Interleukin-28B polymorphisms, IP-10, viral load and age predict the outcome of therapy in genotype 1 hepatitis C virus under real-life conditions

Background and Aims: IL28B polymorphisms, interferon (IFN)-gamma inducible protein-10 (IP-10) levels and the homeostasis model assessment of insulin resistance (HOMA-IR) score have been reported to predict rapid (RVR) and sustained (SVR) virological response in chronic hepatitis C (CHC), but it is not known whether these factors represent independent, clinically useful predictors. The aim of the study was to assess factors (including IL28B polymorphisms, IP-10 levels and HOMA-IR score) independently predicting response to therapy in CHC under real life conditions.Methods: Multivariate analysis of factors predicting RVR and SVR in 280 consecutive, treatment-naive CHC patients treated with pegylated IFN alpha and ribavirin in a prospective multicenter study.Results: Independent predictors of RVR were HCV RNA < 400,000 IU/ml (OR11.37; 95% CI 3.03-42.6), rs12980275 AA (vs. AG/GG) (OR 7.09; 1.97-25.56) and IP-10 (OR 0.04; 0.003-0.56) in HCV genotype 1 patients and lower baseline γ-glutamyl-transferase levels (OR = 0.02; 0.0009-0.31) in HCV genotype 3 patients. Independent predictors of SVR were rs12980275 AA (OR 9.68; 3.44-27.18), age < 40 yrs (OR = 4.79; 1.50-15.34) and HCV RNA < 400,000 IU/ml (OR 2.74; 1.03-7.27) in HCV genotype 1 patients and rs12980275 AA (OR = 6.26; 1.98-19.74) and age < 40 yrs (OR 5.37; 1.54-18.75) in the 88 HCV genotype 1 patients without a RVR. RVR was by itself predictive of SVR in HCV genotype 1 patients (32 of 33, 97%; OR 33.0; 4.06-268.32) and the only independent predictor of SVR in HCV genotype 2 (OR 9.0, 1.72-46.99; p=0.009) or 3 patients (OR 7.8, 1.43-42.67; p=0.01).Conclusions: In HCV genotype 1 patients, IL28B polymorphisms, HCV RNA load and IP-10 independently predict RVR. The combination of IL28B polymorphisms, HCV RNA level and age may yield more accurate pretreatment prediction of SVR. HOMA-IR score is not associated with viral response.

Variants in MTNR1B influence fasting glucose levels.

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.

Metabolically healthy obesity: different prevalences using different criteria.

To estimate the prevalence of metabolically healthy obesity (MHO) according to different definitions. Population-based sample of 2803 women and 2557 men participated in the study. Metabolic abnormalities were defined using six sets of criteria, which included different combinations of the following: waist; blood pressure; total, high-density lipoprotein or low-density lipoprotein-cholesterol; triglycerides; fasting glucose; homeostasis model assessment; high-sensitivity C-reactive protein; personal history of cardiovascular, respiratory or metabolic diseases. For each set, prevalence of MHO was assessed for body mass index (BMI); waist or percent body fat. Among obese (BMI 30 kg/m(2)) participants, prevalence of MHO ranged between 3.3 and 32.1% in men and between 11.4 and 43.3% in women according to the criteria used. Using abdominal obesity, prevalence of MHO ranged between 5.7 and 36.7% (men) and 12.2 and 57.5% (women). Using percent body fat led to a prevalence of MHO ranging between 6.4 and 43.1% (men) and 12.0 and 55.5% (women). MHO participants had a lower odd of presenting a family history of type 2 diabetes. After multivariate adjustment, the odds of presenting with MHO decreased with increasing age, whereas no relationship was found with gender, alcohol consumption or tobacco smoking using most sets of criteria. Physical activity was positively related, whereas increased waist was negatively related with BMI-defined MHO. MHO prevalence varies considerably according to the criteria used, underscoring the need for a standard definition of this metabolic entity. Physical activity increases the likelihood of presenting with MHO, and MHO is associated with a lower prevalence of family history of type 2 diabetes.

Association between the A-2518G polymorphism in the monocyte chemoattractant protein-1 gene and insulin resistance and Type 2 diabetes mellitus.

AIMS/HYPOTHESIS: The molecular mechanisms of obesity-related insulin resistance are incompletely understood. Macrophages accumulate in adipose tissue of obese individuals. In obesity, monocyte chemoattractant protein-1 (MCP-1), a key chemokine in the process of macrophage accumulation, is overexpressed in adipose tissue. MCP-1 is an insulin-responsive gene that continues to respond to exogenous insulin in insulin-resistant adipocytes and mice. MCP-1 decreases insulin-stimulated glucose uptake into adipocytes. The A-2518G polymorphism in the distal regulatory region of MCP-1 may regulate gene expression. The aim of this study was to investigate the impact of this gene polymorphism on insulin resistance. METHODS: We genotyped the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort ( n=3307). Insulin resistance, estimated by homeostasis model assessment, and Type 2 diabetes were diagnosed in 803 and 635 patients respectively. RESULTS: Univariate analysis revealed that plasma MCP-1 levels were significantly and positively correlated with WHR ( p=0.011), insulin resistance ( p=0.0097) and diabetes ( p<0.0001). Presence of the MCP-1 G-2518 allele was associated with decreased plasma MCP-1 ( p=0.017), a decreased prevalence of insulin resistance (odds ratio [OR]=0.82, 95% CI: 0.70-0.97, p=0.021) and a decreased prevalence of diabetes (OR=0.80, 95% CI: 0.67-0.96, p=0.014). In multivariate analysis, the G allele retained statistical significance as a negative predictor of insulin resistance (OR=0.78, 95% CI: 0.65-0.93, p=0.0060) and diabetes (OR=0.80, 95% CI: 0.66-0.96, p=0.018). CONCLUSIONS/INTERPRETATION: In a large cohort of Caucasians, the MCP-1 G-2518 gene variant was significantly and negatively correlated with plasma MCP-1 levels and the prevalence of insulin resistance and Type 2 diabetes. These results add to recent evidence supporting a role for MCP-1 in pathologies associated with hyperinsulinaemia.

IL28B polymorphisms, IP-10 and viral load predict virological response to therapy in chronic hepatitis C.

Aliment Pharmacol Ther 2011; 33: 1162-1172 SUMMARY: Background  Hepatitis C virus (HCV) is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma and the identification of the predictors of response to antiviral therapy is an important clinical issue. Aim  To determine the independent contribution of factors including IL28B polymorphisms, IFN-gamma inducible protein-10 (IP-10) levels and the homeostasis model assessment of insulin resistance (HOMA-IR) score in predicting response to therapy in chronic hepatitis C (CHC). Methods  Multivariate analysis of factors predicting rapid (RVR) and sustained (SVR) virological response in 280 consecutive, treatment-naive CHC patients treated with peginterferon alpha and ribavirin in a prospective multicentre study. Results  Independent predictors of RVR were HCV RNA <400 000 IU/mL (OR 11.37; 95% CI 3.03-42.6), rs12980275 AA (OR 7.09; 1.97-25.56) and IP-10 (OR 0.04; 0.003-0.56) in HCV genotype 1 patients and lower baseline γ-glutamyl-transferase levels (OR = 0.02; 0.0009-0.31) in HCV genotype 3 patients. Independent predictors of SVR were rs12980275 AA (OR 9.68; 3.44-27.18), age <40 years (OR = 4.79; 1.50-15.34) and HCV RNA <400 000 IU/mL (OR 2.74; 1.03-7.27) in HCV genotype 1 patients and rs12980275 AA (OR = 6.26; 1.98-19.74) and age <40 years (OR 5.37; 1.54-18.75) in the 88 HCV genotype 1 patients without a RVR. RVR was by itself predictive of SVR in HCV genotype 1 patients (OR 33.0; 4.06-268.32) and the only independent predictor of SVR in HCV genotype 2 (OR 9.0, 1.72-46.99) or genotype 3 patients (OR 7.8, 1.43-42.67). Conclusions  In HCV genotype 1 patients, IL28B polymorphisms, HCV RNA load and IP-10 independently predict RVR. The combination of IL28B polymorphisms, HCV RNA level and age may yield more accurate pre-treatment prediction of SVR. HOMA-IR score is not associated with viral response.

Alcohol drinking, the metabolic syndrome and diabetes in a population with high mean alcohol consumption.

AIMS: To investigate the relationship of alcohol consumption with the metabolic syndrome and diabetes in a population-based study with high mean alcohol consumption. Few data exist on these conditions in high-risk drinkers. METHODS: In 6172 adults aged 35-75 years, alcohol consumption was categorized as 0, 1-6, 7-13, 14-20, 21-27, 28-34 and ≥ 35 drinks/week or as non-drinkers (0), low-risk (1-13), medium-to-high-risk (14-34) and very-high-risk (≥ 35) drinkers. Alcohol consumption was objectively confirmed by biochemical tests. In multivariate analysis, we assessed the relationship of alcohol consumption with adjusted prevalence of the metabolic syndrome, diabetes and insulin resistance, determined with the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Seventy-three per cent of participants consumed alcohol, 16% were medium-to-high-risk drinkers and 2% very-high-risk drinkers. In multivariate analysis, the prevalence of the metabolic syndrome, diabetes and mean HOMA-IR decreased with low-risk drinking and increased with high-risk drinking. Adjusted prevalence of the metabolic syndrome was 24% in non-drinkers, 19% in low-risk (P<0.001 vs. non-drinkers), 20% in medium-to-high-risk and 29% in very-high-risk drinkers (P=0.005 vs. low-risk). Adjusted prevalence of diabetes was 6.0% in non-drinkers, 3.6% in low-risk (P<0.001 vs. non-drinkers), 3.8% in medium-to-high-risk and 6.7% in very-high-risk drinkers (P=0.046 vs. low-risk). Adjusted HOMA-IR was 2.47 in non-drinkers, 2.14 in low-risk (P<0.001 vs. non-drinkers), 2.27 in medium-to-high-risk and 2.53 in very-high-risk drinkers (P=0.04 vs. low-risk). These relationships did not differ according to beverage types. CONCLUSIONS: Alcohol has a U-shaped relationship with the metabolic syndrome, diabetes and HOMA-IR, without differences between beverage types.

Intrahepatic mRNA levels of SOCS1 and SOCS3 are associated with cirrhosis but do not predict virological response to therapy in chronic hepatitis C.

BACKGROUND: Antiviral treatment of chronic hepatitis C is not invariably successful, costly and associated with serious side-effects, and therefore should be indicated only when the chances of benefitting patients exceed the potential risks. The suppressor of cytokine signalling (SOCS) family members have been suggested to affect the rate of virological response to therapy, but the published evidence is conflicting. METHODS: We measured the intrahepatic SOCS1, SOCS3 and SOCS7 mRNA levels in 107 chronic hepatitis C patients and assessed their clinical and histological correlates with the virological response to therapy and with some factors known for affecting treatment outcome. RESULTS: By multivariate analysis, SOCS1, SOCS3 and SOCS7 mRNA levels were not associated with rapid or sustained virological response. Similarly, no association was found between the levels of any intrahepatic SOCS mRNA and those of the homeostasis model assessment of insulin resistance. Conversely, SOCS1 (OR 2.185, 95% CI 1.223-3.906, P=0.0083) and SOCS3 (OR 40.601, 95% CI 2.357-699.25, P=0.0108) mRNA level (but not SOCS7), together with age (OR 1.156, 95% CI 1.049-1.275, P=0.0036), were independently associated with cirrhosis. CONCLUSIONS: Intrahepatic SOCS1, SOCS3 and SOCS7 mRNA levels do not predict virological response to therapy in chronic hepatitis C. The association between SOCS1, SOCS3 and cirrhosis warrants further study.

Differences in low-grade chronic inflammation and insulin resistance in women with previous gestational diabetes mellitus and women with polycystic ovary syndrome.

BACKGROUND: Polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) are both characterized by an increase in insulin resistance. Our goal in the present study was to measure insulin resistance (as estimated by homeostasis model assessment, sex hormone-binding globulin (SHBG) and adiponectin concentrations) and parameters of low-grade inflammation in non-diabetic, non-hyperandrogenic ovulatory women with previous GDM (pGDM) and in non-diabetic women with classic PCOS, characterized by hyperandrogenism and oligo/anovulation. PATIENTS AND DESIGN: We evaluated 20 women with PCOS, 18 women with pGDM and 19 controls, all matched according to body mass index (BMI). Fasting blood samples were drawn in all women 3-6 days after spontaneous or dydrogesterone-induced withdrawal bleeding. Body fat distribution was assessed using dual-energy X-ray absorptiometry in all women. RESULTS: After adjusting for age and percent body fat, measures of insulin resistance such as SHBG and adiponectin concentrations were decreased and central obesity was increased in women with PCOS and pGDM compared with controls (all p < 0.05). Parameters of low-grade inflammation such as serum tumor necrosis factor-alpha and highly sensitive C-reactive protein concentrations, white blood cell and neutrophil count were increased only in women with PCOS compared with BMI-matched controls (all p < 0.05). CONCLUSIONS: Certain markers of insulin resistance are increased in both women with PCOS and women with pGDM, while low-grade inflammation is increased only in PCOS. PCOS and GDM might represent specific phenotypes of one disease entity with an increased risk of cardiovascular disease, whereby women with PCOS demonstrate an augmented cardiovascular risk profile.

Reduced cardiorespiratory fitness, low physical activity and an urban environment are independently associated with increased cardiovascular risk in children.

AIMS/HYPOTHESIS: To assist in the development of preventive strategies, we studied whether the neighbourhood environment or modifiable behavioural parameters, including cardiorespiratory fitness (CRF) and physical activity (PA), are independently associated with obesity and metabolic risk markers in children. METHODS: We carried out a cross-sectional analysis of 502 randomly selected first and fifth grade urban and rural Swiss schoolchildren with regard to CRF, PA and the neighbourhood (rural vs urban) environment. Outcome measures included BMI, sum of four skinfold thicknesses, homeostasis model assessment of insulin resistance (HOMA-IR) and a standardised clustered metabolic risk score. RESULTS: CRF and PA (especially total PA, but also the time spent engaged in light and in moderate and vigorous intensity PA) were inversely associated with measures of obesity, HOMA-IR and the metabolic risk score, independently of each other, and of sociodemographic and nutritional parameters, media use, sleep duration, BMI and the neighbourhood environment (all p < 0.05). Children living in a rural environment were more physically active and had higher CRF values and reduced HOMA-IR and metabolic risk scores compared with children living in an urban environment (all p < 0.05). These differences in cardiovascular risk factors persisted after adjustment for CRF, total PA and BMI. CONCLUSIONS/INTERPRETATION: Reduced CRF, low PA and an urban environment are independently associated with an increase in metabolic risk markers in children.

Serum Vitamin D Concentrations Are Not Associated with Insulin Resistance in Swiss Adults.

BACKGROUND: Low vitamin D status has been associated with an increased risk of developing type 2 diabetes and insulin resistance (IR), although this has been recently questioned. OBJECTIVE: We examined the association between serum vitamin D metabolites and incident IR. METHODS: This was a prospective, population-based study derived from the CoLaus (Cohorte Lausannoise) study including 3856 participants (aged 51.2 ± 10.4 y; 2217 women) free from diabetes or IR at baseline. IR was defined as a homeostasis model assessment (HOMA) index >2.6. Fasting plasma insulin and glucose were measured at baseline and at follow-up to calculate the HOMA index. The association of vitamin D metabolites with incident IR was analyzed by logistic regression, and the results were expressed for each independent variable as ORs and 95% CIs. RESULTS: During the 5.5-y follow-up, 649 (16.9%) incident cases of IR were identified. Participants who developed IR had lower baseline serum concentrations of 25-hydroxyvitamin D3 [25(OH)D3 (25-hydroxycholecalciferol); 45.9 ± 22.8 vs. 49.9 ± 22.6 nmol/L; P < 0.001], total 25(OH)D3 (25(OH)D3 + epi-25-hydroxyvitamin D3 [3-epi-25(OH)D3]; 49.1 ± 24.3 vs. 53.3 ± 24.1 nmol/L; P < 0.001), and 3-epi-25(OH)D3 (4.2 ± 2.9 vs. 4.3 ± 2.5 nmol/L; P = 0.01) but a higher 3-epi- to total 25(OH)D3 ratio (0.09 ± 0.05 vs. 0.08 ± 0.04; P = 0.007). Multivariable analysis adjusting for month of sampling, age, and sex showed an inverse association between 25(OH)D3 and the likelihood of developing IR [ORs (95% CIs): 0.86 (0.68, 1.09), 0.60 (0.46, 0.78), and 0.57 (0.43, 0.75) for the second, third, and fourth quartiles compared with the first 25(OH)D3 quartile; P-trend < 0.001]. Similar associations were found between total 25(OH)D3 and incident IR. There was no significant association between 3-epi-25(OH)D3 and IR, yet a positive association was observed between the 3-epi- to total 25(OH)D3 ratio and incident IR. Further adjustment for body mass index, sedentary status, and smoking attenuated the association between 25(OH)D3, total 25(OH)D3, and the 3-epi- to total 25(OH)D3 ratio and the likelihood of developing IR. CONCLUSION: In the CoLaus study in healthy adults, the risk of incident IR is not associated with serum concentrations of 25(OH)D3 and total 25(OH)D3.

Short-term HIIT and Fatmax training increase aerobic and metabolic fitness in men with class II and III obesity.

OBJECTIVE: To compare the effects of two different 2-week-long training modalities [continuous at the intensity eliciting the maximal fat oxidation (Fatmax ) versus high-intensity interval training (HIIT)] in men with class II and III obesity. METHODS: Nineteen men with obesity (BMI ≥ 35 kg(.) m(-2) ) were assigned to Fatmax group (GFatmax ) or to HIIT group (GHIIT ). Both groups performed eight cycling sessions matched for mechanical work. Aerobic fitness and fat oxidation rates (FORs) during exercise were assessed prior and following the training. Blood samples were drawn to determine hormones and plasma metabolites levels. Insulin resistance was assessed by the homeostasis model assessment of insulin resistance (HOMA2-IR). RESULTS: Aerobic fitness and FORs during exercise were significantly increased in both groups after training (P ≤ 0.001). HOMA2-IR was significantly reduced only for GFatmax (P ≤ 0.001). Resting non-esterified fatty acids (NEFA) and insulin decreased significantly only in GFatmax (P ≤ 0.002). CONCLUSIONS: Two weeks of HIIT and Fatmax training are effective for the improvement of aerobic fitness and FORs during exercise in these classes of obesity. The decreased levels of resting NEFA only in GFatmax may be involved in the decreased insulin resistance only in this group.

Serum insulin and inflammatory markers in overweight individuals with and without dyslipidemia.

CONTEXT: The worldwide epidemic of overweight and obesity is setting the scene for a new wave of premature cardiovascular disease. OBJECTIVE: The objective of this study was to define relationships between dyslipidemia and other metabolic abnormalities in overweight subjects. DESIGN: This study included comparison of overweight subjects with and without dyslipidemia. SETTING: The setting was an institutional practice. PATIENTS: Dyslipidemic subjects (n = 715) had plasma triglyceride greater than or equal to the 75th percentile in combination with high-density lipoprotein cholesterol (HDL-C) less than or equal to the 25th percentile. Unrelated, normolipidemic controls (n = 1073) had HDL-C higher than the median and triglyceride lower than the median. It was a requirement for the control subjects to have a body mass index (BMI) greater than 25 kg/m(2). MAIN OUTCOME MEASURES: The main outcome measures included BMI, inflammatory markers, adipokines, blood pressure, and fasting plasma glucose and insulin. RESULTS: The mean BMI in the subjects and controls was 28.7 and 28.2 kg/m(2), respectively. Subjects had higher levels of plasma high-sensitivity C-reactive protein (3.0 vs. 2.0 mg/liter; P < 0.001), lower levels of adiponectin (4.7 vs. 6.6 mg/liter; P < 0.001), and, after adjustment for age, BMI, gender, smoking, statin, and beta-blocker use, higher systolic (P = 0.001) and diastolic (P = 0.05) blood pressures. Fasting plasma glucose, insulin, and homeostasis model of assessment-insulin resistance were all significantly higher in subjects than controls (P < 0.0001). CONCLUSIONS: Identification of people solely on the basis of an elevated plasma triglyceride and a low HDL-C uncovers an overweight group of people who have a generalized metabolic disorder. In contrast, overweight people with normal plasma lipids have normal glucose and insulin metabolism, low levels of inflammatory markers, and normal blood pressure. Such people may thus be at relatively low risk of developing diabetes and cardiovascular disease despite being overweight.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

The association between inflammatory biomarkers and metabolically healthy obesity depends of the definition used.

BACKGROUND/OBJECTIVES: To assess the distribution of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) according to the different definitions of metabolically healthy obesity (MHO). SUBJECTS/METHODS: A total of 881 obese (body mass index (BMI) > or =30 kg/m2) subjects derived from the population-based CoLaus Study participated in this study. MHO was defined using six sets of criteria including different combinations of waist, blood pressure, total high-density lipoprotein cholesterol or low-density lipoprotein -cholesterol, triglycerides, fasting glucose, homeostasis model, high-sensitivity CRP, and personal history of cardiovascular, respiratory or metabolic diseases. IL-1β, IL-6 and TNF-α were assessed by multiplexed flow cytometric assay. CRP was assessed by immunoassay. RESULTS: On bivariate analysis some, but not all, definitions of MHO led to significantly lower levels of IL-6, TNF-α and CRP compared with non-MH obese subjects. Most of these differences became nonsignificant after multivariate analysis. An posteriori analysis showed a statistical power between 9 and 79%, depending on the inflammatory biomarker and MHO definition considered. Further increasing sample size to overweight+obese individuals (BMI > or =25 kg/m2, n=2917) showed metabolically healthy status to be significantly associated with lower levels of CRP, while no association was found for IL-1β. Significantly lower IL-6 and TNF-α levels were also found with some but not all MHO definitions, the differences in IL-6 becoming nonsignificant after adjusting for abdominal obesity or percent body fat. CONCLUSIONS: MHO individuals present with decreased levels of CRP and, depending on MHO definition, also with decreased levels in IL-6 and TNF-α. Conversely, no association with IL-1β levels was found.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions.

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.