0.1601, 95% confidence interval (CI) = 0.0604 ~ 0.2597, p = 0.0016] and valine (Val) levels (IVW: effect = 0.0953, 95% CI = 0.0251 ~ 0.1655, p = 0.0078) were positively associated with total body BMD (TB-BMD). The results also revealed that genetically increased tyrosine (Tyr) levels were negatively associated with TB-BMD (IVW: effect = -0.1091, 95% CI = -0.1863 ~ -0.0320, p = 0.0055).ConclusionsIn this study, associations between serum AA levels and BMD were established. These findings underscore the important role that serum AAs play in the development of osteoporosis and provide evidence that osteoporosis can be prevented and treated by the intake of certain AAs.

Global Information for Multidimensional Tests

New measures of test information, termed global information, quantify test information relative to the entire range of the trait being assessed. Estimating global information relative to a non-informative prior distribution results in a measure of how much information could be gained by administering the test to an unspecified examinee. Currently, such measures have been developed only for unidimensional tests. This study introduces measures of multidimensional global test information and validates them in simulated data. Then, the utility of global test information is tested in neuropsychological data collected as part of Rush University’s Memory and Aging Project. These measures allow for direct comparison of complex tests calibrated in different samples, facilitating test development and selection.