The aim of this study was to decompose independent effects of age, period, and cohort on trends in outpatient addiction care utilization resulting from alcohol (AUD) and illicit substances use disorders (ISUD). Decomposing trends in addiction care utilization into their independent effects by age, period, and cohort may lead to a better understanding of utilization patterns.n = 46,706) and 18–70 years for ISUD  were standardized to the general Berlin population using data from the German Federal Statistical Office. Classification of utilization as AUD- (F10) or ISUD-related  help-seeking was based on primary diagnoses according to the International Statistical Classification of Diseases and Related Health Problems. Age was measured in years and period as year of data collection. Cohort was defined as the mathematical difference between period and age. Age, period, and cohort analyses were conducted using the intrinsic estimator model on AUD- and ISUD-related outpatient addiction care utilization.Individuals seeking help in Berlin outpatient addiction care facilities between 2008 and 2016 with an age range of 18–81 years for AUD (Age effects on AUD-related utilization were highest in 18- to 19-year-old and in 39- to 59-year-old individuals. ISUD-related utilization declined almost continuously with increasing age. Period effects on AUD- and ISUD-related utilization were small. AUD-related utilization was highest in cohorts born from 1951 to 1986. ISUD-related utilization increased in cohorts born between 1954 and 1973 where utilization peaked, followed by a decline of the same order.Age and cohort effects were the strongest drivers of trends in AUD- and ISUD-related outpatient addiction care utilization. Onset of help-seeking in earlier phases of AUD development should be enhanced as well as help-seeking for AUD and ISUD in general. The highest cohort-related rates in the baby boomer and following cohorts for AUD and ISUD underline an increased demand for addiction care.The online version contains supplementary material available at 10.1186/s12889-022-12744-6. Addiction care constitutes a relevant sector of health care as alcohol and illicit substance use are important contributors to the global disease burden . As addiIn Germany, trend analyses of addiction care utilization are scarce. A recently conducted study of the outpatient German Addiction Care Statistical Service unveiled a decreasing proportion of primary alcohol use disorders (AUD) in the last decade. Furthermore, help-seeking decreased for opioid use disorders but increased for cannabis and stimulants use disorders . These aThe composition of the entire population of individuals with substance use disorders is generally not known except for its characteristics based on samples or point estimates of the number of individuals meeting specific criteria such as reporting intravenous substance use or fulfilling diagnostic criteria of addiction. Hence, the evaluation of changes in addiction care management has to start from the general demographic development as the reference population. This reference to the general population is conceptually comparable to the analysis of mortality as the use of addiction care services can theoretically affect anyone. The use of addiction care services reflects the changes in substance abuse in the general population and thus demographic developments against the background of changing substance abuse habits and societal reactions dealing with emerging problems.Decomposing trends in addiction care utilization into its independent effects by age, period, and cohort (APC) may lead to a better understanding of utilization patterns. Age effects on addiction care utilization reflecting variations in aging processes  reveal cIn order to investigate temporal changes in addiction care utilization in Germany, the present paper aimed to analyze exploratively the independent APC effects on admission to outpatient addiction care related to AUD and illicit substance use disorders (ISUD) in the general Berlin population.Data came from the outpatient Berlin Addiction Care Statistical Service, a series of annual, cross-sectional surveys of participating outpatient addiction care facilities, predominantly delivering addiction counseling. Facility personnel documented data on their clientele according to a German-wide standardized core dataset  containiDouble counting of individuals seeking help more than once per year was accounted for by including only one episode per individual using an identifier variable. Because age was collected at admission, the first rather than the last episode per individual was chosen. In 2010, the identifier variable was missing in 8,388 out of 16,968 cases (including multiple counts) because of a technical malfunction. We treated each of these 8,388 help-seeking episodes as one distinct individual.The primary substance use disorder was defined by codes from the International Statistical Classification of Diseases and Related Health Problems, 10th revision  using the previous 12 months as the reference time. The number of individuals seeking help as a result of a primary AUD (ICD-10 code F10) served as base for AUD-related outpatient addiction care utilization (AUD-related utilization). Analogously, the number of individuals seeking help for a primary ISUD  was used for ISUD-related outpatient addiction care utilization (ISUD-related utilization).The number of individuals using outpatient addiction care (AUD- or ISUD-related) was standardized to the general Berlin population, generating a utilization rate per 10,000 individuals. The size of the general Berlin population was taken from the German Federal Statistical Office . The genAge at admission was measured in years and period as the year of data collection. Cohort was defined as the mathematical difference of period and age.We portrayed descriptive trends by depicting the number of individuals seeking help for AUD or ISUD in Berlin outpatient addiction care standardized to 10,000 individuals from the general Berlin population.Estimating APC effects simultaneously is challenging because of their exact linear dependency (period = age + cohort), known as the “identification problem” . To diseFor this purpose, the AUD- and ISUD-related utilization rates were each composed in age- and period-specific rates containing age as row, periods as columns, and cohorts as diagonal elements. This resulted in 64 (AUD) and 53 (ISUD) age groups , nine period timepoints , and 72 (AUD) and 61 (ISUD) birth cohorts . Choosing single-year groups instead of summarizing them, e.g., in 5-year intervals, was considered to achieve more reliable results. A wider grouping would have shortened the period range noticeably, resulting in a small number of observations in the analytical models (age*period groups). Although the nine period timepoints limit the extent to alter temporal widths of the APC dimensions within sensitivity analyses, we used 2-year intervals in order to test the robustness of the models (SA1). Help-seeking individuals younger than 18 years (focus on adult population) and older than 70 years for ISUD- and 81 years for AUD-related utilization (too few: less than 10 in summarized age groups) were excluded. The number of individuals seeking help within this age and period range was 46,706 for AUD and 51,113 for ISUD. The general Berlin population totaled 25,297,254 individuals.IRR). The IRR and corresponding 95% confidence intervals (CI) were plotted along the APC dimensions.The analyzed utilization rates were non-negative count variables with evidence of overdispersion assessed by likelihood ratio tests. Therefore, we applied negative binomial regression instead of Poisson models , and theOwing to many empty cells in the APC models and lack of power, distinct illicit substances could not be analyzed separately in the main analysis. To examine substance-specific patterns among the sum of ISUD-related utilization, models with separate help-seeking for primary diagnoses of opioids , cannabis , and stimulants/cocaine  use disorders were run as sensitivity analyses (SA2). All analyses were conducted with Stata/SE 15  using the “apc_ie” command . An alphFigure IRR. Most of the age effects were statistically significant for AUD- and ISUD-related utilization. For AUD-related utilization, a bi-modal pattern was observed  and declined thereafter. The rate was lowest beginning from the age of 70 years onwards. ISUD-related utilization showed a nearly continuous decline in the IRR with increasing age  followed by a steep decline until the mid-twenties. After this, the curve decreased more slowly. The lowest IRR was found at age 68 years .Figures ved Fig. . The firIRR = 1.08, CI = 1.02, 1.14), 2012/2013 , 2015 , and 2016   and 2016  . The earliest and latest birth cohorts showed lower IRR than the in-between cohorts. ISUD-related utilization increased from birth cohort 1954 to its peak in cohort 1973 . In later cohorts, the IRR declined again as rapidly as it had risen before. ISUD-related utilization was lowest in the cohorts born from 1938 to 1950. See Supplementary Table 1, Additional File 1 for the estimation of the IRR, 95% CI, and P-values for AUD- and ISUD-related utilization.Cohort effects were statistically significant for most cohorts in both AUD- Fig.  and ISUDThe results of the APC models using 2-year intervals (SA1) are depicted in Supplementary Figs. 1–6  and show similar, but smoothed effects compared with the main analysis. The only exception is the year 2016 for AUD showing an increase in AUD-related utilization compared to the constant trend when using yearly data.SA2 widely mirrored the results of the overall ISUD model . Compared with the ISUD model, where age and cohort effects were mainly statistically significant, these effects were hardly significant for the distinct illicit substances. A detailed comparison revealed that age effects showed the same declining pattern from young to old age . The periodical pattern for ISUD-related utilization with a slight overall increase was also seen for the distinct illicit substances . Cohort effects for OUD, CaUD, and StiUD ressembled those of ISUD-related utilization, with OUD and CaUD peaking at higher levels. CaUD- and StiUD-related utilization showed an additional peak in the late 40 s/early 50 s.Regarding a change in the alpha level to 0.01, only a few of the estimated effects would not be statistically significant (SA3) .Our APC analysis of trends in outpatient addiction care utilization in the general Berlin population revealed the highest age effects for AUD-related utilization in 18- to 19-year-old and in 39- to 59-year-old individuals. ISUD-related utilization declined almost continuously with increasing age. Period effects on trends in AUD- and ISUD-related utilization were quite small. Treatment utilization for AUD was highest in the cohorts born from 1951 to 1986, and ISUD-related utilization increased from the 1954 birth cohort to its peak in the 1973 birth cohort and declined with later cohorts.AUD-related utilization showed a first and slight peak in 18- to 19-year-olds and a second one in middle age. Addiction prevention approaches are often targeted at younger age groups , 15, andIn middle age, even higher AUD-related utilization rates were found than in young adulthood. Here, the onset of alcohol abuse occurred most likely some time ago , and theISUD-related utilization decreased with increasing age. The pronounced peak in young adulthood may be explained by a similar combination as for AUD: frequent experimentation with illicit substance use in young adulthood , the maiWhen controlled for age and cohort, period effects on trends in AUD-related utilization were quite small. Over the relatively short period of 9 years, no major legislative and economic changes took place that could have affected access requirements and the use of addiction care. It is known that only a minority of individuals with AUD seek help , 37. In The ISUD-related period effects were small as well. A slight and singular significant increase was observed in 2016, which may correspond with the implementation of interventions targeting cannabis users . It is iThe earliest birth cohorts born between 1928 and 1943 showed relatively low AUD-related utilization rates, whereas the highest rates were found in the cohorts born between 1951 and 1986. Previous findings on the extent of alcohol use problems indicate higher alcohol use rates in the so-called baby boomer generation compared with earlier cohorts , 42. In The lowest rates regarding ISUD-related utilization were found in the earliest analyzed cohorts. There is evidence that limited health care provision for illicit substance abusers in the past has reduced the survival odds of these groups, resulting in diminished numbers of individuals with ISUD in earlier cohorts . Our finOur study is not without limitations. First, as different APC effects might occur in particularly rural German regions, the generalizability to the whole of Germany should be handled with care. Second, the mode of data collection was uniform for the comparatively short timeframe of 9 years. Hence, long-term trends could not be analyzed, and more substantial period effects might occur in a longer period of time. This emphasizes the need to maintain comparable data collection modes. Third, owing to challenges in detecting multiple individual counts in half the cases in 2010, the number of individuals seeking help was somewhat overestimated in 2010. On average, 1.2 episodes per individual were found for the cases with an undamaged identifier variable. Excluding the cases with a damaged identifier variable would have caused greater bias (underestimation) than accepting the presumable low overestimation. This seems to be negligible as the period trends in 2010 did not turn upwards.The analysis of APC effects on trends in AUD- and ISUD-related outpatient addiction care utilization in a German setting is an innovative study approach. The sample covers almost all individuals using outpatient addiction care in Berlin, reducing the risk of selection bias. To investigate the consistency of the APC effects in the compound measure of ISUD, we separated this group into the most prevalent diagnoses. These analyses largely confirmed the results of the pooled ISUD analysis. The overall APC effects were rather invariant to models using 2-year intervals instead of single-years or an application of an alpha level of 0.01.Age and cohort were the strongest drivers of trends in AUD- and ISUD-related outpatient addiction care utilization in the general Berlin population. The lack of substantial period effects might result from the short period time available. Considering delayed help-seeking, the finding of the highest AUD-related utilization rates in middle age indicates the need for interventions facilitating treatment uptake at an early stage of AUD development. The constant period-related utilization rates suggest a stable attainment rate of addiction care. Considering changes in the affected populations of individuals with AUD or ISUD and low utilization rates for AUD and ISUD per se , 37, enhAdditional file 1. Supplementary Table for the estimation of the IRR, 95% CI, and P-values for AUD- and ISUD-related utilization and Supplementary Figures and Tables regarding the sensitivity analyses SA1-SA3


Tic disorders and Tourette syndrome are the most common movement disorders in children and are characterized by movements or vocalizations. Clinically, Tourette syndrome is frequently associated with comorbid psychiatric symptoms. Although dysfunction of cortical–striatal–thalamic–cortical circuits with aberrant neurotransmitter function has been considered the proximate cause of tics, the mechanism underlying this association is unclear. Recently, many studies have been conducted to elucidate the epidemiology, clinical course, comorbid symptoms, and pathophysiology of tic disorders by using laboratory studies, neuroimaging, electrophysiological testing, environmental exposure, and genetic testing. In addition, many researchers have focused on treatment for tics, including behavioral therapy, pharmacological treatment, and surgical treatment. Here, we provide an overview of recent progress on Tourette syndrome. Tourette syndrome (TS) indicates the presence of multiple motor and vocal tics spanning a period of more than 1 year, and onset is before the age of 18 years. The cardinal features of tics are a premonitory urge (an unpleasant sensation preceding tics)2, suppressibility (the ability to voluntarily suppress tics for variable periods)3, and suggestibility (more likely to experience a tic when it is mentioned)4. Tics can be associated with various psychiatric comorbidities, which can complicate the clinical picture. Since the most recent previous review in this journal5, the number of publications on tic disorders has been steadily increasing  or vocalization creasing , leadingDiagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision (DSM-IV-TR) required a year of tics, excluding any tic-free period of three months or longer, for the diagnosis of TS; however, the three-month requirement was removed in the DSM-51. The International Classification of Diseases 10th revision (ICD-10) required “multiple motor tics” and one or more vocal tics for the diagnosis of TS, but the requirement for more than one motor tic was removed in ICD-117.Recent years have seen changes to definitions of tic disorders. The 9. Traditionally, experts have asserted that a tic disorder that began only in the past few months would usually disappear within a year; however, a direct follow-up study revealed that at least 90% of children still exhibited tics after a year10. Among them, children who could suppress tics better under conditions of immediate reward showed less severe tics at follow-up11. A population-based longitudinal study of parents and children with TS showed that low socioeconomic status was a risk factor for TS and chronic tic disorders12. A longitudinal cohort study of children with TS at the Danish National Tourette Clinic identified that severity of tics, attention-deficit/hyperactivity disorder (ADHD), and obsessive–compulsive disorder (OCD) in childhood strongly predicted the corresponding severity scores in early adulthood13. In the same group, 18% of participants who were at least 16 years old were tic-free, 60% had minimal or mild tics, and 22% had moderate to severe tics, indicating an age-related decrease in tics14.Tic symptoms generally follow a fluctuating course in terms of severity and frequency, with a mixture of old and new tics, and may be exacerbated by psychological and physical strains (such as anxiety or fatigue) and environmental changes15. A large cross-sectional study of 617 adults and children with tic disorders found good internal consistency of the YGTSS between children and adults but suggested some modifications to improve its usability and value16. Similarly, the European Multicentre Tics in Children Study (EMTICS), which includes 16 clinical sites, examined the psychometric quality of the YGTSS and found overall good results but suggested some modifications, including that the total tic severity scale and the impairment rating be used separately17.The Yale Global Tic Severity Scale (YGTSS) was invented to rate tic severity18. Tics can be further classified as clonic, tonic, or dystonic on the basis of their phenomenology20. Clonic tics are abrupt, brief jerking movements. Dystonic tics are sustained abnormal movements, whereas tonic tics are isometric contractions. Some authors add blocking tics, namely transient interruptions of ongoing motor activities or speech without loss of consciousness20. A prospective study identified tonic tics in 85% of adults and 64% of children with TS; tonic tics correlated with the number of tics, severity, and comorbidities21.Both motor and vocal tics are categorized as simple or complex22. Compared with TS, functional tics are thought to be characterized by lack of premonitory urge and suppressibility, female preponderance, the presence of other functional symptoms, resistance to tic medications, and lack of positive family history of tic disorders22. During the Covid-19 pandemic, we encountered many adolescents with sudden onset of severe tics and tic-like movements. Some of the cases may be explained by increased stress exacerbating pre-existing tic disorders in the context of widespread social stressors, but other cases were more consistent with a functional tic-like disorder23. Some patients before onset of their symptoms had watched videos of social media influencers demonstrating similar tic symptoms, suggesting probable social contagion23.Functional tic-like movements, which are usually rare in clinical practice, have recently drawn attention. Clinical features of tics and functional tic-like movements overlap and can coexist, which can make it difficult to differentiate tics from functional tic-like movements24. In a meta-analysis of school-based studies, the prevalences of transient tic disorder , chronic vocal tics (phonic tics of more than 1 year but no motor tics), chronic motor tics (motor tics of more than 1 year but no phonic tics), and tic disorder not otherwise specified (tics that do not meet criteria for other tic disorders) were estimated to be 3.0%, 0.7%, 1.7%, and 0.8%, respectively25. However, this analysis excluded several studies that used direct observation to identify tics, and these studies generally reported much higher prevalence. A meta-analysis using data from population-based studies conducted in China reported overall prevalences of 1.7% for transient tic disorder and 1.2% for chronic motor or vocal tic disorders26. A systematic review of 21 population-based studies of children who were 4 to 18 years old estimated the prevalence of TS to be 0.52% 27, although some high-quality studies find prevalence to be as much as 10-fold higher28. In contrast, prevalence is much lower in adults; a meta-analysis of three studies involving 2,356,485 adults estimated the prevalence to be 0.001% (118 cases per million)29. However, given that most children with recent onset of tics continue to have tics for over 1 year10, this result probably underestimates the true prevalence of TS among the general population. A possible explanation for this is that a substantial number of patients with tics do not seek medical attention or do not realize they have tics since their tics are subtle and not troublesome. Therefore, a large population-based observational study is needed to evaluate the true prevalence of TS.The true prevalence of tic disorders is difficult to estimate owing in part to symptom fluctuation over time and heterogeneous presentations31. Various methods, including neuroimaging, physiological, laboratory, animal, and genetic studies, have been used to unveil its pathophysiology.The pathophysiology of tic disorders is complicated, and studies have implicated cortical–striatal–thalamic–cortical (CSTC) circuits and associated neurotransmitters32. A follow-up study using high-resolution magnetic resonance imaging (MRI) in 41 children with new-onset tics showed that larger hippocampal volume at the baseline visit predicted higher tic severity at 1-year follow-up33. A high-resolution MRI study using voxel-based cerebellar morphometry and seed-to-voxel structural covariance mapping  demonstrated reduced cerebellar gray matter volume in patients with TS, which was considered to affect higher-order cognitive and motor processing34. The study also showed abnormal gray matter structural connectivity with frontal and cingulate cortices and sensorimotor networks, indicating that cerebellar involvement in tics is part of cortico–basal ganglia–cerebellar interactions.Several neuroimaging studies have investigated anatomical changes as well as structural and functional connectivity32. To investigate changes of functional brain organization in TS with development, a resting-state functional connectivity MRI study of 172 children and adults with TS was performed35. Functional connectivity alteration was age-specific: brain networks in children with TS appeared “older” whereas brain networks in adults with TS appeared “younger” than those in age-matched controls35. A resting-state functional MRI (fMRI) study using graph theoretical measures focused on topological changes of basal ganglia–thalamocortical and cortico–cerebellar brain networks in TS36. Patients with TS showed increased basal ganglia–cortical and thalamo–cortical connectivity and reduced cortico–cerebellar connectivity. They also showed decreased connectivity within the precuneus, posterior cingulate, and right and left angular gyri and within the right and left insular cortex. The altered connectivity may suggest a lack of brain maturation and interoception involvement as neural correlates of tics and premonitory urges.Functional imaging studies have been providing new insights into the temporal correlation of activity between different brain regions 37. Motor severity and premonitory urge severity were not correlated and were associated with anatomically separate regions of the right insular cortex. This result suggests that tics and premonitory urges have separate network connectivity. A resting-state fMRI with seed-based functional connectivity analysis was conducted to investigate neuronal functional connectivity of tics, OCD, and premonitory urge38. Greater connectivity between the putamen and sensorimotor cortex was noted in participants with TS, whereas less connectivity between the supplementary motor area (SMA) and thalamus and between the caudate and precuneus was noted in participants with obsessive–compulsive symptoms. Moreover, a case-control study using diffusion tensor imaging MRI and transcranial magnetic stimulation (TMS) over the right pre-SMA was conducted in children with chronic motor tics and healthy controls39. The study showed that pre-SMA-mediated motor cortex inhibition was impaired in participants with tic disorders; less inhibition correlated with worse tic suppressibility and more severe tics39. The functional connectivity within sensorimotor regions might play a role in tic severity, premonitory urges, suppressibility, and obsessive–compulsive symptoms.A functional imaging study using whole-brain structural MRI with voxel-based morphometry techniques and seed-to-voxel structural covariance mapping was conducted to investigate structural connectivity of tic severity and of premonitory urges40. A case-control study using resting-state EEG of patients with TS showed decreased frontotemporal–occipital–parietal connectivity and a dysfunctional network of intrinsic long-range connectivity between the frontal and temporal–occipital–parietal lobes and proposed these as potential biomarkers for TS41. Local field potentials can be recorded during deep brain stimulation (DBS) implantation surgery. A retrospective clinical study of 17 patients with TS who underwent DBS of the thalamus showed that increased power in the low-frequency (5–15 Hz) band could be a biomarker for TS and correlated with the severity of tics42.Electrophysiological methods are well suited to studying temporal brain dynamics. A narrative review summarized that electrophysiological studies, including electroencephalogram (EEG) and event-related potential studies, could echo neuronal processes and parallel clinical characteristics of TS43. Another case-control study measuring cerebrospinal ﬂuid (CSF) levels of endocannabinoids demonstrated significant alterations in the levels, suggesting an involvement of the endocannabinoid system in the pathophysiology of TS44. The study authors speculated that an increased level of endocannabinoids might be a compensation for dopaminergic hyperactivity.Recently, new evidence has supported dopaminergic involvement in the pathophysiology of TS. A case-control study measuring urine tetrahydroisoquinolines, which modulate dopaminergic neurotransmission and metabolism in the central nervous system, demonstrated a significant increase in the levels of norsalsolinol in patients with TS and those with TS and ADHD, suggesting dopaminergic hyperactivity in the pathophysiology of TS45. Sapap3-knockout mice exhibited tic-like movements with short, sudden, repetitive movements 46. The tic-like movements in Sapap3-knockout mice were reduced significantly by treatment with aripiprazole, an atypical antipsychotic drug used to treat tics46. Another animal experiment was conducted using D1CT-7 transgenic TS mice47. D1CT-7 mice are a “transgenic line generated through the attachment of a neuropotentiating cholera toxin to the D1 receptor promoter” and have been considered a good animal model of TS48. The researchers administered DK-I-56-1, a selective positive allosteric modulator of GABA-A receptor containing alpha6 subunits, to D1CT-7 transgenic TS model mice and found that DK-I-56-1 was as effective as D1 and D2 receptor antagonists and significantly reduced tic-like movements47. MicroRNAs (miRNAs) have attracted attention as biomarkers for diseases, intercellular communication, and neural development49. A clinical study using serum miRNA expression proﬁles as molecular fingerprints for children with either TS or Arnold–Chiari malformation showed nine differentially expressed miRNAs as potential molecular tools for the diagnosis of TS50. These pathophysiological studies have converged to suggest the importance of CSTC circuits and their associated neurotransmitters and other brain regions but have not yet supported a clear, inclusive theory of tic pathophysiology.Animal studies have also suggested CSTC circuit involvement in TS pathophysiology. Postsynaptic SAP90/PSD95-associated protein 3 (SAPAP3) is highly expressed in the striatum and plays an important role in cortico-striatal circuitry in OCD-like behaviors, as shown in a mouse experiment51. Similarly, a prospective case-control study showed that maternal pro-inflammatory states were associated with tics and OCD in children, supporting a possible role of maternal inflammation52.Environmental influences such as prenatal and perinatal epigenetic factors and inflammatory factors have been investigated as underlying causes of tic disorders. A systematic meta-analysis found a 35% increase in the risk of tic disorders in offspring with maternal smoking during pregnancy 53. The article also postulated that hyper-reactive systemic immune pathways and neuroinflammation may help explain the natural fluctuations of tic disorder symptoms over time.Inflammation has been extensively discussed in tic pathophysiology. A recent review article on immunological mechanisms in the pathophysiology of tic disorders argues that innate and adaptive systemic immune pathways and neuroinflammatory mechanisms play an important role in the pathogenesis of at least some patients with TS54. A case-control autopsy study  using basal ganglia transcriptome by RNA sequencing in the caudate and putamen found disrupted basal ganglia neuronal signaling55. The study also found a significant increase in immune and inflammatory transcripts. These results suggest metabolic alterations and inflammatory involvement in TS pathophysiology. A comprehensive review of immune dysfunction in TS discussed clinical correlation with group A Streptococcus (GAS) infection, autoantibody analysis, and gene expression studies and identified some support for a hypothesis of autoimmune dysfunction as the pathophysiology of TS and its associated neuropsychiatric symptoms56.The prevalence and characteristics of tics in patients with encephalitis were reviewed in a systematic study, which found that sporadic cases of tics were associated with encephalitis, particularly during a post-encephalitis period, and with basal ganglia involvement57, and immunohistochemistry staining on rat brain sections failed to show evidence of specific neuronal surface antibodies  in children with TS58. A prospective CSF analysis study demonstrated positive oligoclonal bands in 20% of participants (4 out of 20) but did not compare that rate with that of tic-free control participants and observed no specific surface autoantibodies, such as NMDA, CASPR2, LGI1, AMPA, and GABA1/B, and no specific binding pattern59. Although specific surface antibodies were not detected, the presence of oligoclonal bands in CSF analysis could suggest an autoimmune etiology in TS59. The authors suggested a pathological immune process of intrathecal IgG antibody production, considering that other studies find OCB positive in only 5% of healthy individuals and it is rarely seen in patients with non-inflammatory diseases.CSF analyses have revealed inflammatory mechanisms in tic disorders. The longitudinal EMTICS study investigated the role of environmental exposure and immunology in the clinical course and comorbidities of TS60. GAS exposure was not significantly associated with tic exacerbations ; however, it was associated with hyperactivity–impulsivity symptoms. The study authors concluded that GAS exposure was less likely to be a risk factor for tic exacerbations; therefore, the evaluation and treatment of GAS infections are not warranted in the context of worsening of tics. The authors also attempted to identify biomarkers of tics, examining hair cortisol concentration as a physiological marker of long-term stress in patients with tics, and found no association between hair cortisol concentration and tic severity61.On the other hand, the EMTICS study also examined whether exacerbations of tics and comorbid symptoms were associated with GAS exposure, which was determined by throat swabs and serum antibodies63.Tic disorders are polygenic inherited disorders involving different genes. In a population-based cohort study in Sweden using the Genome-wide Complex Trait Analysis program, the heritability estimate of TS was 0.58 to 0.77, and the odds ratio for tic disorders of first-degree relatives of probands with tic disorders (18.7) was significantly higher than that of the second-degree (4.6) and third-degree (3.1) relatives64. The SLITRK1 gene on chromosome 13q31.1 encoding a single-pass transmembrane protein in the central nervous system was reported to be associated with TS65. The IMMP2L gene encoding the inner mitochondrial membrane peptidase subunit 2 was implicated in TS66, but a recent study using skin fibroblasts from adults with the IMMP2L deletions and TS failed to show evidence of mitochondrial dysfunction67. Expression analysis, genotyping, and methylation analysis of SLC6A4 in 57 patients with TS showed a significantly higher expression of SLC6A4 mRNA, which encodes serotonin transporter, compared with healthy controls68. SLC6A4 overexpression may contribute to TS pathophysiology by increasing serotonin clearance. Whole-exome sequencing studies identified the CELSR3 gene on chromosome 3p21.3169, the ASH1L gene on chromosome 1q2270, and possibly disrupted variants of the OPRK1 gene on chromosome 8q11.23, encoding the opioid kappa receptor71 as high-risk genes for TS.Several candidate susceptibility genes for TS have been identified but have not been confirmed and this is likely due to the small sample size of each study and genetic and phenotypic heterogeneity69. That study also identified shared genetic variance with OCD and autism spectrum disorder. The Brainstorm Consortium Genome-wide association study data on 3581 patients with TS and 7682 controls identified three significant gene sets involving ligand-gated ion channel signaling, lymphocytic and cell adhesion, and trans-synaptic signaling processes72.A study of 802 TS trios found that novel mutations were more common in simplex but not multiplex families and identified a greater-than-expected number of mutations related to cell polarity77. Aggressive behavior measured by the Overt Aggression Scale is associated with the severity of comorbid ADHD78. According to a systematic literature review, 35% of patients with TS had SIB, and obsessive–compulsive behaviors were correlated with SIB in patients with TS74. Similarly, a cohort study of Polish patients with TS showed that SIB was associated with tic severity, OCD, and ADHD79. To understand the prevalence of psychiatric comorbidities, a cross-sectional interview study of 1374 adolescents and adults with TS and 1142 TS-unaffected family members was conducted. The study found that 86% of patients with TS had a lifetime prevalence of any psychiatric symptoms (excluding tics) and 58% of them had more than two psychiatric illnesses80. The severity of tics as well as symptoms of the two most common comorbidities—ADHD and OCD—declined during adolescence in a 6-year Danish cohort study of 314 children and adolescents with TS14.TS is frequently accompanied by ADHD, OCD, anxiety, depression, autism spectrum disorder, sleep disorders, migraine, rage attacks, and self-injurious behavior (SIB)81. Moreover, patients with TS undergoing antipsychotic treatment had a lower risk of TBI than infrequent users . The study authors speculated that the improvement of tics with antipsychotics protected against TBI or that antipsychotics reduced their impulsivity (or SIB). A large population-based cohort study using the Swedish National Patient Register has shown that individuals with tic disorders have a higher risk of transportation-related injuries and death than the general population ; however, TS individuals without ADHD did not have a significantly elevated risk, suggesting that comorbid ADHD was the contributor to the automotive injuries82. The same group showed a higher risk of metabolic and cardiovascular disorders such as obesity , type 2 diabetes , and circulatory system diseases  in patients with TS compared with the general population83. Surprisingly, use of antipsychotics for more than 1 year significantly decreased the risk of metabolic and cardiovascular disorders83. The risk of substance misuse  in individuals with TS was higher than that in the general population 84.Non-psychiatric comorbidities have been increasingly reported. A study using data from the National Health Insurance Research Database of Taiwan showed an increased risk of traumatic brain injury (TBI) in patients with previously diagnosed TS 85. A case-control study on learning ability in TS revealed impairment of visual associative learning (a style of learning where one learns things by associating them with a stimulus), but retrieval and generalization were not affected86. Another case-control study using an automatic imitation task showed that participants with TS responded faster than controls but had higher error rates, suggesting a different control mechanism of their motor responses to sensory stimuli from observed actions87. Yet another case-control study examined the executive function and psychomotor speed of TS children with ADHD, TS children without ADHD, ADHD children without tics, and controls and showed that the severity of ADHD possibly affects executive dysfunction88. ADHD appears to play a role in learning, and ADHD treatment may improve learning and executive function, but more research is necessary. A case-control study in Sweden showed that treatment-seeking individuals with tic disorders experienced academic underachievement from primary school through university89.Although it is generally assumed that most patients with tic disorders have normal intelligence, the association between TS and cognition is unclear90. A retrospective analysis of 1018 patients with TS and chronic motor tic disorders (motor tics for more than 1 year but no phonic tics) found that TS and chronic tic disorders were not distinct in clinical or demographic variables and suggested that “tic spectrum disorders” with TS were more severe and were associated with more comorbidities whereas chronic motor tics were less severe91. A very compelling data analysis and review concludes that TS and chronic motor or phonic tic disorder are the same illness or at least that they occur on a spectrum with TS at the more severe end92. In clinic settings, the term TS can occasionally provoke avoidance from patients and their guardians because of myths and misconceptions created by social media. These findings will allow clinicians to advise patients on the expected clinical course of tics and other comorbidities, and the concept of “tic spectrum disorder” may help patients and guardians accept the diagnosis.Owing to heterogeneous symptoms, several groups have attempted to categorize or view tic disorders and TS as a spectrum. Using a cluster dendrogram of hierarchical ascendant clustering based on comorbidities, a prospective clinical study of 174 patients with TS demonstrated three clusters: TS with no other neurodevelopmental comorbidities; TS with higher intelligence, attention deficit, and handwriting problems; and TS with neurodevelopmental comorbidities, learning disabilities, and academic impairments93, non-tic-related symptoms can be more problematic than tics themselves94. Paying attention to comorbid symptoms and treatment is often more important than addressing tics themselves. Continual assessment of comorbidities by using a scale or assessment tool is warranted. For example, the mini-child Tourette syndrome impairment scale, a parent- and child-reported tic impairment scale, was invented to quantify tic-related and non-tic-related impairment across the school, home, and social domains and was shown to be well correlated with tic and comorbid symptom severity96.Although a large interview study across nine academic TS and OCD specialty clinics showed a correlation between tic severity and tic impairment97.The European Society for the Study of Tourette Syndrome (ESSTS) is about to release an updated version of its 2011 guidelines for TS, and the revised guidelines will cover in detail many of the points we touch on in this section98. These therapies consist of exposure and response prevention (ERP), habit reversal therapy (HRT), or its descendant comprehensive behavioral interventions for tics (CBIT)99. A randomized control trial evaluating the long-term effect of both HRT and ERP in children and adults with tic disorders showed that the benefit of the therapies persisted at the 1-year follow-up visit in 74% of participants100. Despite robust evidence of the behavioral therapies to reduce tic frequency and severity and diminish the urges, finding a trained therapist can be challenging. To improve access to the therapies, internet-based training programs, which have shown improvement in parent-rated tic severity, tic-related impairment, and quality of life, have been developed102. Group-based behavioral therapies have also been investigated because group therapies are more cost-effective, treating more patients at once. They can also provide an opportunity for patients to meet in person, share their experiences, and support each other. An open-label controlled clinical trial of combined HRT and ERP was conducted in adolescents with TS103. The participants were randomly assigned to either individual or group therapy. In total, 67% of participants were considered responders, and there was no significant difference between individual and group therapies. Furthermore, group-based CBIT for children and adolescents showed a significant reduction in tics and severity of comorbid symptoms such as anxiety, behavioral problems, and aggressive behaviors105.Behavioral therapies are recommended as the first-line treatment for tics by the American Academy of Neurology practice guidelines98. Most patients with tics respond to behavioral therapy or tic-suppressing medications. However, some do not, and others experience problematic side effects, so new treatment modalities are being investigated. Recently, novel drugs have been investigated for the treatment of tics. Tiapride, a dopamine receptor blocking agent, is used mainly in Europe for the treatment of tics. A clinical study of children with TS showed that 83% of participants responded to tiapride and no patients had serious adverse reactions106. Ecopipam, a selective D1 receptor agonist, was studied in a randomized, placebo-controlled crossover study of children and adolescents with TS107. Ecopipam significantly reduced tic severity at 16 days  and 30 days  and was well tolerated without serious side effects. Lurasidone, a dopamine and serotonin receptor antagonist, is an atypical antipsychotic used for the treatment of schizophrenia and bipolar disorder108. Six children and adolescents with treatment-refractory TS, aggressive behavior, and obsessive symptoms responded significantly to lurasidone as an add-on therapy to risperidone or aripiprazole109.Pharmacological treatment is considered when behavioral interventions fail or are unavailable or when urgent benefit is required. Various medicines, including alpha-2 adrenergic agonists, antiepileptic drugs, and dopamine receptor blocking agents, are commonly used for the treatment of tics110. Tetrabenazine, a dopamine-depleting agent, was found to be effective in an open-label study of 120 patients with tics111. Subsequently, an open-label study of 28 children and adolescents with TS investigated valbenazine, which is a purified parent drug of the (+)-α-isomer of tetrabenazine, but it failed to show statistically significant efficacy112. A trial of deutetrabenazine, a deuterated form of tetrabenazine, also failed to show a significant benefit (ARTISTS1).Dopamine-depleting agents block the vesicular monoamine transporter type 2 and are used to treat hyperkinetic movement disorders such as chorea, tardive dyskinesia, and tics113. A retrospective data analysis of adults with TS who received cannabis-based medicine showed a subjective improvement in tics, comorbidities, and quality of life, although adverse effects were noted in half the patients114. A randomized clinical trial to evaluate the safety and efficacy of cannabis in adults with TS was launched in 2018, but it was terminated because the recruitment and enrollment were prolonged . A multicenter, randomized, double-blind, placebo-controlled trial of patients with tic disorders is being conducted to investigate the use of the cannabis extract nabiximols for the treatment of tics115.The use of cannabis and cannabis-derived products has been reported to improve tics. A study of TS model rodents demonstrated that delta-9-tetrahydrocannabinol might reduce tic behaviors and premonitory urges in young adult mice but might also exacerbate tic behaviors in juvenile mice10, fish oil, gastrodin, and vitamins B, C, D, and E), chiropractic manipulations, meditation, acupuncture, hypnosis, homeopathy, and biofeedback—have been reported for the treatment of tics117; however, the evidence is limited because of a lack of randomized control studies. The efﬁcacy and safety of a Chinese herbal medicine (5-Ling granule) in the treatment of TS were evaluated in a multicenter, double-blind randomized controlled trial, finding it as effective as tiapride in improving tic symptoms118.Complementary and alternative medicines—including dietary or nutritional supplements  using low-frequency repetitive TMS to the bilateral SMA for 15 sessions showed a statistically significant decrease in tic severity120. These results are promising but a large randomized trial is warranted to validate the findings.TMS is a non-invasive brain stimulation treatment to modulate neural plasticity and has been attracting considerable attention121. Patient selection criteria and an algorithm for DBS treatment for TS, consisting of five pillars, have been proposed: high tic severity, tic-related impact on quality of life, failure of behavioral and pharmacological treatment, stability of comorbid symptoms, and age of 18 years or more122. The International Deep Brain Stimulation Database and Registry reports an overall adverse event rate of 35%, and medically serious complications—intracranial hemorrhage (1.3%), infection (3.2%), and lead explantation (0.6%)—were less common than stimulation-induced adverse effects, including dysarthria (6.3%) and paresthesia (8.2%)121. Tic-like behaviors have also been reported as adverse effects of DBS. A patient who underwent DBS of the ventral internal capsule and ventral striatum for treatment-resistant major depressive disorder developed stimulation-dependent TS-like behaviors such as motor tic-like movements in the arms as well as coprolalia and stuttered speech123.DBS may be a promising neurosurgical treatment for tics121. A double-blind randomized controlled trial of bilateral anterior globus pallidus pars interna (GPi) DBS was conducted in 19 patients with TS; one group received active stimulation and the other group received sham stimulation124. No significant difference in tic severity was noted three months after surgery. However, in an open-label, follow-up study, 75% of patients had an average 70% tic reduction in the YGTSS total score after 48 months125. Posteroventral GPi DBS has also been reported126. In addition to the GPi, the thalamus, globus pallidus externus, anterior limb of the internal capsule, and nucleus accumbens have been suggested as targets for DBS for tics127. An adult with TS who underwent bilateral dual-targeted DBS to the centromedian–parafascicular complex (CM-Pf) and the ventral capsule/ventral striatum reported benefits in terms of motor and non-motor TS symptoms128. A prospective clinical study of 25 patients with TS who underwent DBS to the CM-Pf showed improvement of tics by 45% at the 1-year follow-up129. Another, retrospective, study focused on DBS with a target of either the ventralis oralis (Voi) or the CM-Pf of the thalamus (41 patients) and the anteromedial GPi (am-GPi) (14 patients)130. They found possible superiority of the am-GPi to the Voi/CM-Pf for the treatment of obsessive–compulsive symptoms in TS; however, target selection was not random, as the authors note the CM-Pf was preferred for patients with impairment mostly from tics rather than comorbidities. The International Tourette Syndrome DBS Database and Registry conducted a retrospective, probabilistic tractography study of DBS targeting the GPi or CM131. Stimulus-dependent connectivity to specific regions was shown to be likely to mediate improvement in tics131. Specifically, the improvement of tics by DBS in GPi can be attributed to modulation of the limbic and associative networks by optimally positioned stimulation contacts, while the improvement of tics by DBS in the medial thalamus can be attributed to modulation of the sensorimotor and parietal–temporal–occipital networks. This finding could be used to refine the neuromodulation targets and stimulation parameters for tic disorders. Currently, it is common to select targets on the basis of clinical symptoms. However, considerable debate remains about the optimal DBS target (or targets) in TS, and there are no evidence-based guidelines to assist in the selection of DBS target in TS. Most studies that reported successful DBS results for the treatment of TS are case reports or open-label studies with various targets, and randomized control studies have shown inconsistent results134. Some investigators have interpreted the greater benefit in open-label trials as evidence of our difficulty predicting ideal lead location and pulse characteristics for treating tics. In fact, considerable debate remains about the optimal DBS target (or targets) in TS, and there are no evidence-based guidelines to assist in the selection of DBS target in TS. However, in other movement disorders, the stringent requirements of randomized controlled trials have not prevented DBS from producing relatively dramatic results . Alternatively, the better results in open-label studies may indicate expectation or placebo effects, even in patients with treatment-resistant TS treated with DBS. Placebo benefit can be demonstrated directly in DBS for Parkinson disease137. Thus, further studies are needed to identify the optimum target, benefits, risks, and stimulation parameters for DBS in TS138, and in our current state of knowledge, selection of patients for DBS surgery, including patients with severe TS, should be done quite cautiously139.There have been many reports of patients with TS who underwent DBS in various targetsAlthough tics are a common movement disorder in children, there are still many unanswered questions, including on the causes and natural history of tics and their relationship with comorbid symptoms. Increasingly many research studies are published each year and have provided new insights into the pathophysiology and etiology of tics. Recent years have seen increasing information about the relationship between tics and comorbidities and about new genetic findings. Inflammatory processes have also been a topic of continued interest.We believe the near future for Tourette research may include more large-scale collaborative studies, which can provide more powerful results. Advances in imaging technology are also likely to enhance our understanding of tics. Treatment of TS is becoming more standardized with the recent American Academy of Neurology and forthcoming ESSTS guidelines. Behavioral therapy interventions are becoming more widely accepted but still have limitations on availability. However, alternative approaches, including internet-delivered and group therapy, are being explored. Furthermore, new medications are still needed and likely will lead to improved treatments. Substantial debate continues about DBS therapy, its effectiveness, and optimal targets, and the international DBS registry will continue to move the field forward. We remain optimistic about improved care for TS that future research in all these areas is likely to produce.


Previous studies have linked the Mediterranean diet (MED) with improved cardiometabolic health, showing preliminary evidence for a mediating role of the gut microbiome. We recently suggested the Green-Mediterranean (Green-MED) diet as an improved version of the healthy MED diet, with increased consumption of plant-based foods and reduced meat intake. Here, we investigated the effects of MED interventions on the gut microbiota and cardiometabolic markers, and the interplay between the two, during the initial weight loss phase of the DIRECT-PLUS trial.In the DIRECT-PLUS study, 294 participants with abdominal obesity/dyslipidemia were prospectively randomized to one of three intervention groups: healthy dietary guidelines , MED, and Green-MED. Both isocaloric MED and Green-MED groups were supplemented with 28g/day walnuts. The Green-MED group was further provided with daily polyphenol-rich green tea and Mankai aquatic plant (new plant introduced to a western population). Gut microbiota was profiled by 16S rRNA for all stool samples and shotgun sequencing for a select subset of samples.Prevotella and enzymatic functions involved in branched-chain amino acid degradation, and reductions in the genus Bifidobacterium and enzymatic functions responsible for branched-chain amino acid biosynthesis. The MED and Green-MED diets were also associated with stepwise beneficial changes in body weight and cardiometabolic biomarkers, concomitantly with the increased plant intake and reduced meat intake.Both MED diets induced substantial changes in the community structure of the gut microbiome, with the Green-MED diet leading to more prominent compositional changes, largely driven by the low abundant, “non-core,” microorganisms. The Green-MED diet was associated with specific microbial changes, including enrichments in the genus Furthermore, while the level of adherence to the Green-MED diet and its specific green dietary components was associated with the magnitude of changes in microbiome composition, changes in gut microbial features appeared to mediate the association between adherence to the Green-MED and body weight and cardiometabolic risk reduction.Our findings support a mediating role of the gut microbiome in the beneficial effects of the Green-MED diet enriched with Mankai and green tea on cardiometabolic risk factors.NCT03020186) on January 13, 2017.The study was registered on ClinicalTrial.gov (The online version contains supplementary material available at 10.1186/s13073-022-01015-z. The Mediterranean (MED) diet, high in nuts, vegetables, and legumes and low in red meat intake, is recommended for the prevention of cardiometabolic diseases –3.n = 82) of an isocaloric MED diet intervention revealed changes in multiple microbial features in the gut, including an increased abundance of major dietary fiber metabolizers such as Bacteroides cellulosilyticus  or dyslipidemia . Exclusion criteria are detailed in Additional file Design and intervention of the DIRECT-PLUS, as well as primary outcomes of the trial , were previously reported in detail , 9. ThisAll eligible participants were randomized in a 1:1:1 ratio, stratified by gender and work site , into one of the three intervention groups: healthy dietary guidelines (HDG), MED, Green-MED, all combined with physical activity accommodation . All participants were provided with a free gym membership and were guided to engage in moderate-intensity physical activity  HDG group: In addition to physical activity, participants received standard nutritional counseling based on the Harvard T. H. Chan School of Public Health’s “The Nutrition Source,” a website sharing informed nutrition knowledge with the public, providing science-based guidance for healthy living. 2) MED group: In addition to physical activity, participants were instructed to adopt a calorie-restricted Mediterranean diet  MED grou. The MEDWolffia globosa (Mankai strain) plant frozen cubes, as a green shake for dinner. Both the MED and green-MED diets were equally calorie-restricted . Two hundred eighty-six subjects, all of which provided a fecal sample at baseline (97%), were included in the current analyses.(3) Green-MED group: In addition to physical activity and the provision of 28g/day walnuts, the Green-MED diet was further restricted in processed and red meat and was richer in plants and polyphenols. The participants were provided with 3–4 cups/day of green tea and 100g/day of frozen Details regarding the lifestyle interventions and motivation techniques are provided in Additional file Measurements and sample collection were obtained at baseline and 6 months. Participants were weighed without shoes to the nearest 0.1 kg. Waist circumference was measured halfway between the last rib and the iliac crest to the nearest millimeter.Two blood pressure (BP) measurements and pulse were recorded after resting, using an automatic BP monitor . Blood pressure was calculated as the mean of the two measurements.Blood samples were obtained after a 12-h fast, centrifuged, and stored at –80°C pending analyses; further information regarding the assays can be found in Additional file Fecal samples were collected at the study site, immediately frozen to –20°C for 1–3 days, then transferred to –80°C pending DNA extraction. Participants prescribed antibiotic therapy 2 months prior to the delivery of baseline fecal samples were excluded from all microbiome analyses. All blood biochemical assays were performed at the University of Leipzig, Germany. 16S rRNA gene sequencing was performed at Fondazione Edmund Mach, Italy. Fecal metagenomic sequencing was performed at CoreBiome, MN, USA.To characterize the microbiome composition and to assess taxon abundance, fecal DNA from 546 fecal samples was extracted and 16S rRNA gene amplicon sequencing was performed by targeting the V3–V4 variable region of approximately 460-bp length using the bacterial primer pair 341F (5′ CCTACGGGNGGCWGCAG 3′) and 806R (5′ GACTACNVGGGTWTCTAATCC 3′). Paired-end sequencing reads were quality filtered, trimmed, de-noised, and merged using the DADA2 software version 1.14.0 . To rejeTo characterize the microbiome’s functional capacity, a subset of 173 samples (31% of samples) underwent shotgun metagenomics. Samples were collected from 90 participants as part of the pre-transplantation sampling of the DIRECT-PLUS autologous fecal microbiota transplantation study , with 31Assessment of nutritional intake and lifestyle habits was performed using self-reported food frequency questionnaires administered through a computer at baseline and after 6 months , 26. FreWe then applied a Green-MED adherence score to measure the degree of adherence to the Green-MED pattern. The adherence score was created based on the MED index by Willett et al.  and TricAll statistical analyses were performed in R v3.5.0. To assess the effect of dietary intervention on the composition of microbial communities, we applied permutational multivariate analysis of variance (PERMANOVA) on dissimilarity matrices of weighted UniFrac, using the adonis function from the R package vegan with 999 permutations . To furtP values from the PERMANOVA were corrected for multiple comparisons using the Benjamini-Hochberg procedure. For all analyses stratified by core/non-core taxonomic features, the cutoff was defined as >50% prevalence [6 permutations of random sample labeling. For per-feature analysis, we used the R package MaAsLin2 [−5 in at least 5% of samples. To detect differences in changes of microbial features between groups over time, we built linear mixed models that include group, time, and their product term, with participant identifier as random. A significant P value for the product term indicates that over time changes in microbial features differ between groups. For changes in biomarkers and specific microbial features, we determined the gradual dietary effect using Kendall’s tau-b correlation on the percent change in each biomarker across dietary groups and used generalized linear models to assess between-group differences. Dietary groups were considered a ranked variable, taking into account the increase in polyphenols and decrease in red and processed meat across the groups. To assess the correlation between specific taxa and biomarkers, the Spearman correlation test was used.To quantify the percentage of variance explained by change in biomarkers and dietary variables on the gut microbiome’s composition, vectors of person-specific ASV changes were calculated for each ASV per individual as follows: evalence . To asseMaAsLin2 , with miAssessing the mediatory effect of the microbiome, we first employed the meditation analysis suggested by Imai et al.  by the “P values were corrected for multiple comparisons using the Benjamini-Hochberg procedure. All multiple hypothesis testing was controlled for false discovery rate with a target of q < 0.25.We next used the high-dimensional mediation analysis suggested by Zhang et al. , using tTwo hundred ninety-four subjects were recruited in the DIRECT-PLUS weight-loss trial , 9 and rn = 286) provided a fecal sample at baseline and were included in the current analyses. We measured body weight, waist circumference, and blood pressure and collected fasting blood samples, stool samples, and dietary data at baseline and month 6. Of the 546 stool samples profiled by 16S rRNA gene sequencing, 173 were further profiled by shotgun metagenomic sequencing [2. Follow-up stool samples were obtained from 91% of the recruited participants. See Additional file Of those, 97% (quencing . The meaP of interaction = 0.01) as revealed by principal coordinates analysis (PCoA) based on weighted UniFrac distances. To compare the compositional change between groups in a subject-specific manner, we created a log2 change ASV matrix between the two timepoints of each subject. The Green-MED group differed significantly in its change compared to the other two groups , whereas no significant difference was observed between the MED and HDG groups  and group , and a stepwise decrease in Bifidobacterium across the groups . These observations are in accordance with previous reports that linked vegetable-based diets [Prevotella abundance [Bifidobacterium spp. [We conducted per-feature testing by using MaAsLin2 linear mixed models  to idented diets  and adhebundance  and a diium spp. .Fig. 3MEP = 0.02) and a decrease in pathways of BCAA biosynthesis  comparing MED diet groups to the HDG group. MED diet interventions also led to an enrichment in lipid metabolizing pathways, possibly due to the increased lipid intake and decreased carbohydrate intake commensurate with MED diets  that utilize dietary components , we found a stepwise increase in BCAA degrading pathways . As we recently reported, the Green-MED diet led to the greatest body-weight reduction (−6.5%), followed by MED (−5.4%) and the HDG group  [To examine the effects of plant-enriched and meat-depleted diets on cardiometabolic markers, we evaluated the 6-month change in a graded manner across the dietary groups. Among 47 blood biomarkers and anthropometric measurements, significant effects of the dietary intervention were found in 21  .Fig. 4SiEvaluating the association between changes in biomarkers and shifts in microbiome composition (assessed by 16S rRNA sequencing), body-weight change explained the highest proportion of variation (0.9%). Significant associations with compositional changes were observed in the change in several biomarkers, including plasma leptin (0.7%), waist circumference (0.66%), systolic blood pressure (0.5%), HOMA-IR (0.5%), and Framingham risk score .In order to assess the interplay between adherence to the Green-MED diet, gut microbial changes, and cardiometabolic effects, we devised a 9-dimensional adherence score (the “Methods” section), modified from the original Mediterranean index , 39, 40,q < 0.25). Among Green-MED-associated taxonomic features, we found that change in Prevotella abundance was positively associated with the Green-MED adherence score, while Bifidobacterium was inversely associated with the score  associated with the Green-MED diet, i.e., features with 6-month changes in abundance significantly associated with the Green-MED adherence score or significantly different across the groups . We also found that increased abundance of several genera from the Ruminococcaceae family was associated with weight loss, namely Ruminococcaceae UCG10 , Ruminococcaceae NK4A214 group , and Ruminococcaceae UCG3 . In addition, a reduction in Bifidobacterium and Dorea and an increase in genera from the Ruminococcaceae and Lachnospiraceae families were associated with a reduction in Framingham risk score . The leucine degradation pathway was positively correlated with Green-MED adherence . Reduction in the levels of the cysteine biosynthesis module was associated with reductions of body weight  and Framingham risk score , an observation that is consistent with a previous report demonstrating that high abundance of cysteine biosynthesis pathways is associated with unsuccessful weight loss [In a similar analysis performed on KEGG modules (assessed by shotgun sequencing), we identified significant associations of the Green-MED adherence score with 10 microbial metabolic pathways  and Ruminococcaceae UCG10 mediated the effect on FRS reduction (1.3%). Changes in the cysteine biosynthesis pathway were a prominent mediator of weight loss (14.2%) and FRS reduction (29.3%).As we hypothesized that the dietary interventions, through modulation of the gut microbiome, exert their effects on cardiometabolic risk, we next sought to quantify the mediation effect. To this aim, we estimated the causal mediation effect as proposed by Imai et al. , using tPrevotella and BCAA degradation pathway concomitant with the increment of plant components in MED diets, and reductions in the abundance of Bifidobacterium and BCAA biosynthesis pathways when comparing MED diets vs. the control diet. The MED and Green-MED diets improved cardiometabolic markers, including the Framingham risk score, body weight, blood pressure, HOMA-IR, and fasting plasma leptin. These beneficial changes in levels of cardiometabolic biomarkers were associated with a concurrent shift in the gut microbiome composition, estimated to mediate 12% of body-weight reduction and 18% of Framingham risk score reduction.In the current study, we demonstrate the effect of MED and Green-MED diets on the gut microbiome and determine the mediatory role of the microbiome in the associations between adherence to the Green-MED diet and subsequent improvement in markers of cardiometabolic risk. We showed that the Green-MED diet induced a prominent change in the gut microbiome composition, driven by the low-prevalent “non-core” fraction of the gut microbiome. This change was convergent by nature, with the taxonomic composition of the microbiome of individuals in the Green-MED becoming more similar to each other. The different diets were also characterized by distinct taxonomic and functional changes, inducing a gradual increase in the abundance of Our study has several limitations. The high proportion of male participants in the trial (88%) may limit the generalizability of our results to females. However, a previous report showed that, in western populations, gut microbiome composition is not associated with gender . We addrThe strengths of the study include the intense dietary instruction and multidisciplinary supervision, the simultaneous design, and the high retention rate.Although the function and composition of the gut microbiome have dynamic features, with some changes observed on a daily scale, most of this variation is person-specific . MoreoveThe major determinants differentiating the Green-MED diet from the MED diet are the supplementation of Mankai and green tea intake while reducing the consumption of red and processed meat.Mankai was previously established as a high-quality substitute source for animal protein in a controlled test meal, with blood concentrations of essential amino acids being similar after Mankai intake to that of well-established animal and plant protein sources. As an exception, Mankai intake induced only a minor increase in circulating BCAA levels . This obFurthermore, both Mankai and green tea were shown to be rich sources of polyphenols , 52, 53,Prevotella abundance, a genus previously associated with high fiber intake [Prevotella was shown to be a hallmark for the transition to a western lifestyle [Prevotella species, Prevotella copri, in host metabolism. It was recently suggested that the abundance of Prevotella copri, as an indication of the preexisting, diet-related biosynthetic capacity of the gut microbiome, potentially attenuates the protective effect of the Mediterranean diet on cardiometabolic disease risk [Prevotella copri abundance is associated with improvements in glucose metabolism and insulin sensitivity by the production of succinate [Prevotella copri abundance is associated with insulin resistance, presumably due to increased BCAA biosynthesis [Prevotella may not be beneficial or deleterious per se, but should be examined in light of other environmental and host-specific factors, requiring further investigations [Bifidobacterium with cardiometabolic disease risk has also been inconsistent in previous studies, with an increase in Bifidobacterium abundance linked to both successful [Bifidobacterium.While the Mankai plant is considered fiber-rich, with a fiber content of ~25% , the Grer intake  and veger intake , 56. Moruccinate , while aynthesis . Here, wigations . The assccessful  and unsuccessful  weight lBlautia [Bacteroides [The associations between dietary patterns, the gut microbiome, and cardiometabolic health have been extensively evaluated in recent years , 60, 61,Blautia  and enriteroides , adding MED diet enriched in plant components and with decreased red and processed meat consumption (Green-MED diet) has extensive effects on the composition and function of the host gut microbiome, with the latter partially mediating the beneficial effects of the diet on cardiometabolic health. In future studies, the diet-microbiome-host interplay should be further explored and could guide novel beneficial modifications in known dietary patterns.Additional file 1. Methods – Exclusion criteria, Physical activity protocol, Lifestyle sessions and motivation techniques, Blood sample analysis, 16s rRNA sequencing pipeline, Metagenomics analysis BoosterShot pipeline.Additional file 2: Table S1. Outline of the lifestyle interventions.Additional file 3: Table S2. Characteristics of the study population.Additional file 4: Figure S1. Flow Diagram of the DIRECT-PLUS trial.Additional file 5. Contains Figures S2 and S3.


Events associated with the COVID-19 pandemic, such as physical distancing, closure of community services, postponement of health appointments, and loss of employment can lead to social isolation, financial uncertainty, and interruption of antiretroviral adherence, resulting in additional health-related challenges (disability) experienced among adults living with chronic illness such as HIV. ‘Living strategies’ is a concept derived from the perspective of people living with HIV, defined as behaviors, attitudes and beliefs adopted by people living with HIV to help deal with disability associated with HIV and multi-morbidity. Our aim was to describe disability among adults living with HIV and self-care living strategies used during the COVID-19 pandemic.Adults living with HIV in Toronto, Ontario, Canada, including some with pre-pandemic HIV Disability Questionnaire (HDQ) data, completed a cross-sectional web-based survey between June-August 2020. The survey included the HDQ and questions about self-care living strategy use during the pandemic. We compared disability (HDQ) scores prior to versus during the pandemic using paired t-tests. We reported the proportion of participants who engaged in various living strategies at least ‘a few times a week’ or ‘everyday’ during the pandemic.Of the 63 respondents, 84% were men, median age 57 years, and 62% lived alone. During the pandemic the greatest disability severity was in the uncertainty : 16, 43) and mental-emotional  domains. Among the 51 participants with pre-pandemic data, HDQ severity scores were significantly greater (worse) during the pandemic (vs prior) in all domains. Greatest change from prior to during the pandemic was in the mental-emotional domain for presence , severity , and episodic nature  of disability. Most participants (>60%) reported engaging a ‘few times a week’ or ‘everyday’ in self-care strategies associated with maintaining sense of control and adopting positive attitudes and beliefs.People living with HIV reported high levels of uncertainty and mental-emotional health challenges during the pandemic. Disability increased across all HDQ dimensions, with the greatest worsening in the mental-emotional health domain. Results provide an understanding of disability and self-care strategy use during the COVID-19 pandemic. Adults with HIV can experience complex physical, mental and social health-related consequences of multimorbidity, known as disability –7. EventDue to measures implemented to slow the transmission of COVID-19, adults with HIV need to employ independent self-care living strategies in order to deal with uncertainty and the physical, social and mental health challenges of the pandemic . Living Our aim was to describe disability experienced by adults with HIV and self-care living strategies used during the COVID-19 pandemic. Our primary objective was to describe the dimensions of disability experienced among adults with HIV during the pandemic and identify change in disability compared with prior to the pandemic. Our secondary objectives were to describe self-care living strategies used; and examine associations between disability and the frequency of living strategies use; and to identify changes in mental health and mastery compared with prior to the pandemic.We conducted a cross-sectional web-based survey using EQUATOR guidelines for web-based surveys , 20. ThiIn response to the World Health Organization’s declared outbreak of the novel coronavirus disease (COVID-19) the province of Ontario, Canada declared a state of emergency on March 17, 2020. To slow the transmission of SARS-CoV-2, the City of Toronto closed all shared, public or private recreational amenities and non-essential businesses, including community service organizations and health and fitness centres, and issued a stay-at-home order.Individuals were eligible if they self-identified as an adult ≥ 18 years living with HIV living in Toronto, Canada.We emailed adults with HIV who participated in a community-based exercise (CBE) intervention study  and agreThe survey included questionnaires capturing disability, self-care living strategies use, contextual factors , and COVID-19, health and demographic characteristics of participants. For participants recruited from the exercise study, we used HDQ data collected during that study (prior to the pandemic) to assess change in disability.We administered the HIV Disability Questionnaire (HDQ), to capture the presence, severity and episodic nature of disability experienced by adults aging with HIV across six domains including challenges with physical, mental-emotional, and cognitive health, day-to-day activities, social inclusion and uncertainty or worrying about the future , 25. TheSelf-Care Living Strategies: We administered a Living Strategies Questionnaire, adapted from categories in the Episodic Disability Framework and previously administered with adults with HIV in Canada . The 51-We administered a demographic and COVID-19 questionnaire to capture personal characteristics , HIV-related information , and impact of the COVID-19 pandemic on access to health care services, supports, experiences and lifestyle changes.Mental Health: The Patient Health Questionnaire (PHQ8) is an 8-item measure of depression severity  . We calcWe calculated medians and interquartile ranges (IQR) for HDQ presence, severity and episodic domain scores from all survey respondents. For participants recruited from the exercise study, we used paired t-tests to determine if their disability changed prior to versus during the pandemic. We used each participant’s median pre-pandemic HDQ score across all possible 12-time points in our previously 22 month exercise study  as the pWe reported the frequency (%) of participants who engaged in each strategy ‘a few times a week’ or ‘everyday’ and change in strategy use (increase / decrease / no change). We conceptualized 37 of the items as having positive influences on health, 8 having negative influences on health, and 6 as having either a positive or a negative influence on health, dependent on the individual and context .adjα = 1.6 × 10−4) to report the most significant correlations. We chose the severity scale of the HDQ as this scale possesses most measurement properties.We calculated median (IQR) scores for the PHQ8 (score range: 0–24) of which scores of ≥ 5, ≥10, and ≥ 20 indicate mild, moderate, and severe depression, respectively . We calcWe recruited participants and administered the web-based survey between June 9 and August 12, 2020. Of 114 exercise study participants emailed to participate in the study, 60 (53%) clicked on the survey link (view rate), 59/60 (98%) consented to participate and initiated the questionnaires (participation rate), and 51/59 (86%) consented and completed the questionnaires (completion rate) ; and 12 The majority of participants were men (84%), White (65%), single (54%), and living alone (62%) with a median age 57 years . No participants reported testing positive for COVID-19.Of the 61 (97%) participants who were receiving care from an HIV doctor or clinic, 71% received care remotely (telephone or online) during the COVID-19 pandemic .Sixteen (25%) participants reported working during the pandemic. Among those not working, most  were not working prior to the COVID-19 pandemic. During the pandemic, participants reported boredom (79%), increased anxiety (75%) and depression (54%), and changes to sleep patterns (59%). Thirty-three (52%) reported accessing emotional or social support from friends, family, partners, or counselors .HDQ scores are presented in Change in Disability (prior to versus during the pandemic)Among the 51 participants with pre-pandemic HDQ scores, mean HDQ severity scores were significantly higher (greater disability) during compared to prior to the pandemic, for all domains. The largest increase in disability severity was in the mental-emotional domain  ; Table 3The majority of participants (> 60%) reported engaging in positive living strategies a ‘few times a week’ or ‘everyday’ pertaining to maintaining a sense of control  and adopting positive attitudes and beliefs (represented by 5 different strategies related to positive outlook) . Nine stAll domains of the HDQ except the physical domain were significantly associated (Spearman rho | ≥ 0.46|) with frequency of use of eight living strategies. Maintaining a sense of control , maintaining a good balance of activity in life (Spearman rho | 0.51|), and trying to stick to daily structure or routine (Spearman rho | 0.46|), were associated with lower HDQ (improved) severity scores for mental-emotional health challenges. Living strategies pertaining to attitudes and beliefs , accepting and valuing who I am (Spearman rho | 0.47 to 0.52|), positive outlook on life (Spearman rho | 0.46 to 0.54|), choosing to believe one can overcome any challenges (Spearman rho | 0.47 to 0.53|), were associated with lower (improved) HDQ severity scores for challenges with mental-emotional and cognitive health, uncertainty, day-to-day activities, and social inclusion, and feeling hopeless (Spearman rho | 0.46 to 0.62|) was associated with greater (worse) HDQ severity scores for challenges with mental-emotional and cognitive health, and social inclusion .Using a previously validated disability questionnaire with adults with HIV administered prior to the pandemic, we found that self-reported disability severity increased across all dimensions during the COVID-19 pandemic among adults with HIV, with the largest increase found in the presence, severity, and episodic components of mental-emotional health. This finding was supported by the significant increase in mean PHQ8 scores and 39% reporting a higher category of depression during the pandemic compared to prior  and 2. SUncertainty followed by mental-emotional health challenges were the most severe dimensions of disability experienced during the pandemic . These dIn addition to the greater risk and poorer outcomes of COVID-19 that may occur among people with HIV –47, the The greatest change in disability was in the mental-emotional health domain, where participants experienced the largest increases in presence, severity and episodic scores of disability compared with pre-pandemic scores. Physical distancing measures and public health restrictions during the COVID-19 pandemic have been linked to loneliness and social isolation among adults with HIV , which mThe majority of participants reported sustained use of positive living strategies during the pandemic with the exception of positive social interaction strategies and negative strategies (e.g. isolating self) that increased during the pandemic . AnotherTo our knowledge this is the first study to explore the nature, extent and impact of disability experienced by adults with HIV prior to and during the COVID-19 pandemic, and to specifically explore the impact of the COVID-19 pandemic on health outcomes and living strategies use for people with chronic illness. This work provides insights to the health challenges experienced by adults with HIV who may be living with the added complexity of concurrent health conditions –53, and We administered study questionnaires in-between a first (Spring 2020) and second  wave of the COVID-19 pandemic in Toronto, Ontario. With COVID-19 restrictions continuing with third and fourth waves in Spring and Summer 2021, the sustained and potential cumulative impact of COVID-19 on disability dimensions are unclear. The clinical importance of HDQ change scores should be interpreted with caution. Pre-pandemic measures were collected from 2016–2018, hence it is unknown to what extent changes may be attributed to other contextual factors, such aging over time.While a strength of our study was building on data collected pre-pandemic  with an existing cohort of adults living with HIV who participated in an earlier exercise intervention study, our study is not without limitations. We assessed disability and living strategies use cross-sectionally during the pandemic, as distinct constructs and cannot infer causation between the pandemic and disability and living strategies use. Due to our small sample size, our analysis was exploratory. Furthermore, the clinical importance of HDQ change scores, particularly given the episodic nature of disability in the context of the COVID-19 pandemic is unclear. Nevertheless, our inclusion of supplemental measures of mental health (PHQ8) support the direction of change in disability this study. Given the majority of the sample were from a previous study examining the impact of community-based exercise among adults living with HIV, primarily including White men living in an urban setting, results may not be representative of the larger HIV population. Men and women can experience disability differently pertaining to hospitalization, parental roles, fatigue, mental health, and social inclusion –58. FutuParticipants with HIV reported high levels of uncertainty and mental health challenges during the pandemic. All six dimensions of disability increased during the pandemic, the largest increase was the mental-emotional health domain. Strategies involving maintaining a sense of control, and positive attitudes and beliefs were associated with lower disability during the pandemic. Results help to provide an understanding of disability and self-care living strategy use among adults living with HIV during the COVID-19 pandemic.Supplement 1Supplement 2Supplement 3Supplement 4


Australia has one of the world’s highest breast cancer incidences. For most women who are not classified as at high risk, eligibility and frequency of breast cancer screening in Australia is based solely on their age. Breast cancer risk models can help to optimise early detection and management of breast cancer. We evaluated six commonly used models over 15 years follow-up using an Australian community-based cohort of 7608 women aged 50–65 years. The BOADICEA and IBIS models best discriminated women who were at higher risk of developing breast cancer from those at lower risk, but no model apart from BOADICEA accurately predicted absolute risk across the risk spectrum. The BOADICEA model could be of clinical use for women of similar demography. p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk . The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum. Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models . 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50–65 years and unaffected at commencement of follow-up two (conducted in 2003–2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group  and family history of breast cancer. C-statistics were higher for BOADICEA  0.56–0.62) and IBIS  than the other models ( Breast cancer is the most common cancer and cause of cancer death for women worldwide, with approximately 2.3 million incident cases in 2020, and carries a substantial burden of disease ,2. AustrBreast cancer risk models are currently used in familial cancer clinics by genetic counsellors to stratify women and inform risk-tailored advice on the optimal age range, frequency, and modality of screening for those at high risk ,4. For mThe Melbourne Collaborative Cohort Study (MCCS) is a prospective cohort that includes 24,469 women from Melbourne, Australia, aged between 27 and 76 years (99% were 40–69 years) at recruitment . All parWe used the latest versions  of the risk models: BOADICEA version 5.0.0, using updated Australian incidence rates ; IBIS ve2). History of hyperplasia or benign breast disease were not available. As our aim was to compare models using solely family history and lifestyle risk factor information, results from germline genetic testing for pathogenic variants in BRCA1 and BRCA2 (or susceptibility genes) and mammographic density were not included in our analyses due to lack of availability of these data for most women. At follow-up 2, MCCS participants completed a questionnaire that asked about their demographic characteristics and lifestyle-related factors, including, for example, age, alcohol intake, age at menarche, parity, number of sisters, brothers, and children, age at first birth, menopausal status, and use of the oral contraceptive pill and menopausal hormone therapy. Summary family history data on affected relatives were obtained from questionnaires at follow-up 2 (first-degree relatives) and follow-up 1 (second-degree relatives). Data from the most recent questionnaires were used and supplemented with that from older questionnaires if unavailable. To reconstruct pedigrees, the following assumptions were made about the year of birth (YOB) of participants’ relatives: mothers and aunts (25 years before the participant’s YOB), grandmothers (50 years before the participant’s YOB), sisters (participant’s YOB), and daughters (25 years after the participant’s YOB). Missing ages for affected and unaffected mothers, aunts, and grandmothers were imputed to 70 years, whereas for sisters, they were imputed to the youngest of the participants’ age at follow-up 2 or aged 70 years . Weight at follow-up 2 was measured to the nearest 100 g using a digital electronic scale, while height was measured at baseline to the nearest 1 mm, using a stadiometer. Body mass index (BMI) was defined as weight (kg) divided by height squared  during follow-up to 1 March 2019. Follow-up began at follow-up 2 attendance and ended at: (i) diagnosis of invasive breast cancer, (ii) follow-up time reaching 15 years, (iii) age 80 years (maximum age for estimating risk in BOADICEA), or (iv) censor date of 1 March 2019, whichever came first. Expected cancer counts for the defined cohort were estimated for each model by summing the predicted risks over all eligible participants. Deaths from causes other than breast cancer were included as competing risks for all models except for two, BOADICEA and BRCAPRO-BCRAT, because they do not currently have an option to account for competing causes of death.We compared the performance of the models with up to 15-year risk in terms of discrimination and calibration. Calibration was assessed by comparing the number of expected cases (E) within the cohort with the number observed (O). Model discrimination was assessed using a concordance statistic (C-statistic)  and plotp-value < 0.05 indicates miscalibration [The assessment of model calibration at the individual level was graphically represented from the model’s goodness of fit using the calibration belt routine. This method uses likelihood-based tests on a data-driven forward selection of polynomial regression models to assess the goodness of fit of the 15-year risk estimates from the six models, where a ibration . Calibra2; 23% had a first- or second-degree family history of breast cancer . C-statistics did not vary significantly across different age subgroups, whereas C-statistics from all models (except for BCRAT) were slightly higher for women who had a family history of breast cancer than for those who did not have any affected relatives. The overall discrimination of 15-year breast cancer risk (measured by C-statistic) across the six models ranged between 0.51 and 0.59 . IBIS anp-value < 0.03), where they generally underpredicted risk at the low end of risk and overpredicted risk at high end of risk  , particu of risk . p-value < 0.02), whilst iCARE-lit had higher discrimination at 5-year and 10-year risk compared with 15-year risk  had the widest range of predicted risk distribution. The exceptions to this wider predicted risk distribution by pedigree-based models were the two BRCAPRO models, likely because they only allow for the effects of ase risk . InteresA previous study that analysed a combined Australian and North American cohort reported higher 10-year C-statistics for BCRAT (0.64), BRCAPRO (0.62), IBIS (0.66), and BOADICEA (0.65) . This maIBIS and BOADICEA consistently outperformed other risk models in discrimination, including in family registries that encompass participants from Australia, USA, and Canada . We showWe have previously demonstrated a doubling of discriminatory accuracy for IBIS and BOADICEA (C-statistic from 0.56–0.57 to 0.62) with the addition of a polygenic risk score to predictors examined  using a subsample of the MCCS . AdditioWe evaluated six breast cancer risk models within an Australian average-risk cohort of women aged 50 to 65 years and found that IBIS and BOADICEA had the highest discriminatory accuracy and that their discriminatory accuracy remained consistent over time. However, apart from BOADICEA, no model was well-calibrated across the risk spectrum. Breast cancer risk models can help strengthen preventive efforts such as screening programs for average-risk Australian women via tailored surveillance advice. Models with lifestyle-related factors and family history will further benefit from the inclusion of information on genetics and mammographic density.