The preclinical phase of autoimmune disorders is characterized by an initial asymptomatic phase of varying length followed by nonspecific signs and symptoms. A variety of autoimmune and inflammatory manifestations can be present and tend to increase in the last months to years before a clinical diagnosis can be made. The phenotype of an autoimmune disease depends on the involved organs, the underlying genetic susceptibility and pathophysiological processes. There are different as well as shared genetic or environmental risk factors and pathophysiological mechanisms between separate diseases. To shed more light on this, in this narrative review we compare the preclinical disease course of four important autoimmune diseases with distinct phenotypes: rheumatoid arthritis (RA), Systemic Lupus Erythematosus (SLE), multiple sclerosis (MS) and type 1 diabetes (T1D). In general, we observed some notable similarities such as a North-South gradient of decreasing prevalence, a female preponderance (except for T1D), major genetic risk factors at the HLA level, partly overlapping cytokine profiles and lifestyle risk factors such as obesity, smoking and stress. The latter risk factors are known to produce a state of chronic systemic low grade inflammation. A central characteristic of all four diseases is an on average lengthy prodromal phase with no or minor symptoms which can last many years, suggesting a gradually evolving interaction between the genetic profile and the environment. Part of the abnormalities may be present in unaffected family members, and autoimmune diseases can also cluster in families. In conclusion, a promising strategy for prevention of autoimmune diseases might be to address adverse life style factors by public health measures at the population level. Autoimmune disorders are diseases in which the immune system recognizes and reacts against self-antigens. Clinical onset is often preceded by low grade inflammation , diseaseIndividuals in the pre-clinical phase have an initial asymptomatic phase of varying length in which the immune system is activated and the autoimmune process is started. Oftentimes, this phase is followed by nonspecific signs and symptoms and it might take years for the disease to manifest itself. To shed more light on this matter, we here compare the preclinical disease course of a selection of four important autoimmune diseases: rheumatoid arthritis (RA), Systemic Lupus Erythematosus (SLE), multiple sclerosis (MS) and type 1 diabetes (T1D). Although these are clinically distinct diseases, involving different autoimmune reactions and target organs, in some cases they appear to share certain genetic and environmental risk factors as well as pathophysiological mechanisms , 6. Thesvia PubMed and Medline   , 14, 15.proteins , 17. Othectively , 18. RA ectively .in utero may contribute to the risk for RA , but many more experiencing frequent flares of disease activity and/or chronic symptoms. For many patients, the general feeling of illness, accompanied by fatigue, lassitude, and minor cognitive difficulties is the most burdensome feature of the disease.HLA-DRB1*1501 and HLA-DRB1*0301 are associated with a 2-to-3 fold increase risk of SLE (IRF8), IFIH1, Toll-like receptor 7 (TLR7), and Tyrosine Kinase 2 (TYK2) are also risk loci for the disease  antibody production . In the rd and 4th decades of life, and men have a later peak incidence compared to women  and anti-La antibodies (SS-B), which manifest at the same time. Anti-Ro antibodies are detectable in the serum approximately four years before SLE clinical manifestations. Subsequently, anti-dsDNA antibodies become manifest months before clinical diagnosis, followed by anti-Sm and anti-nuclear ribonucleoprotein (anti-RNP) antibodies, whose levels start increasing exponentially up to a year before diagnosis and are highest just before the disease is diagnosed , 84.SLE also has alterations in levels of pro-inflammatory cytokines long before the onset of clinical signs and symptoms, with increased type I and II interferon (IFN-I and IFN-II), IL-5, IL-6, IL-17, and TNF , 85.HLA-DRB1*1501 haplotype has been demonstrated to be the most significant genetic risk factor to develop MS (odds ratio approximately 3) ((IL2RA), IL7R, CLEC16A and CD226  with a presumed autoimmune pathogenesis. Several genetic, environmental and lifestyle risk factors are reported. A latitudinal gradient has been found, i.e. the farther away from the equator the frequency of MS increases. This latitudinal risk factor may reflect differences in UV radiation, sun exposure, vitamin D levels and epigenetic interactions. Migration from a higher to a lower latitude after puberty has an impact on disease risk: migrants retain its original risk , 86, 87.ately 3) . More thnd CD226 .Cigarette smoking contributes to the risk of MS, with a 50% higher risk in ever smokers compared to never smokers , 87. TwoIn general patients are identified when they first manifest signs and symptoms characteristic for this disease . Most paSerum neurofilament light chain (sNfl) is indicative of ongoing neuraxonal degeneration, and can be used as a biomarker for neuronal injury. MS patients usually have high levels of sNfl that decrease after treatment with disease modifying therapies, and MS risk positively correlates with higher sNfl levels in a time-dependent manner, starting several years before MS (median of 6 years) , 98. In MS can either manifest as episodes of inflammation with neurological symptoms followed by partial or total remission , or as a gradually progressive disease (PPMS). In time, RRMS may evolve into a progressive phase of the disease called secondary progressive MS (SPMS). Depending on the site of the lesion, patients may have different clinical pictures. Common presenting symptoms in RRMS are optic neuritis and ascending sensory symptoms, whereas PPMS in general presents with progressive motor impairment .In T1D autoimmunity targets the beta-cells of the pancreas eventually resulting in absolute insulin deficiency. Similarly to the diseases mentioned above, T1D incidence is also affected by the latitudinal gradient and migration, with increased disease risk when populations move from low-incidence to high-incidence countries , 101. HoIn contrast with the other diseases discussed here, there is no demonstrated association between smoking and T1D , which mDiet may also influence T1D risk, as there is an increased risk in overweight children . Cow’s mT1D present two peaks of incidence at 4-7 years old and – more commonly – 10-14 years of age , 105. T1Biomarkers of the T1D preclinical phase, and its progression towards clinical manifestation, are also the proinsulin to c-peptide (PI:C) ratio and reduced pancreatic volume. The first is indicative of beta cell stress, while the latter seems to correlate with reduced pancreatic islets and loss of exocrine volume. At-risk individuals, especially children younger than 10 years old, that progress to T1D have higher serum PI:C ratio than those who never progress to T1D. Moreover, FDR of T1D patients have reduced pancreatic volume compared to seronegative individuals, although it is still higher than patients with recent onset T1D , 109.High levels of CD4+ and CD8+ T cells with specificity for beta cell autoantigens are now found in the islets of asymptomatic individuals. This antigen recognition might be mediated by B cell antigen presentation to T cells , 110. AsThe symptomatic stage of T1D manifests as polyuria, polydipsia due to hyperglycemia, and eventually ketoacidosis caused by excessive lipolysis due to insulin deficiency and can only be treated with insulin replacement therapy .The four diseases included in this review can affect a wide range of organs and tissues, that may be the initial site of an attack by the immune system. In line, the resulting pathology is diverse and one could easily conclude that the diseases have little in common. However, when one looks beyond the clinical manifestations to the genetic, environmental and behavioral determinants, it appears that apart from the differences there are also some notable similarities , 87, 101The North-South gradient may point to genetic differences, but can also be partly due to different climatic influences or dietary habit differences between more Northern and more Southern regions. Likewise, the observed female preponderance may be related to reproductive hormonal factors or alternatively to X-linked genetic factors. For both explanations, the available data do not fully explain the predominance of females . The impWhen we thus suppose there may be a partly shared pathophysiology between the four diseases, one might expect this to become apparent in a clustering of diseases in the same individual. RA and SLE can indeed occur together, a situation called “rhupus”, however, this is quite uncommon . MS and On the level of antibodies, we see that RA patients might express ANA antibodies, while SLE and T1D patients can also express RF and/or ACPA . RelativIn this sections below, we look further into these overlapping aspects.RA, SLE, MS, and T1D all have a genetic component, with familial clustering and higher risk of disease in first degree relatives of patients (FDR) , 122. SeHLA-DRB1. HLA contributes to nearly 33% of RA risk , and Signal transducer and activator of promoter 4 (STAT4)  , 14. In STAT4 gene in the third intron is associated with both RA and SLE, with higher risk when this SNP is present in both alleles. STAT4 is involved in the signaling of cytokines, such as IFN-I, IL-12, and IL-23, which promote differentiation of effector T cells towards a Th17 phenotype. However, STAT4 has different roles in RA and SLE at least according to animal models: while in RA STAT4 deficiency in mice is protective, with inability of those mice to develop RA, in SLE STAT4-deficient mice have accelerated nephritis and higher mortality  in immune associated genes, such as T1D risk , 131–134T1D risk , 6. BothT1D risk , 135. InAlthough genetic factors play an important role in risk of autoimmunity, genetic predisposition is able to explain only up to 50% of the risk of developing RA and T1D, leaving half of the patients without any known genetic marker , 135. NuSmoking is one of the most prominent environmental risk factors, and has a role in RA, SLE, and MS , 77, 87.Occupational exposure seems also to be a risk factor for autoimmune diseases; silica and other inorganic dust exposure have been reported to increase the risk of RA and SLE , 140. HoAdditional lifestyle factors are exercise, alcohol consumption, diet and body mass index (BMI). Exercise and moderate alcohol consumption have been associated with decreased risk of RA and SLE , 141, whEither chronic stress or the presence or post-traumatic stress disorder (PTSD) have both been related to the subsequent occurrence of autoimmune diseases . In a stIt is important to consider that many of the associations mentioned above have a tendency to cluster within the population. Unhealthy diet, lack of physical activity, obesity, chronic stress, as well as environmental exposure, low socio-economic status and low income, all co-segregate, making it hard to identify if the causal association found by observational studies is caused by one specific factor or a combination of them.Vitamin D levels have been suggested to influence disease severity in both MS and T1D in a seasonal way, with higher relapses in MS and diagnostic rate in T1D linked to vitamin D status . The mecAnother factor that may play a role in disease risk are viral infections. In RA there is no consistent evidence of infections involved in the pathogenesis. Epstein-Barr (EBV) infection has been suggested to increase the risk of SLE , 155 andWhile the association between MS and EBV infection is strong, the role of infections inT1D pathogenesis is not yet well defined. The Diabetes Prediction and Prevention (DIPP) study demonstrated a correlation between first autoantibody appearance and enterovirus infection, and serological studies suggest a link between Coxsackie B virus, in particular CBV4 serotype, and T1D. Moreover, the Teddy study described a possible correlation between respiratory infections, with a common peak between 6 and 9 months of age, and increased risk of islet autoimmunity, which follow a similar trend , 157. InRA, SLE, MS, and T1D all have a latent phase that precedes formal clinical diagnosis . The most reproducible autoantibodies for diagnostic purposes are those reflecting renal involvement , 161.So far, in MS no specific autoantibody has been found, however, autoantibodies against several CNS cells have been reported in this disease , 163.As noted above, also persons at risk for T1D can develop several types of autoantibodies. There is a combination effect of multiple antibodies, with 70% risk of disease in children with multiple (three or four) circulating antibodies. Young children preferably develop IAA, while GAD autoantibodies are most commonly found in teenagers. However, the conversion from single to multiple antibodies can be slow , 164–166Nearly 60% of children with single autoantibodies will lose antibody production over time and convert to seronegative . This meOf note, FDR of RA, SLE, and T1D patients may have autoantibodies detectable in their serum in absence of any signs or symptoms of disease , 121.The cellular component of the immune system also has an active role in disease pathogenesis. In preclinical RA, ACPA+ individuals have decreased T regulatory (Treg) cell levels and a shift of CD4+ T cells towards pro-inflammatory subsets, in particular T helper (Th) 2 cells , 167. InThe B cell component is also altered in individuals at risk for RA, who have higher levels of IgA plasmablasts than the general population . The impSoluble factors have a role in disease pathogenesis, inducing immune activation, recruitment, and regulation of the immune response. They are also responsible for direct pathogenic manifestations and can be used in some cases as biomarkers of disease progression. Soluble factors involve a variety of molecules, such as cytokines, complement and markers of inflammation.de novo onset of SLE, the symptoms of which would improve after the treatment is stopped. Serum levels of IFN-I increase drastically one year before SLE onset, and circulating IFN-I is considered an hereditary risk factor for SLE effectiveness of preventive therapy in high risk individuals.All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 847551 (GF).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.Box 1All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The World Health Organization defines quality of life as “ an individuals’ perception oftheir position in life, in the context of the culture and value systems in which they live andin relation to their goals, expectations, standards, and concerns.” physicians, when dealingwith illness and exposing themselves to the risks of their profession, must act withoutcompromising their own health status in view of the function performed.To evaluate and correlate physicians’ quality of life, professional illness, andpresenteeism.This is an epidemiological, cross-sectional, descriptive study with an exploratoryquantitative approach. Overall, 309 physicians working in Juiz de Fora, state of Minas Gerais,Brazil were interviewed and answered a questionnaire with sociodemographic and healthinformation and the World Health Organization Quality of Life instrument-Abbreviated version(WHOQOL-BREF).Of physicians in the sample, 57.6% fell ill during their professional activities, 35% tooksickness absence, and 82.8% practiced presenteeism. The most prevalent diseases were thoseinvolving the respiratory system (29.5%), infectious or parasitic diseases (14.38%), and thoseinvolving the circulatory system (9.59%). WHOQOL-BREF scores were boas, and were influenced bysociodemographic characteristics such as sex, age, and time of professional experience. Malesex, professional experience greater than 10 years, and age above 39 years were associatedwith beter quality of life. Previous illness and presenteeism were negative factors.The participating physicians had a good quality of life in all domains. Sex, age, and timeof professional experience were relevant factors. The highest score was observed in thephysical health domain, followed by psychological domain, social relationships, andenvironment, in a descending order. Theycan only be measured by the quality of life they provide to people.” Regardless of thesociocultural context, each individual should feel psychologically well, in a good physicalcondition, socially integrated, and functionally competent.1 From this perspective, it is important that physicians, when dealingwith illness and exposing themselves to the risks inherent to professional practice, must actwithout compromising their own health status in view of the function performed.2The World Health Organization (WHO) defines quality of life as “an individuals’ perception oftheir position in life, in the context of the culture and value systems in which they live andin relation to their goals, expectations, standards, and concerns.”3 Updated to multicausality theory and developed interprofessionally,occupational health adopts the perspective that a set of risk factors is considered in theproduction of disease, being assessed from the perspective of medical clinical and byenvironmental and biological indicators of exposure and effect.4The discussions of the VIII Brazilian National Health Conference and of the I BrazilianNational Occupational Health Conference, in line with the Brazilian democratic transition andwith what was occurring in the Western world, provided a new decisive focus for the theme, withthe changes established in the new 1988 Federal Constitution.5Occupational risks are divided into five groups, according to their nature: physical risksinclude exposure to noise, extreme temperatures, and ionizing radiation; chemical risks arerepresented by gases, vapors, and various reagents; biological risks cover exposure tomicro-organisms, blood, and blood-derived products; ergonomic risks refer to inadequate posture,repetitiveness, work in shifs, and stressful situations; and risks of accident encompassinadequate arrangement of workplace, insuficient lighting, potential accidents with electricity,and probability of fre.6 The observedprevalence of presenteeism, i.e., atending work while sick, is 80 to 90% among medicalprofessionals, in comparison with 30 to 70% in other professions.7 Due to ergonomic issues of their activity, 59% of surgeons presentwith neck pain, observed in 20% of the general population.8 Dissatisfaction with work-life balance is also higher than that of populationcontrols, 40.2% vs. 23.2%, respectively.9 In a research conducted by the Medical Society of the State of New York withmore than 1,000 physicians, 57% of respondents had symptoms of burnout.10Different risk groups may be present in medical activity, in addition to the specific demandsrelated to the work of these professionals. The literature shows that, compared with otherprofessionals, physicians’ vacation time is nearly half shorter and their average weekly workinghours is 15 hours longer.11 Therefore, physicians’ perception about their own quality of lifecollaborates closely to investigate the interdependence between their extenuating professionalactivity and the several aspects of their life, even afecting their ability to provide qualitycare to patients who seek them.12 It is knownthat 74% of diagnostic errors are related to cognitive aspects of these professionals, dependingnot only on good training and level of knowledge, but also on good reasoning andinterpretation.12 These cognitive aspectsare compromised by burnout, which is a very common condition among professionals who sacrificetheir well-being in favor of profession activity and are subject to various occupationalrisks.6According to the WHO Declaration on Workers’ Health, there is a growing recognition about thelinkages between working conditions, health, and productivity.th, 2020, the WHO declaredCOVID-19 as a pandemic, thus ratifying and exacerbating the frequent physical, ergonomic, andpsychological risks of health care professionals. Increased workload, physical exhaustion,inadequate personal equipment, nosocomial transmission, and need of making ethically difficultdecisions on rationing of care may have dramatic effects on physical and mental well-being. Thishighlights the urgent need for beter interventions on health care providers’ physical and mentalhealth.13This research collected data up to the beginning of the coronavirus disease 2019 (COVID-19)pandemic, a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),which emerged in December 2019 in Wuhan, China. On March 11The present study aimed to assess physician’s quality of life and aspects that afect it, aswell as professional illness and presenteeism, in addition to correlating these factors withphysician’s quality of life.An epidemiological, cross-sectional, descriptive study with an exploratory quantitativeapproach was performed. It consisted of an original survey conducted with physicians in the cityof Juiz de Fora, state of Minas Gerais, Brazil. As a standardization criterion, the area ofstudy was delimited as the geographic area with the greatest concentration of doctor’s oficesand hospitals. Therefore, the study was conducted in the city’s downtown, because care provisionis centralized in this area, thus characterizing a plural and representative sample for thisstudy.14According to a survey performed by the Brazilian Federal Council of Medicine , Juiz de Fora had 3,191 physicians in 2018, working and living in themunicipality. Of these, 2,405 were registered as specialists.15 According to Levine et al.,15 when p and q values are unknown, the following equation should be used tocalculate the sample: 15 For estimates with no continuity correction, the sample wasestimated at 309 individuals.In a literature review, it was not possible to obtain an accurate and reliable prevalence ofillness in the medical population; therefore, to estimate the sample, the hypothetic prevalenceof illness leading to sick leave was set at least 20% per year.Inclusion criteria were being a physician working in Juiz de Fora and agreeing to participatein the research by signing the informed consent form (ICF). Incomplete questionnaires wereconsidered sample loss. Exclusion criteria consisted of physicians who were not practicing theirprofession.Information was obtained using a structured questionnaire containing 40 questions divided intotwo parts. The first part consisted of 14 questions developed by the researchers and thatenabled to characterize the sample with regard to sociodemographic aspects, alcohol consumption,and smoking, in addition to previous illnesses and absence from work activities. In the secondpart, quality of life was assessed using the World Health Organization Quality of Lifeinstrument-Abbreviated version (WHOQOL-BREF) questionnaire, which contained 26 questions, twogeneral questions on quality of life and the others related to the following domains: physicalhealth, psychological, social relationships, and environment. This instrument does not providean overall quality of life score, because it assumes the premise that quality of life is amultidimensional construct; thus, each domain is score independently. The final score istransformed into a 100-point scale, in which 0 equals the worst quality of life and 100, thebeter.Data collection was conducted from July 2019 to February 2020 by five duly trained studentsfrom the School of Medicine of Universidade Federal de Juiz de Fora, so that the questionnaireitems were applied and explained in a standardized way. Researchers’ training occurred in apilot study conducted with 20 volunteer physicians in order to identify problems in theunderstanding of instruments and to define approach and approximation criteria, thus ensuringthe quality of data collection. Researchers made previous contact with hospitals, clinics, andprofessionals via institutional email to schedule the interview. Volunteers were approached intheir workplaces and during their work hours. Afer in-person presentation, explanation onresearch goals, and clarifications on the confdentiality of information and data contained inthe forms, professionals were invited to answer printed questionnaires. Researchers did notinsist in case of refusal, even afer previous contact. Participants could withdraw from theresearch at any time if they so requested. Refusal rates were low, being estimated at one forevery five physicians approached, and were most related to lack of time availability from theprofessional. No participant withdrew or was excluded from the study.Data were double-typed and double-checked so as to mitigate possible inconsistencies ortypos.Data were described by measures of central trend and dispersion, as appropriate depending onlevel of measurement and symmetry of distribution for the variable of interest, i.e., means,standard deviations, medians, range, confdence intervals, and absolute (n) and relative (%)values.16Odds are frequently assessed using a measure of association or a measure of effect, whichtranslates the association between exposure and outcome. Teoretically, these indicators measurethe strength of the association between epidemiological variables. In this study, with respectto analysis of data with binary outcomes, the measure of association called odds ratio (OR) wasused, especially because this measure (estimator) express risk. OR assesses the relationshipbetween the odds of individuals exposed to have the condition of interest for the study,compared to that of non-exposed ones.The effects of the association between exposure and outcome of “quality of life, illness, andmedical presenteeism” (QLIMP) was measured using a multivariate logistic regression model toestimate OR. The multivariate model followed a forward-driven approach, i.e., a method to selectvariables grouped into dimensions considering the proximity of each dimension with a potentialmodifer of the QLIMP outcome. The final model considered all variable with effect >25% inmodules (increased or reduced odds), p-value < 0.20, and 95%CI that did not contain (1).2; in contrast to minimum ordinaryR2-squared, pseudo-R2 is based on a likelihood logarithm and did notrepresent the proportion of the explained variance, but rather the increased probability of themodel to contain explanatory variables in relation to a null hypothesis model, which onlycontains the constant.18 Secondly, by the finalquality of adjustment based on the Akaike’s information criteria (AIC).18 AIC admit the existence of a “true” model whichdescribes data that are unknown in the study and tries to choose between a group of modelsassessed, which minimizes the Kullback–Leibler divergence related to information that isnaturally lost when using an approximate model and not the “true” one, i.e., the one thatcontained the true parameter in the population.18 The model with beter adjustment was the one that presented lower AICvalues.The selection for the final multivariate model that beter explained the study outcome wasdefined by two criteria. Firstly, by pseudo-RThe level of significance was alpha ≤ 0.05 for a 95%CI. Analyses were conducted usingStata 15 sofware .The research was approved by the Research Ethics Commitee of Universidade Federal de Juiz deFora under opinion n. 2.642.932 and Certificate of Presentation for Ethical Appraisal(Certificado de Apresentação de Apreciação Ética)87463018.8.0000.5147. Reliability and privacy criteria were ensured to participants according toResolution n. 466/2012 of the Brazilian National Health Council, which addresses researchinvolving human beings.The study assessed 309 physicians of 38 specialties working in the city of Juiz de Fora, stateof Minas Gerais, Brazil. The sample consisted mainly of women, 54.4% (n = 168), and mean age was40.9 ± 12.8 years, ranging from 24 to 79 years, and median of 39 years. Mean time ofprofession for the group was 14.3 ± 12.8 years, ranging from 1 to 50 years, and withmedian of 10 years, which suggests that the group had a significant number of young physiciansat the initial stage of their career.More than a half of participants worked in the large area of clinical medicine , one fourth of them worked in surgical specialties ; 11.3% (n = 35), ingynecology and obstetrics; 9.4% (n = 29), in pediatrics; and only 1% (n = 3) worked in familypractice.19  reported falling ill during their professionalactivities, totaling 292 episodes of illness and 109 different diseases, which were dividedaccording to the 24 chapters of the International Classification of Diseases and Related HealthProblems, eleventh revision (ICD-11)19 .Among respondents, 82.8% (n = 256) reported having already practiced presenteeism. Absencefrom work was reported by 35% (n = 110); of these, 64.5% were absent once; 22.7%, twice; 5.5%,three times; 5.5%, from four to nine times; and 1.8%, 10 times or more. Mean number of daysabsent from work was 23 ± 83 days, ranging from 1 to 730 days. Among participants, 52.1%(n = 161) have sick leave insurance, and 80.9% (n = 250) do not feel represented by entitiesrepresenting their professional category with regard to quality and safety of their work.Consumption of alcohol was reported by 61.8% (n = 191); of these, 7.3% consumed alcoholicbeverages less than once a week; 50.3%, once a week; 24.6%, twice a week; 12%, three times aweek; and 5.8%, four times a week or more. Smoking was reported by 4.5% (n = 14), of which 57%smoked less than a packet of cigaretes per week.Answers to the WHOQOL-BREF questionnaire were divided into its respective domains andtransformed into scales ranging from 0 to 100 points .Subsequently, a multivariate regression analysis was performed associating sociodemographicaspects, alcohol consumption, smoking, previous illnesses, and sickness absence from work withdomain scores .2 value (22.09). This means that the variables in this model explain 22.09%of variance in the scores for the question “how would you rate your quality of life?”, and theindependent variables sex , time of profession ≥10 years , physical health , psychological domain , and environment were associated with greater odds of increased scoresin this question.Model 1 shows the best values in adjustment criteria, lower AIC value (326.4), and higherpseudo-R2 value (19.8), i.e., it explains nearly20% of variance in scores for the environment domain, exerting a great effect on the variablessex , age ≥ 39 years , and time of profession ≥ 10 years . Age had a protective effect; therefore, physician older than 39 years have nearly 79%lower odds of obtaining a poor score in the environment domain. In model 4, age also exerted aprotect effect and led to 53% lower odds of low scores in the psychological domain, but with nostatistical significance .Model 6 shows the second highest pseudo-R20 Our literaturereview found few texts that enabled to establish a scientific comparison, because there is ascarcity in investigations addressing overall quality of life among the medical population. Thedimension of Brazil and its remarkable regional characteristics hamper this comparison,considering the influence of culture on individual’s perception of quality of life.Studies addressing quality of life in Brazil are relatively recent and have increased everyyear. Most of them are not limited to a certain social or professional group, but rather topatients with some disease.13Previous studies about SARS and Ebola epidemics indicated that the onset of a sudden andimmediate life-threatening illness could lead to an extraordinary amounts of pressure on healthcare professionals, resulting in high rates of depression and anxiety, as well as post-traumaticstress disorder.13The COVID-19 pandemic that ravaged the country exacerbates a characteristic presented by ourresearch: although the risks of medical practice involving quality of life are evident, they arealso ofen hidden in the precarious working conditions in general, which are overcome byprofessionals with professional dedication and diligence. A systematic review and meta-analysisassessing 13 studies with more than 30 thousand physicians found a pooled prevalence of 23.2%for anxiety and 22.8% for depression.13 The numberof confirmed cases of COVID-19 among health care professionals in general, according to theBrazilian Ministry of Health, 2021, exceeded 442 thousand up to January 2nd,including 48,859 physicians,21 of which 551died up to December 2020, according to the CFM.22Physicians have experienced even more significant physical, ergonomic, and psychological risksduring the COVID-19 pandemic. Strenuous workload, inappropriate personal protective equipment,and the risk of nosocomial transmission, among others, have catastrophic effects on physicians’physical and mental state. Teir resilience may be even more compromised by isolation and loss ofsocial and risk or infections of friends and relatives, as well as drastic, ofen unsetlingchanges in the ways of working.Physicians interviewed in Juiz de Fora reported high quality of life, based on the assessmentmodel proposed at the time of data collection. This is a medium-sized city; thus, distances tocommute to work are shorter, trafic has known botlenecks that can be avoided, and levels ofcriminality are lower than those of the large Brazilian cities, factors that also contribute toa good quality of life for the general population. The quality of education and health servicesis high in all levels, compared to most Brazilian municipalities.23 Score for male respondents were higher than those offemales, which was also observed in the study conducted in Paraíba.23 Considering a 100-point scale, scores wererelatively good, ranging within the threshold of the third quartile, as well as the assessmentof individuals’ own quality of life and health.Quality of life indicators for participating physicians exhibited higher scores than thoseobserved in the four domains included in a study with 1,110 out of the 6,100 physiciansregistered at the Regional Medical Council of the state of Paraíba, Brazil.The worst score was observed in the environment domain, a result that is probably related tothe particularities of health organization in the city. Additionally, the interviewed physiciansreported great dissatisfaction in relation to the entities that represent their professionalcategory, in terms of occupational quality and safety, since 80.9% of workers did not feelrepresented by these entities.24According to the analysis of the data obtained, being a male, having more than 10 years ofprofessional experience, and obtaining a high score in the physical health and psychologicaldomains led to greater odds of individuals rating their own professional quality of life as goodand of having greater satisfaction with their own health. In an American study, physicians whohad already completed residency showed higher rates in the following domains: physical health,psychological, and environment.25whereas many women also have to balance their professional, maternal, and maritalroles.6Good scores in the psychological domain are related to male sex, previous illness, no historyof presenteeism, and time of profession of 10 years or more. These numbers indicate the positiveinfluence of greater maturity for a beter psychological well-being. With regard to disparitybetween sexes in this domain, it may be related to the fact that women are more concerned abouttime for their relationships than men,26 AEuropean study observed that female physicians were more likely to be dissatisfed with theirsafety and living places than their male counterparts, with a relative risk of 2.51,27 a situation corroborated by our study.The environment domain had the lowest mean and the lowest minimum score, being positivelyinfluenced by male sex and time of profession of 10 year or more. This is an extremely relevantaspect, because 84% of recently graduated physicians consider working conditions as relevant,and 45.7% value safer environments.25 This scenario is corroborated byour study, since the social relationships domain was more positive in the male sex.An American systematic review pointed that men physicians had higher scores in the socialrelationships domain than women physicians, being more satisfed with friends, family,colleagues, and bosses, as well as with career-advancement opportunities, recognition, andsalary.23Some factors inherent to the female universe, such as pregnancy, delivery, breastfeeding, andinvolvement in children’s education, in addition to the medical work itself, may be associatedwith lower scores in the following domains: psychological, physical health and environmentdomains, since women experience double burden of work in their personal and professional life,whereas some factors, such as leisure and availability, are less present in the life of femaleprofessionals.In relation to illness during work activities, most participants reported that they hadalready fell ill (57.6%), whereas 35.6% reported taking a sick absence from work, an absencethat lasted for 23 days, on average, and was repeated for three times or more among 12.8% ofphysicians. These numbers would be even greater if there was no trivialization of less severeconditions in the group of relatively young professionals and if presenteeism was not so commonamong physicians. This fact was corroborated in our research, since 82.8% of respondents statedhaving atended work while feeling sick, although a smaller portion had reported falling illduring medical practice.28 In New Zealand, 88% of the 1,806physicians participating in a study reported that they had already atended work while feelingsick to maintain their usual standards of performance.29 Among 107 Israeli physicians, only 17.8% said that they did not come to workill,30 a percentage similar to the 17.2% ofparticipants who reported doing so in our research.Presenteeism is a phenomenon observed in several countries, showing various rates and causes.In National Health Service (NHS), the United Kingdom’s health system, sickness absence ratesamong physicians were less than a third of rates across the system as a whole, and they wereabsent because of sickness leave on only 1.3% of the days they were scheduled to work, incomparison to an average sickness absence rate of 4.5% for nurses and 5.5% for ambulanceworkers.31 However, this atitude may be motivated by inability to remainfinancially stable during sickness absence,31a situation that could apply to the respondents of this study, since slightly more than a halfof participants (52.1%) are covered by labor insurance services.In addition to organizational, cultural and social components that motivate presenteeism,there are others whose correlation is more evident, such as appreciation and awards to longerworking hours and to high workload, inability of others to take over duties, negative sanctionsfrom colleagues or management, and feelings of moral obligation.28 Although our sample had a different nosologic profile, it was found that thepercentage of mental disorders is close to that of the British study, accounting for 6.17% ofdiseases,28 whereas diseases of themusculoskeletal disorders accounted for 3.76%. This similarity in the percentage of mentaldisorders show that, despite ethnical, cultural, and epidemiological diferences, physicians fromJuiz de Fora have a burden of stressors similar to that of physicians from the United Kingdom.These stressors associated with the profession may be related to medical practice itself, suchas few hours of sleep and fear of medical error, or related to individual’s personality inrelation to medicine, such as patients’ idealization of physicians, constant and intense contactwith pain, death, and sufering, working with emotional and physical intimacy, and relationshipwith difficult patients.6In our study, the most prevalent diseases during medical practice were those involving therespiratory system (29.50%), infectious or parasitic diseases (14.38%), and those involving thecirculatory system (9.59%). These findings are somewhat different from the causes of sicknessabsence among NHS physicians, with a higher prevalence of musculoskeletal problems, present in18.1% of the cases, and stress and depression in 7.3%, whereas no evidence of infectious orparasitic diseases was observed in this group.32with 57% displaying a worrying level of burnout.33 However, our study found that only 2.4% of participants sufered from diseasesrelated to factors influencing health status or contact with health services, including burnout.This diference is possibly explained by the fact that we did assess symptoms of disease itself;instead, we collected a general report from professionals about conditions that had already beendiagnosed, which may suggest that this disease is underdiagnosed among our respondents.The professional activity of Brazilian physicians is characterized by extenuating workingshifs, great variety of atributions, low payment, and occupational burnout, a consensual viewfor more than a half of these professionals,34 which may evidence a possibleneglect of this professional category. Furthermore, long working hours and the typical featuresof physicians’ personality6 may contribute tothe development of depression and anxiety, with need for psychological support. Our study foundthat 10.1% of the physicians who had already fell sick during their professional activitiespresent or had already presented some mental or behavioral disorder, which accounts for 6.17% ofdiseases, including depression, anxiety, and panic disorder, diseases that are closely relatedto suicide.Suicidal rates are a serious issue among physicians, being higher than those of the generalpopulation,35 Our study found that 61.8% ofprofessionals drank alcohol, and 11% drank it three times a week or more. However, it is worthconsidering that there is no safe limit for the consumption of alcohol, according to theWHO.36 High consumption of alcohol isassociated with 60 different conditions, such as cancer and increased blood pressure, usuallyhaving a high correlation with the ingested amount.36 This habit is ofen acquired during early adulthood, during the trainingperiod of these professionals, when intense course load, competitiveness among colleagues, sleepdeprivation, fear of making a mistake, and others stressors are compensated for by the use ofillicit and licit drugs, such as alcohol.37 Ina medical school in the state of Minas Gerais, Brazil, it was observed that 83.5% of studentsconsumed alcohol, of which 39.6% could be classified as heavy users, and 2.8% as being in asituation of alcohol dependence syndrome.37With regard to alcohol consumption, a German study reported that 82.5% of physicians consumedalcohol at least once a week, and 50.1% reported higher ingestions than the recommended dailyallowance by the German Nutrition Society – up to 20 grams/day for men and 10 grams/day forwomen.38 isstill significant, especially considering the level of physicians’ awareness about the risksassociated with this habit.As for smoking, it was reported by only 4.5% of the physicians interviewed, and 8 out of the14 smokers smoked sporadically, consuming less than a packet of cigaretes a week. Thispercentage of smokers in the population interviewed, despite being lower than that observed inthe general Brazilian population (14.7%),26 susceptible to growing rates of burnout and depression.10A weakness of this study is not considering the prevalence of use of anxiolytic agents,antidepressants, analgesics, and medications used to improve sleep and psychosomatic symptoms, atopic that may be investigated in future studies, especially because physicians are aprofessional category with a very specific profile,39 Therefore, new research is proposed afer the pandemic in order to assesspossible changes from the perspective of this group of professionals in Juiz de Fora.Another aspect that may represent a fall short of expectations, but provide subsidies forfuture studies, was the fact that we collected data up to the beginning of the COVID-19pandemic. According to the Juiz de Fora City Hall, more than 820 deaths and 20 thousand caseswere identified in the city up to March 2021.The participating physicians in the had a good quality of life in all domains, which wasinfluenced by sociodemographic characteristics such as sex, age, and time of professionalexperience. The highest score was observed in the physical health domain, followed bypsychological, social relationships, and environment domains, in a descending order.Results indicate that male sex, professional experience greater than 10 years, and age above39 years are factors associated with beter quality. Conversely, previous illness and practice ofpresenteeism were associated with lower scores.Most respondents reported having already fell ill, and a smaller portion reported takingsickness absence, whereas the levels of presenteeism were remarkably high, probably motivated byappreciation and awards to longer working hours and by the inability to remaining financiallystable during sickness absence, considering that slightly more than a half of participants arecovered by a labor insurance.The most prevalent diseases during physician’s profession were those related to therespiratory system, infectious or parasitic diseases, and those related to the circulatorysystem, with a relevant number of mental and behavioral diseases.This study is expected to contribute with the assessment of quality of life, illness, andfactors related to this process, improving understanding about the implications of illness andpresenteeism on physicians’ quality of life.


IntroductionSignificant advancements in human immunodeficiency virus (HIV) treatment have led to an increasing life expectancy among patients living with HIV (PLWH). Given this rise in life expectancy, as well as the ability to lead a more active lifestyle, the rate of total joint arthroplasty (TJA) in this population is increasing. Unfortunately, the current medical literature surrounding the safety and efficacy of TJA in this patient population is indeterminant. Therefore, the purpose of this study was to determine if optimization of PLWH prior to TJA would result in any changes in the incidence of postoperative complications and hospital length of stay (LOS) when compared to historically reported data. Materials and methods2, hemoglobin >12 g/dL, no tobacco use within 30 days of surgery, albumin >3.5 g/dL. Independent-sample t-tests and Pearson's chi-square tests were used to evaluate the continuous and categorical variables, respectively.A retrospective study was performed of all PLWH 18 years and older who underwent either a primary total knee arthroplasty (TKA) or total hip arthroplasty (THA) between 2009 and 2019 at our academic institution. Medical records were reviewed for each patient to assess demographics, comorbidities, preoperative laboratory studies, operative details, length of hospital stay, complications, and follow-up time. Patients were optimized using our institution's current optimization guidelines: body mass index (BMI) less than 40 kg/mResultsThis study included 47 TJA in PLWH, including 14 TKA and 33 THA. Out of the 47 patients, 13 (27.7%) were fully optimized for all four variables: BMI, hemoglobin, non-smoking status, and albumin. There was no significant difference between the group of PLWH that was completely optimized and the group that was not in any patient characteristics, preoperative labs, intraoperative variables, or postoperative variables, including length of hospital stay and complications. A larger proportion of patients not completely optimized was found to be active smokers (p=0.0003). All complications occurred in cases in which the patients were not fully optimized. Subgroup analysis of PLWH, who were completely optimized, showed an average LOS of 4.3+/-1.5 days following TKA and 2.9+/-1.1 days following THA. Subgroup analysis of PLWH not completely optimized showed that each case was optimized for at least one variable and that those optimized for albumin had the largest (12.2%) number of complications.ConclusionPLWH can achieve a low rate of complications and LOS similar to that of the general population if medically and nutritionally optimized. Additional research is necessary to reveal well-defined parameters for achieving a higher rate of optimization prior to surgery in this important patient population. Despite concentrated efforts to address this severe public health issue, the human immunodeficiency virus (HIV) continues to be a major global health tragedy. While many countries have started to witness a decrease in the incidence of HIV, the United States has been experiencing a rise in new cases since 2010, with a current prevalence of approximately 0.2% of the entire United States population . As osteAdvancements in HIV medication and surgical devices and techniques have allowed TJA to become safer for PLWH; however, the literature surrounding the efficacy of TJA in this patient population is uncertain. Several small retrospective studies show high rates of postoperative complications in PLWH following TJA, especially infection, as well as a longer length of hospital stay (LOS) -9. HowevIn order to develop an evidence-based, standardized, preoperative optimization protocol to be used prior to total hip arthroplasty (THA) or total knee arthroplasty (TKA) with the objective of improving surgical outcomes for patients, Johns et al. performed a review of the literature . They foThe purpose of this study was to determine whether medical and nutritional optimization of PLWH prior to TJA will result in a rate of postoperative complications and LOS similar to that of the general population. We hypothesize that PLWH who are optimized accordingly prior to TJA will have comparable rates of complications and a similar LOS to the general population.This study was approved by the university Institutional Review Board. A retrospective study was performed of all PLWH 18 years and older who underwent either a primary TKA or THA between 2009 and 2019 at our academic institution. All relevant cases were identified by using Current Procedural Terminology (CPT) and International Classification of Diseases (ICD-10) codes for primary TKA and THA, and HIV, respectively.Medical records were reviewed for each patient to assess demographics, comorbidities, preoperative laboratory studies, operative details, length of hospital stay, complications, and follow-up time. Demographics and comorbidities include age, sex, body mass index (BMI), coronary artery disease (CAD), congestive heart failure (CHF), pulmonary disease (defined as either obstructive sleep apnea or chronic obstructive pulmonary disease), diabetes, smoking status, hypertension, inflammatory state, anemia, drug use, and hepatitis. Preoperative laboratory studies include levels of hemoglobin A1c, albumin, transferrin, hemoglobin, creatinine, CD4 T cell count, and HIV viral load. Operative details include estimated blood loss and operative time. Lastly, complications include infection, fracture, neurologic injury, wound healing, acute kidney injury (AKI), and dislocation. Patients were excluded from our study if they were prisoners, had coagulopathy, or if they had a postoperative follow-up of fewer than 90 days.2, hemoglobin >12 g/dL, non-smoking status or no tobacco use within 30 days of surgery, albumin >3.5 g/dL. Albumin was used as a surrogate for nutritional status, while the other variables were used to approximate medical status. These parameters are very similar to those described by Johns et al., with the only difference being that they also recommend a measure of glucose control (hemoglobin A1c <7.0-7.5%) and negative methicillin-resistant Staphylococcus aureus colonization status [Patients were optimized using our institution's current optimization guidelines: BMI less than 40 kg/mn status . PatientIndependent-sample t-tests and Pearson's chi-square tests were used to evaluate the continuous and categorical variables, respectively. An alpha of 0.05 was used for statistical significance. All analyses were completed using JMP Software .2, and had a range of comorbidities, the most common of which were hypertension (46.8%), diabetes (21.3%), and hepatitis (17.0%). There were a total of seven complications (14.9%) in four patients. One patient who underwent a complex TKA  developed a peroneal nerve palsy. Postoperatively, the patient fell and sustained partial wound dehiscence and patella fracture that required revision surgery which was subsequently complicated by infection. The overall mean LOS was 87.90+/-40.16 hours or 3.7+/-1.7 days.This study included 47 total TJA in PLWH, including 14 TKA and 33 THA. All patients were on HAART therapy at all time points. The patients had an overall mean age of 53.06 years with a mean follow-up of 32 months. Patients tended to be overweight, with a mean BMI of 28.5 +/- 6.5 kg/mThirteen out of the 47 cases (27.7%) were fully optimized for all four variables: BMI, hemoglobin, smoking status, and albumin. Between the group of PLWH that was completely optimized and the group that was not, there was no significant difference in any of the patient characteristics, preoperative labs, intraoperative variables, or postoperative variables, including length of hospital stay and complications Table . A largeSubgroup analysis of PLWH, who were completely optimized, showed no complications following either TKA or THA. Furthermore, this group had an overall average LOS of 85.92+/-34.02 hours or approximately 3.6+/-1.4 days. Upon further splitting by surgery type, PLWH had an average LOS of 104.37+/-35.48 hours, or 4.3+/-1.5 days, following TKA and 70.55+/-26.16 hours, or 2.9+/-1.1 days, following THA.Subgroup analysis of PLWH not completely optimized showed that each case was optimized for at least one variable. Furthermore, the proportion of patients in this subgroup that developed at least one complication varied Figure . Most ofAdvancement in antiretroviral therapy, along with other therapeutic interventions, has allowed PLWH to live longer, more active lifestyles, with many living past the age of sixty . As thisIn our study, we had 47 cases that were each optimized for at least one of the criteria described by Johns et al., specifically, BMI, hemoglobin, smoking status, and albumin, which served as a surrogate for nutritional optimization . Overall3 are at a similar risk of PJI as the average population, especially after medical and nutritional optimization [In the subgroup of patients who were completely optimized, there were no complications, including infection. The rate of complications following TKA or THA is generally low, with fewer than one percent of patients typically experiencing deep vein thrombosis or pulmonary embolism, urinary tract infection, myocardial infarction, renal failure, pneumonia, and mortality . Furthermization .The complications in this study were solely found in the cohort of PLWH who were not completely medically optimized; however, there was no significant difference in complications and LOS between the two cohorts. Although this is likely due to the small sample sizes, it is also possible that the absence of a significant difference is due to the fact that these patients were still partially optimized. When looking at the subgroup of PLWH, who were partially optimized in our study, cases with nutritional/albumin optimization developed the largest rate of complications (12.2%). However, Nelson et al. and Bohl et al. have previously found that hypoalbuminemia independently predicts complications after TJA ,20. ThisOur study had limitations, mainly the small sample size and incompleteness of the data. Due to this, we were unable to follow the complete recommendations for optimization put forth by Johns et al. . It is rIn conclusion, our study suggests that PLWH can achieve a low rate of complications and a LOS similar to that of the general population if medically and nutritionally optimized. Optimization for all four guidelines can be difficult in this patient population, and further research may reveal more precise parameters and elucidate the role of achieving a higher rate of optimization prior to surgery.


Lactobacillus reuteri (L. reuteri), to pregnant mother animals. In this study, we tested a cohort of Western diet-fed descendant mice exhibiting a high frequency of behavioral features and lower FMRP protein expression similar to what is observed in FXS in humans . By investigating 17,735 CpG sites spanning the whole mouse genome, we characterized the epigenetic profile in two cohorts of mice descended from mothers treated and non-treated with L. reuteri to determine the effect of prenatal probiotic exposure on the prevention of FXS-like symptoms. We found several genes involved in different neurological pathways being differentially methylated (p ≤ 0.05) between the cohorts. Among the key functions, synaptogenesis, neurogenesis, synaptic modulation, synaptic transmission, reelin signaling pathway, promotion of specification and maturation of neurons, and long-term potentiation were observed. The results of this study are relevant as they could lead to a better understanding of the pathways involved in these disorders, to novel therapeutics approaches, and to the identification of potential biomarkers for early detection of these conditions. Environmental factors such as diet, gut microbiota, and infections have proven to have a significant role in epigenetic modifications. It is known that epigenetic modifications may cause behavioral and neuronal changes observed in neurodevelopmental disabilities, including fragile X syndrome (FXS) and autism (ASD). Probiotics are live microorganisms that provide health benefits when consumed, and in some cases are shown to decrease the chance of developing neurological disorders. Here, we examined the epigenetic outcomes in offspring mice after feeding of a probiotic organism,  Several neurodevelopmental disabilities such as ASD cannot be well-characterized by the one-disease one-gene school. Their complex nature is attributed to the interplay between genetic, epigenetic alterations, neuroinflammation, and the innate immune system, that are associated with factors such as alteration in the gut microbiota and other environmental factors . In the Lactobacillus reuteri (L. reuteri) is a well-studied probiotic bacterium that can colonize an array of mammals. In humans, it is found in different organs, including the gastrointestinal tract, urinary tract, skin, and in breast milk [ast milk . It has ast milk . L. reuteri in mice significantly reduced the pro-inflammatory cytokine response, specifically the percentage of Th17 cells and IL-17 levels [Oral administration of 7 levels . Dysbiosis, which is the imbalanced gut microbiome with an increase in the population of gut bacteria with pathogenic traits, is frequently observed in children with neurodevelopmental disabilities ,10. SeveFMR1) gene. The transcriptional silencing and the absence or reduced expression of the encoded gene product, FMRP [FMR1, specifically by DNA methylation and histone modifications resulting in loss of FMRP, has genome-wide consequences because of the role of FMRP in regulating the expression of several non-coding RNAs [Fragile X syndrome (FXS), a model of epigenetic dysregulation, is the most common monogenic cause of ASD, with ~60% of FXS individuals presenting autism spectrum disorder ,16. FXS ct, FMRP , is whating RNAs . As a reL. reuteri and those whose mothers did not. This study aimed to determine whether there is any potential interaction between the L. reuteri intake and changes in the methylomic profiles of one or both groups and if maternal induced diet correlated with the observed phenotype. The focus was on the pathways involved in neurogenesis and synaptogenesis, in addition to inflammation. Here, we report our findings from a study that characterized the global DNA methylation profile of biological samples derived from two groups of mice, those whose mothers had a prenatal intake of The results of this study are relevant as they could lead to a better understanding of the pathways involved in neurodevelopmental disabilities, independently coming from some of the already identified risk genes, to novel therapeutics approaches, and to the identification of potential biomarkers for early detection of these conditions. L. reuteri, reported here as Group A, and 8 were born to mothers who did not prenatally take L. reuteri, and therefore received regular untreated water, reported as Group B. Mother’s drinking water was the only difference between the two groups. A cohort of 16 outbred CD1 Swiss mice, six months of age and of approximately the same weight, were used in this study. They were housed and handled in the Association for Assessment and Accreditation of Laboratory Animal Care-accredited facilities with diets, experimental methods, and housing as approved by the MIT Institutional Animal Care and Use Committee. Out of 16 mice, 8 were born from descendants of mothers which consumed a Westernized diet ; specifiHalf brains derived from the 16 mice were snap frozen and then pulverized and divided into aliquots. Genomic DNA (gDNA) samples were extracted from the brain tissue by standard procedure  followed by quantification via a Qubit fluorometer . Five hundred ng of genomic DNA was bisulfite-treated using the EZ DNA methylation kit . Although Infinium Mouse Methylation BeadChips have been developed recently to measure the methylation profile of mice, there was no mature mouse methylation array when this study started, and thus, the study was carried out using the Illumina Human Infinium Methylation BeadChips. Bisulfite-converted DNA was hybridized with the Illumina Human Infinium MethylationEPIC BeadChip Kit  and then scanned with the Illumina iScan System  using the manufacturer’s standard protocol. Samples from the two groups were randomly loaded on the arrays. The Infinium MethylationEPIC BeadChip Kit included >850,000 individual CpG sites genome-wide at single-nucleotide resolution. As the Infinium MethylationEPIC array was not specifically designed for the mouse genome, many primers for each probe in the array do not target or specifically align within the mouse genome, so their location cannot be identified in the mouse genome with certainty. Hence, 22,569 out of the 850,000 probes that were identified in previous studies ,21 to hap-value greater than 0.01 in more than 5% of total samples (≥2). DNA methylation data were pre-processed and quantile-normalized with R package ‘minfi’  . Probes The Limma package was used to compare the methylation difference of CpGs that passed the quality control described above between the two groups. M value was used in statistical analysis instead of β value. M value is the ratio of the methylated to the unmethylated intensity and has a statistical advantage over the β value .p-value of the CpG site was used as that of the gene. The p-values of genes with multiple CpG sites in the gene were calculated by combining the p-values of all CpG sites in the gene, using Fisher’s method [Before the pathway analysis, the significance of each gene was determined. In the case of genes with one CpG site, the s method . R package ‘fgsea’ was used to carry out gene set enrichment analyses on gene sets based on Gene Ontology and metabolic pathways . In GeneDifferent proteins that are encoded by the genes involved in different brain functions based on the conducted pathway analysis were inserted into the String database to see the possible protein–protein interactions between them . A set on = 8) and Group B of untreated mice (n = 8) were homogenized with a tip-sonicator (Q-Sonica) in homogenization buffer containing 20 mM of HEPES buffer , 0.25 M of sucrose , and 1X protease inhibitor cocktail . Homogenates were centrifuged at 200,000× g rpm for 45 min at 4 °C and cytoplasmic fractions (supernatant) were collected and further quantified using the Bradford assay . Ten µg of protein were loaded on 4–12% Bis-Tris gels  and run at 100 V for 60 min and then 130 V for 60 min. Resolved proteins were then transferred onto nitrocellulose membranes using the Trans-Blot Turbo transfer system  at 25 V, 1.0 A, for 30 min. Membranes were stained with Ponceau to test for transfer efficiency, blocked with 3% milk for 1 h at room temperature, followed by incubation with 1:500 diluted Agap3 primary antibodies , 1:2000 diluted Shank3 primary antibodies , and 2.7:1000 diluted Dlg2 primary antibodies , respectively, overnight at 4 °C. Membranes were then washed in 1X-TBS and incubated with HRP-linked secondary antibody diluted 1:10,000  for Agap3, and HRP-linked secondary antibody diluted 1:2000  for Shank3 and Dlg2, for 1 h at room temperature. Bands were then visualized using a Chemiluminescent substrate, Super Signal West Dura . Densitometry analysis of bands for relative protein quantification was performed using the α Innotech Gel Imaging System .Lyophilized brain tissues from Group A of treated mice . Among the key functions, synaptogenesis, neurogenesis, synaptic modulation, synaptic transmission, reelin signaling pathway, promotion of specification and maturation of neurons, and long-term potentiation were observed. Furthermore, additional genes implicated in schizophrenia, intellectual disabilities, social deficits, repetitive behaviors, deafness, pituitary adenomas, and dysmorphic facies were also identified , embryonic placenta development (p = 0.009), and the positive regulation of inflammatory response (p = 0.015). A list of GO pathways that were found to be of significance and the corresponding genes involved are listed in p = 0.004), positive regulation of neuron apoptotic process (p = 0.01), negative regulation of neuron projection development , cerebral cortex neuron differentiation (p = 0.04), and neuromuscular junction development (p = 0.05)  .Several proteins that were identified through the pathway enrichment analysis to be involved in different brain functions were found to interact together. Some of those proteins were found to interact with several others, such as LIM homeobox transcription factor 1-β (LMX1B) which interacts with Homeobox protein OTX2 (OTX2), Sonic hedgehog protein (SHH), Homeobox protein MSX-1 (MSX1), and Homeobox protein engrailed-1 (EN1). Another protein that was found to interact with other different proteins involved in different functions in the brain is Fibroblast growth factor receptor 2 (FGFR2), which interacts with MSX1, SHH, Wingless-type MMTV integration site family, member 1 (WNT1), and Fibroblast growth factor receptor 1 (FGFR1) .n = 8) and in those without any treatment  revealed a significant difference in expression levels of DLG2 between both groups (p = 0.026), while the difference in AGAP3 and SHANK3 expression levels did not reach significance  are key to the induction of ASD by MIA ,59,60 an reuteri ,63, whil reuteri .L. reuteri in utero and those that were exposed to placebo. A total of 23 genes known to have a role in neurological function  receptors and K channels, mediating their clustering on the postsynaptic membrane, and they are differentially expressed in plasmacytoid dendritic cells (pDCs), potentially having different functions in the neuronal postsynaptic membrane [behavior . In neurmembrane . Furthermembrane . Thus, fSHANK3, highly expressed in both the peripheral and the central nervous system, is a scaffolding protein, which plays a key role in synaptic development and function. Impaired gene expression, mutations, methylation, and alternative splicing of SHANK3 have been reported in ASD . MoreoveCenG1A, Drosophila’s ortholog of PIKE, rescued excessive PI3K signaling and mushroom body defects [CenG1A was hypermethylated, its protein levels were higher in the FXS-like group compared to the control group. This might be another factor contributing to the development of FXS-like symptoms in that group, especially since it was shown in the above study that the increased expression of PIKE, which is encoded by CenG1A, mediates deficits in synaptic plasticity and behavior in Fragile X syndrome [Centaurin-gamma3, or AGAP3, is an essential signaling component of the NMDA receptor complex that links NMDA receptor activation to AMPA receptor trafficking . Further defects . In thissyndrome .Nbea is implicated in developmental diseases with early generalized epilepsy phenotypes [Gart improves the IQ of patients with Down syndrome [Agap1 is associated with neurodevelopmental disorders through interference with the cellular structure and internal functioning of neurons and through interactions with other genes, particularly the Dtnbp1 gene [Agap1, one potential impact of L. reuteri that can be inferred from the presented mouse experiment is that it reduced the methylation of Agap1 in mice that received the probiotic in utero, making the mice more neurotypical. In addition, hypermethylation of Agpat1, as well as its loss-of-function mutations, have been found to correlate with metabolic and reproductive disorders, seizures, and abnormal hippocampal brain development [Fbxo11 was shown to be involved in several neurological disorders. Damage to this gene correlates with intellectual disabilities, autism spectrum disorder, ADHD, and anxiety [On the other hand, some genes were not associated with ASD nor FXS but had significant roles in brain functions. For example, enotypes . Overexpsyndrome . Hypermebp1 gene . Consideelopment . Fbxo11  anxiety .Thus, these findings may help to explain why these different proteins interact together and might collectively contribute to the observed FXS-like symptoms in the cohort of mice included in this study. L. reuteri might be transferred from mothers to pups, which could halt alteration in the expression of the genes discussed, hence preventing the development of FXS-like symptoms in the offspring. In our studies (see the companion manuscript in this same issue), C-section rederivation with cross-fostering was used to eliminate the possibility of mother-to-infant transfer of microbiota. It is believed that administration of Fmr1 CGG expansion, and because a link between maternal gut dysbiosis and the development of FXS has never been reported. Our findings are of importance as the observed Fragile X-like syndrome (FXLS), in mice, is based on the maternal microbiome, rather than the presence of the Thus, the gut microbiome might contribute to the development of behavioral and physical features associated with FXS, although the mechanisms by which altered intestinal bacteria may affect brain development and function are not currently known.


The impact of body mass index on incidence of herpes zoster is unclear. This study investigated whether body mass index was associated with a history of herpes zoster and incidence during a 3-year follow-up, using data from a prospective cohort study in Japan.2) was classified into three categories . To evaluate the risk of herpes zoster, we used a logistic regression model for prevalence and a Cox proportional hazard regression model for incidence.In total, 12,311 individuals were included in the cross-sectional analysis at baseline, of whom 1,818 with a history of herpes zoster were excluded from the incidence analysis, leaving 10,493 individuals. Body mass index  in all participants, and 0.57  in women, with no significant difference for men.Being overweight was associated with a lower incidence of herpes zoster than being normal weight in older Japanese women. Reactivation of latent varicella-zoster virus dominant in dorsal root ganglia occurs after its primary infection.4 United States,5,6 Canada,7 and Japan.8 However, most of the studies were cross-sectional, except for one Japanese cohort study.8 Risk factors for HZ have been reported to be age, sex, ethnicity, genetic susceptibility, cell-mediated immune disorders, mechanical trauma, and psychological stress.6,9 Physicians and primary school teachers, who had repeatedly contact with varicella patients, had a lower risk of developing HZ, probably because their cell-mediated immunity was enhanced.6,10 Use of varicella vaccine to enhance varicella-zoster virus-specific cell-mediated immunity has been shown to prevent the development of HZ in older people.11,12 A previous study of 290 volunteers aged 40–45 years showed that body mass index (BMI) was positively associated with selected cell-mediated immunity parameters.13 We therefore hypothesized that BMI may have some impact on the development of HZ.The epidemiology of incidence and risk factors for HZ has been assessed by several studies in the United Kingdom,14 In this study, we used data from the SHEZ Study to investigate whether BMI was associated with HZ prevalence at baseline and incidence during follow-up.The Shozu Herpes Zoster (SHEZ) Study was a 3-year prospective cohort study that aimed to determine the incidence and risk factors for HZ among a general Japanese population.14 This study used data from the SHEZ Study, which was conducted in accordance with the Ethical Guidelines for Epidemiological Research and the Ethical Guideline for Clinical Studies after obtaining written informed consent from all participants. The SHEZ Study was approved by the Ethics Committee of the Research Foundation for Biomedical Diseases of Osaka University, Osaka University , the National Institute of Biomedical Innovation, and Nara Medical University.The SHEZ Study is a 3-year community-based prospective cohort study in Shozu County, Kagawa Prefecture. It aimed to examine the incidence and risk factors for HZ. The detailed methods of this study have been described previously.14 HZ is commonly observed in older people,1,15 and therefore the study only included people aged ≥50 years. From a total of 19,058  residents, 12,522  aged ≥50 years were registered in the SHEZ Study. Of these, 211 individuals (95 men and 116 women) with no BMI data were excluded from this study. This left 12,311 individuals  for inclusion in the cross-sectional analysis for prevalence of HZ at baseline. Of those 12,311 individuals, we further excluded 1,818 individuals  with a history of HZ before the start of the study, leaving 10,493 individuals  for inclusion in the analysis of incidence of HZ. The participants’ enrollment process is shown in a flow chart  who were recruited to this study from December 2008, as described previously.During the 3-year follow-up, 584 people (338 men and 246 women) died, 58 people (18 men and 40 women) were lost to follow-up, 43 persons (18 men and 25 women) withdrew, 39 people (12 men and 27 women) moved away, and one woman developed dementia.14,16Participants were recruited between December 2008 and November 2009, and the baseline survey was conducted at registration. At the time of enrollment, each participant underwent an interview, and completed a self-administered health questionnaire including information about lifestyle habits , and social/psychological factors. The interview was conducted by research physicians to collect information about past history of HZ and other diseases, and family history of HZ.2. It was classified into three categories: underweight (<18.5 kg/m2), normal (18.5 to <25 kg/m2) or overweight (≥25 kg/m2).BMI was calculated as the body weight divided by the square of the height (both self-reported), expressed in units of kg/m14 Participants were instructed to telephone the onsite study office if they showed any symptoms of herpes zoster, such as skin rash or pain, between the monthly telephone calls. The site office was open 24 hours a day. The study staff asked anyone with symptoms to visit a clinic or hospital for diagnosis and any treatment, and would accompany patients or meet them at the clinic or hospital. When a patient with suspected HZ visited a clinic or hospital without calling the study office, physicians at that clinic called the study office.We conducted active surveillance for the incidence of HZ via monthly telephone surveys using an established script during the follow-up period.The research team evaluated pain, photographed skin areas with rash or pain, and collected venous blood to check for varicella-zoster virus using polymerase chain reaction (PCR) analysis at the first visit. A final diagnosis was made by the outcome evaluation team of three dermatologists using this clinical information.t-test for continuous variables, such as age and BMI, and the chi-square test for categorical variables, using the normal-weight group as a reference.To examine differences in baseline characteristics of the participants by BMI category  in total participants and both sexes, we used Student’s 4–9,14In the cross-sectional analysis for the prevalence of HZ at baseline, we used logistic regression analysis to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) and identify any association between BMI category and a past history of HZ after adjustment for age and sex. We subsequently adjusted other confounding variables including smoking (≥one cigarette per day or not), drinking , exercise habit (≥3 hours/week or not), walking (≥1 hour/day or not), sleep time (<6 hours/day or not), perceived mental stress (yes or no), having a positive or optimistic mindset/view (yes or no), and history of diabetes mellitus (yes or no), autoimmune disorders (yes or no), and varicella (yes or no). These were chosen as confounding variables, indicated from previous studies.The incidence of HZ was described per 1,000 person-years, and Kaplan-Meier survival curves were plotted. The Cox proportional hazard regression model was used to obtain hazard ratios (HRs) and 95% CIs of HZ incidence by BMI category. The reference group was the normal-weight group, and the analysis was adjusted for the same variables as in the cross-sectional analysis.P < 0.05 was considered statistically significant. The data were analyzed using the Statistical Package for the Social Sciences software for Windows v. 9.1 .All statistical analyses were two-tailed, and Table Table P < 0.01), but there was no significant difference between the underweight and normal-weight groups.Figure P = 0.43), although the proportion of HZ incidence in the overweight group tended to be higher than in the normal-weight group , but insignificant between the normal-weight and underweight groups.In men, the result of the log-rank test was insignificant between the normal-weight and overweight groups  using a primary case database, but did not describe an association between BMI and HZ.13The lower risk of HZ associated with being overweight can be explained in part by a previous study, which found that enhanced cell-mediated immunology, expressed as higher CD4+ count and CD4+/CD8+ ratio, was positively correlated with BMI.The lack of association between BMI and past history of HZ in our cross-sectional analysis could be because of the use of BMI at the baseline, not at the time that symptoms of HZ occurred. BMI could change after a previous episode of HZ, so that this non-differential misclassification may lead to dilution of the real association.This study has three main strengths. First, it had a response rate of nearly 100% (98.3%), assuring unbiased results of community-dwelling individuals. Second, a prospective cohort study with a large sample size of more than 10,000 enabled us to carry out a robust investigation of the possible association between being overweight and the risk of HZ. Third, diagnosis of HZ was accurately conducted by three dermatologists using both clinical signs and symptoms, and varicella-zoster virus identification from venous blood samples.r = 0.96 for height and weight, r = 0.92 for BMI). Differences in mean height, weight, and BMI for the actual versus self-reported measures were 0.2 to 0.3 cm, −0.4 to −0.1 kg, and −0.1 to −0.2 kg/m2.17 Second, the association between being extremely overweight (BMI ≥30 kg/m2), and the risk of HZ could not be examined in this study because there were just 272 participants and two HZ cases among people with BMI ≥30 kg/m2.However, the present study also has some limitations. First, the participants’ height and weight were collected using a self-report questionnaire and were not actually measured. However, BMI estimated using self-reported height and weight has been validated in a previous study of 1,823 Japanese aged 40–68 years, where the self-reported height, weight and BMI were highly correlated with measured values (In Japan, the package insert for varicella vaccine was revised in 2004 to include elderly people with reduced immunity to varicella virus, and in March 2016, people over 50 years of age was added as vaccine targets. Our study suggests that overweight is unlikely raise risk of HZ, and thus target for vaccination can be set independent of BMI.The SHEZ Study showed that being overweight was associated with a lower incidence of HZ among older adults in the general Japanese population than being normal weight. The association was more evident in women than men. Further studies will be required to determine the effects of being overweight on the reduction of risk of HZ.