The role of body fat in multiple sclerosis susceptibility and severity: A Mendelian randomisation study

Objective: The objective of this study was to explore the potential causal associations of body mass index, height, weight, fat mass, fat percentage and non-fat mass in the whole body, arms, legs and trunk (henceforth, ‘anthropometric measures’) with multiple sclerosis (MS) risk and severity. We also investigated the potential for reverse causation between anthropometric measures and MS risk. Methods: We conducted a two-sample univariable, multivariable and bidirectional Mendelian randomisation (MR) analysis. Results: A range of features linked to obesity (body mass index, weight, fat mass and fat percentage) were risk factors for MS development and worsened the disease’s severity in MS patients. Interestingly, we were able to demonstrate that height and non-fat mass have no association with MS risk or MS severity. We demonstrated that the association between anthropometric measures and MS is not subject to bias from reverse causation. Conclusions: Our findings provide evidence from human genetics that a range of features linked to obesity is an important contributor to MS development and MS severity, but height and non-fat mass are not. Importantly, these findings also identify a potentially modifiable factor that may reduce the accumulation of further disability and ameliorate MS severity

Evaluation of Two Estrus Synchronization Protocols in Dairy Cattle at North Shoa Zone Ethiopia

This study was initiated to change the hesitation of the farmer on the effectiveness of estrus synchronization under their (Ethiopian small holder) livestock management system using two synchronization protocols. Non-pregnant animals with normal reproductive tract and that fulfilled the preconditions for estrus synchronization were considered for treatment & assigned into two synchronization protocols (single PGF2α injection; and double PGF2α injection). Among 94 (27 heifer and 67 cows) synchronized cows using one and two injections of PGF2α protocols 26 heifers and 63 cows (89/94.7%) were exhibited estrus by visual observation and rectal palpation the remaining 5 (5.3%) did not illustrate heat. The overall pregnancy was 59.6 % with overall birth 94.3 %. High pregnancy was obtained in the double injection of PGF2α treatment group (63.1 %) than animals treated with one shot protocol 55.8 % there were statistically significant difference between treatments (p<0.05). Higher pregnancy was obtained from cross breed animals than local breeds. More over most of the animals come to estrus greater than 96 hrs. There was also significant difference between technicians on detecting the CL and conception. The estrus response, conception rate, pregnancy rate and calving rate was higher in both protocols so producers or farmers can use either the two protocols to achieve remarkable result but tight follow-ups and more resources are need to be exploited at farmer level

Age-related telomere attrition in the human putamen

Age is a major risk factor for neurodegenerative diseases. Shortening of leucocyte telomeres with advancing age, arguably a measure of "biological" age, is a known phenomenon and epidemiologically correlated with age-related disease. The main mechanism of telomere shortening is cell division, rendering telomere length in post-mitotic cells presumably stable. Longitudinal measurement of human brain telomere length is not feasible, and cross-sectional cortical brain samples so far indicated no attrition with age. Hence, age-related changes in telomere length in the brain and the association between telomere length and neurodegenerative diseases remain unknown. Here, we demonstrate that mean telomere length in the putamen, a part of the basal ganglia, physiologically shortens with age, like leukocyte telomeres. This was achieved by using matched brain and leukocyte-rich spleen samples from 98 post-mortem healthy human donors. Using spleen telomeres as a reference, we further found that mean telomere length was brain region-specific, as telomeres in the putamen were significantly shorter than in the cerebellum. Expression analyses of genes involved in telomere length regulation and oxidative phosphorylation revealed that both region- and age-dependent expression pattern corresponded with region-dependent telomere length dynamics. Collectively, our results indicate that mean telomere length in the human putamen physiologically shortens with advancing age and that both local and temporal gene expression dynamics correlate with this, pointing at a potential mechanism for the selective, age-related vulnerability of the nigro-striatal network

Exploring the Role of Plasma Lipids and Statins Interventions on Multiple Sclerosis Risk and Severity: A Mendelian Randomization Study

BACKGROUND: There has been considerable interest in statins due to their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. METHOD: We employed two-sample Mendelian randomization (MR) to investigate: (1) the causal role of genetically mimic both cholesterol-dependent (via low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (via Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG)) levels and MS risk and severity; and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n =7,069). RESULTS: The results of MR using the inverse variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway, (OR 0.86 (95% CI 0.78 to 0.95), p-value 3.80E-03) is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. MR results also show that lifelong higher HDL-C (OR 1.14 (95% CI 1.04 to1.26), p-value 7.94E-03) increase MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. CONCLUSION: Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Since RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk via a cholesterol-independent pathway (i.e., RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk

Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

There is currently no disease-modifying treatment for Parkinson's disease, a common neurodegenerative disorder. Here, the authors use genetic variation associated with gene and protein expression to find putative drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.Peer reviewe

Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

There is currently no disease-modifying treatment for Parkinson's disease, a common neurodegenerative disorder. Here, the authors use genetic variation associated with gene and protein expression to find putative drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.Peer reviewe

Detection of exon skipping events in BRCA1 RNA using MLPA kit P002

A rapid and easy method to screen for aberrant cDNA would be a very useful diagnostic tool in genetics since a fraction of the DNA variants found affect RNA splicing. The currently used RT-PCR methods require new primer combinations to study each variant that might affect splicing. Since MLPA is routinely used to detect large genomic deletions and successfully detected exon skipping events in Duchenne muscular dystrophy in cDNA, we performed a pilot study to evaluate its value for BRCA1 cDNA. The effect of puromycin, DNase I and two different DNA cleaning protocols were tested in the RNA analysis of lymphocyte cultures. We used two samples from unrelated families with two different BRCA1 exon deletion events, two healthy unrelated controls and six samples from hereditary breast/ovarian cancer syndrome (HBOC) patients without BRCA1/2 mutations. Using RNA treated with DNase I and cleaned in a column system from puromycin-treated fractions, we were able to identify the two BRCA1 deletions. Additional HBOC patients did not show additional splice events. However, we were not able to get reproducible results. Therefore, the cDNA-MLPA technique using kit BRCA1 P002 is in our hands currently not reliable enough for routine RNA analysis and needs further optimization

Modelling production-consumption flows of goods in Europe: the trade model within Transtools3

The paper presents a new model for trade flows in Europe that is integrated with a logistics model for transport chain choice through Logsum variables. Logsums measures accessibility across an entire multi-modal logistical chain, and are calculated from a logistics model that has been estimated on disaggregated micro data and then used as an input variable in the trade model. Using Logsums in a trade model is new in applied large-scale freight models, where previous models have simply relied on the distance (e.g. crow-fly) between zones. This linkage of accessibility to the trade model makes it possible to evaluate how changes in policies on transport costs and changes in multi-modal networks will influence trade patterns. As an example the paper presents outcomes for a European-wide truck tolling scenario, which showcases to which extent trade is influenced by such a policy. The paper discusses how such a complex model can be estimated and considers the choice of mathematical formulation and the link between the trade model and logistics model. In the outcomes for the tolling scenario we decompose the total effects into effects from the trade model and effects from the logistics model

Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study.

BACKGROUND: Both positive and negative associations between higher body mass index (BMI) and Parkinson disease (PD) have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR)-the use of genetic instrumental variables (IVs) to explore causal effects-has not previously been used to test the effect of BMI on PD. METHODS AND FINDINGS: Two-sample MR was undertaken using genome-wide association (GWA) study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR) for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR-Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69-0.98). MR-Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654). However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights. CONCLUSIONS: In this large study using two-sample MR, we found that variants known to influence BMI had effects on PD in a manner consistent with higher BMI leading to lower risk of PD. The mechanism underlying this apparent protective effect warrants further study

The ventilation of buildings and other mitigating measures for COVID-19: a focus on wintertime.

The year 2020 has seen the emergence of a global pandemic as a result of the disease COVID-19. This report reviews knowledge of the transmission of COVID-19 indoors, examines the evidence for mitigating measures, and considers the implications for wintertime with a focus on ventilation.This work was undertaken as a contribution to the Rapid Assistance in Modelling the Pandemic (RAMP) initiative, coordinated by the Royal Society