PEOPLERoberto Melotti

de en it

Roberto Melotti

Senior Researcher
Institute for Biomedicine

T +39 0471 055 511

roberto.melotti@eurac.edu

https://orcid.org/0000-0003-4115-317X

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About

Roberto Melotti is researcher in Biomedical Statistics and a senior member of the Biostatistics & Epidemiology group at the Institute for Biomedicine.

After graduating in Statistical and Economical Sciences from the University of Bologna in 2001, he attained an MSc in Epidemiology from the University of Verona and a PhD in Health Sciences from the University of Bristol (UK). Since training on the job in Verona, he has taught statistics and epidemiological methods to both undergraduate and postgraduate students over the years. In Bristol he spent more than 5 years specialising in supporting clinical research and focusing on multidisciplinary health research. Hands on the Avon Longitudinal Study of Parents and Children (ALSPAC) resource, one of the richest birth-cohort studies in the world, he gained new methodological knowledge and a broader perspective on Biomedical Sciences. Since 2012 he has been actively collaborating with clinicians in South Tyrol and leveraging the Cooperative Health Research in South Tyrol (CHRIS //chris.eurac.edu/it) study towards precision health and generating new knowledge, particularly focusing on Public Health and Clinical Epidemiology.

Main research interests
Biostatistics and Methodology. Etiological models of determinants of health outcome and disease with applications mainly in large population-based cohort and observational clinical studies. Latent variable modelling for exploratory and confirmatory deep phenotyping. Statistical methods for missing data and attrition. Repeated measures and longitudinal data designs and applications. Survey weighting to control for selection bias. Survey design and questionnaire development and implementation. Machine learning applications to prediction models and variable importance ranking.

Public Health topics. Health inequalities. Substance use. Movement disorders and neuro-psychiatry-psychological traits. COVID-19. Nephrology.

Links

Scholar: //scholar.google.it/citations?user=ce2GMqoAAAAJ&hl=en

Pubmed: //pubmed.ncbi.nlm.nih.gov/?term=%28%22Melotti+R%22%5BAu%5D%29&sort=date&size=200

Linkedin: //www.linkedin.com/in/roberto-melotti-113aab321/

Scientific Publications

Journal article2025

Development and evaluation of a kidney health questionnaire and estimates of chronic kidney disease prevalence in the Cooperative Health Research in South Tyrol (CHRIS) study

Barbieri G, Cazzoletti L, Melotti R, Hantikainen E, Lundin R, Barin L, Gögele M, Riegler P,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Rebecca Lundin, Essi Hantikainen

Background: Kidney diseases are a public health burden but are poorly investigated in the general population. In light of inadequate survey tools, we developed a novel questionnaire for use in population-based studies, to retrospectively assess kidney diseases.

Methods: The questionnaire covered general kidney diseases, reduced kidney function, and renal surgeries. It was administered between 2011 and 2018 to 11,684 participants (median age = 45 years) of the Cooperative Health Research in South Tyrol (CHRIS) study. Fasting estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) were measured. By factor analysis we contextualized the questionnaire content with respect to the biochemical measurements. We estimated overall and sex-stratified prevalence of kidney diseases, including possible CKD, calibrating them to the general target population via relative sampling weights.

Results: Population-representative prevalence of glomerulonephritis, pyelonephritis, and congenital kidney diseases was 1.0%, 3.0%, and 0.2%, respectively, with corresponding odds ratios for females versus males of 1.4 (95% confidence interval: 1.0, 2.0), 8.7 (6.2, 12.3), and 0.7 (0.3, 1.6), respectively. Prevalence of kidney dysfunction (eGFR < 60 mL/min/1.73 m² or UACR > 30 mg/g) was 8.59%, while prevalence of self-reported CKD was 0.69%, indicating 95.3% of lack of disease awareness, with a similar figure in people with diabetes or hypertension. Overall, 15.76% of the population was affected by a kidney disease of any kind.

Conclusion: In the Val Venosta/Vinschgau alpine district, CKD prevalence aligned with Western European estimates. Kidney health questionnaire implementation in population studies is feasible and valuable to assess CKD awareness, which we found to be dramatically low.

DOI Quelle

DOI: 10.1007/s40620-024-02157-6

Journal article2025

The influence of affective temperaments on sleep quality in a general population sample. Data report from the CHRIS study

Favaretto E, Gögele M, Bedani F, Giovannini S, Pramstaller PP, Perugi G, Erfurth A, Sani G,

Andrew Hicks, Martin Gögele, Roberto Melotti, Peter P. Pramstaller

Background: Affective temperaments predispose to life adaptation and affective disorders. The relationship between temperaments and sleep quality is rarely investigated in community-based studies. We hypothesized that cyclothymic-related temperaments relate to worse sleep quality, whereas the hyperthymic temperament favours sleep quality.

Method: We investigated 3701 18 to 65 years old adults from the population-based CHRIS study in Italy. Participants were 54 % females, mean age 38.5 years. The Pittsburgh Sleep Quality Index (PSQI) was the primary outcome score. Five affective temperaments split into quartiles for direct comparison from the TEMPS-M questionnaire were the exposures of interest. Additional covariates comprised sex, age, trait anxiety, and sleep quality-related lifestyles assessed via interviews, self-administered questionnaires or instrumental measurements.

Results: The hyperthymic temperament showed a negative association (better sleep quality) with the global PSQI, whereas the cyclothymic-related temperaments had all associations in opposite direction. While inclusion of trait anxiety appeared to mediate some results, the anxious and other cyclothymic related temperaments were still directly associated with multiple dimensions of poor sleep quality.

Limitations: The cross-sectional design, possible selection into the study by temperamental background or sleep disorders, and no clinically validated self-assessed psychiatric constructs represent possible weaknesses.

Conclusions: Our findings support the hypothesis of a biological binary diathesis of affective temperaments, with hyperthymic and cyclothymic-related temperaments predisposing sleep quality in an antithetical way.

DOI Quelle

DOI: 10.1016/j.jad.2025.03.055

Journal article2024

Archimedes Spiral Ratings: Determinants and Population‐Based Limits of Normal

Hopfner F, Tietz A, D'Elia Y, Pattaro C, Becktepe JS, Gögele M, Barin L, Pramstaller PP,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Peter P. Pramstaller

Background: Tremor is commonly found among healthy humans or prevalently a symptom of neurological dysfunctions. However, the distinction between physiological and pathological tremor is dependent on the examiner’s competence. Archimedes Spiral Rating (ASR) is a valid and reproducible semi-quantitative method to assess the severity of action tremor.

Objectives: (1) To assess the range and percentiles of ASR in a large sample seemingly free of tremor-related conditions or symptoms from the population-based CHRIS-study. (2) To analyse the influence of sex, age, and the drawing hand on ASR. (3) To define ASR limits of normal. (4) To supply exemplary Archimedes spiral drawings by each rating to favour consistent and proficient clinical evaluation.

Methods: Accurately investigated participants were randomly sampled over 14 sex-age strata. 2,686 paired spirals drawn with both hands by 1,343 participants were expertly assessed on a tremor rating scale from 0 to 9.

Results: ASR had a quadratic increase with age in both sexes, while it was relatively lower in the dominant compared to the non-dominant hand and in women compared to men. ASRs above sex-age specific 97.5^th percentiles of 4 and 5, below and above 60 years of age respectively, were conceivably of non-physiological nature.

Conclusions: In a large population-based sample we show a steeper increase of action tremor by age as age progresses. Relatively higher ratings among the elderly, males and the non-dominant hands, appear compatible with ASR limits of “normal” across sex-age groups. The current operational evidence may support practitioners differentiating physiological and pathological hand tremor.

DOI Quelle

DOI: 10.1002/mdc3.14201

Journal article2024

Associations Between Dietary Patterns and Kidney Health Assessed in the Population-Based CHRIS Study Using Reduced Rank Regression

Barbieri G, Garcia-Larsen V, Lundin R, Fujii R, Melotti R, Gögele M, Christopher KB, Cazzoletti L,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Peter P. Pramstaller, Rebecca Lundin, Essi Hantikainen

Objective: While diet plays a key role in chronic kidney disease (CKD) management, the potential for diet to impact CKD prevention in the general population is less clear. Using a priori knowledge, we derived disease-related dietary patterns (DPs) through reduced rank regression (RRR) and investigated associations with kidney function, separately focusing on generally healthy individuals and those with self-reported kidney diseases, hypertension, or diabetes mellitus. Methods: Eight thousand six hundred eighty-six participants from the population-based Cooperative Health Research in South Tyrol study were split into a group free of kidney disease, hypertension and diabetes (n = 6,133) and a group with any of the 3 conditions (n = 2,553). Diet was assessed through the self-administered Global Allergy and Asthma Network of Excellence food frequency questionnaire and DPs were derived through RRR selecting food frequency questionnaire–derived sodium, potassium, phosphorus, and protein intake as mediators. Outcomes were creatinine-based estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, CKD and microalbuminuria. Multiple linear and logistic models were used to assess associations between RRR-based DPs and kidney outcomes separately in the 2 analytic groups. Results: We identified 3 DPs, where high adherence reflected high levels of all nutrients (DP1), high potassium–phosphorus and low protein–sodium levels (DP2), and low potassium–sodium and high protein–phosphorus levels (DP3), respectively. We observed heterogeneous associations with kidney outcomes, varying by analytic group and sex. Kidney outcomes were much more strongly associated with DPs than with single nutrients. Conclusion: RRR is a feasible approach to estimate disease-related DPs and explore the combined effects of nutrients on kidney health. Heterogeneous associations across kidney outcomes suggest possible specificity to kidney function or damage. In individuals reporting kidney disease, hypertension or diabetes, specific dietary habits were associated with better kidney health, indicating that disease-specific dietary interventions can be effective for disease control.

DOI Quelle

DOI: 10.1053/j.jrn.2024.03.003

Internet2024

DASH diet, Reduced Rank Regression Dietary Patterns and relations with kidney function in the CHRIS general population study [preprint]

Barbieri G, Garcia-Larsen V, Lundin R, Fujii R, Melotti R, Gögele M, Christopher KB, Cazzoletti L,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Peter P. Pramstaller, Rebecca Lundin

Objective: We assessed dietary patterns (DPs) using the pre-defined Dietary Approaches to Stop Hy-pertension (DASH) score and reduced rank regression (RRR) to evaluate their association with esti-mated glomerular filtration rate (eGFR) in a general population sample. Methods: We analysed cross-sectional data from 6,133 healthy adult participants of the Cooperative Health Research In South Tyrol (CHRIS) study. Using self-reported food frequency questionnaire data, we derived the DASH-score and two RRR-based sex-specific DP-scores based on nine cardio-renal-metabolic parameters. We fitted sex-stratified linear and non-linear models to assess associations with creatinine-based eGFR. Results: Males with higher intake of cereals, whole grains, sugar, fruits, and legumes, and lower intake of beer, and red and processed meat (MDP1), exhibited higher eGFR levels. Coherently, high adher-ence to the DASH-style diet was associated with higher eGFR. In females, the associations varied by menstrual status. Among those with ceased menstruation, a low intake of meat, spirits, refined grains, beer, and fish, and a high intake of whole grains and dairy products was associated with higher eGFR. In females still experiencing regular menstruation, a high intake of beef, nuts, beer, legumes, fish, and coffee, and low intake of refined grains, (FDP2) was associated with lower eGFR. No association was observed with the DASH score in females. Conclusion: Our findings confirm the DASH-style diet is associated with better kidney function in males, but not in females. By identifying sex-specific kidney function-oriented DPs, the RRR approach provides new insights into the diet-eGFR relation, highlighting in addition potential effect modification by menstrual status.

DOI Quelle

DOI: 10.1101/2024.07.18.24310620

Internet2024

Development and evaluation of a kidney health questionnaire and estimates of chronic kidney disease prevalence in the Cooperative Health Research In South Tyrol (CHRIS) study [preprint]

Barbieri G, Cazzoletti L, Melotti R, Hantikainen E, Lundin R, Barin L, Gögele M, Riegler P,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Peter P. Pramstaller, Rebecca Lundin, Essi Hantikainen

Introduction. Kidney diseases are a public health burden but, except for chronic kidney disease (CKD), they are poorly investigated in the general population. In light of inadequate survey tools for use in population studies, we developed a novel questionnaire to retrospectively assess the main kidney diseases, integrating it within the Cooperative Health Research In South Tyrol (CHRIS) study conducted between 2011 and 2018 in the Alpine district of Val Venosta/Vinschgau (Italy). Methods. The questionnaire covers general kidney diseases, reduced kidney function, and renal surgeries. It was applied to the cross-sectional assessment of self-reported kidney health among 11,684 adults, along with measures of fasting estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR). By factor analysis we contextualized the questionnaire content with respect to biochemical measurements. CKD was defined according to KDIGO guidelines, self-reported diagnosis, and their combination. Prevalence estimates were calibrated to the general target population via relative sampling weights. Results. In this population sample (median age=45 years; median eGFR=98.4 mL/min/1.73 m2; median UACR=5.7 mg/g), 8.3% of participants reported at least one kidney disease. Population-representative prevalence of glomerulonephritis, pyelonephritis, and congenital kidney diseases was 1.0%, 3.0%, and 0.2%, respectively, with corresponding odds ratio for females versus males of 1.4 (95% confidence interval: 1.0, 2.0), 8.7 (6.2, 12.3), and 0.7 (0.3, 1.6), respectively. CKD prevalence was 8.6% when based on KDIGO criteria and 0.7% when self-reported, indicating that 95.3% of affected individuals were unaware of having CKD, with a similar figure of 92.9% in those reporting diabetes or hypertension. Overall, 15.8% of the population was affected by a kidney disease of any kind. Conclusion. In this Alpine population, CKD prevalence aligned with Western European estimates. Kidney health questionnaire implementation in population studies is feasible and valuable to assess CKD awareness, which we found to be dramatically low.

DOI

DOI: 10.1101/2024.03.24.24304607

Journal article2024

Integrating multiple kidney function markers to predict all-cause and cardiovascular disease mortality: prospective analysis of 366,758 UK Biobank participants

Fujii R, Melotti R, Köttgen A, Teumer A, Giardiello D, Pattaro C

Cristian Pattaro, Roberto Melotti

Reduced kidney function is a risk factor of cardiovascular and all-cause mortality. This association was demonstrated for several kidney function markers, but it is unclear whether integrating multiple measured markers may improve mortality risk prediction.We conducted an exploratory factor analysis (EFA) of serum creatinine- and cystatin C-based estimated glomerular filtration rate (eGFRcre and eGFRcys, derived by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) equations), blood urea nitrogen (BUN), uric acid, and serum albumin among 366 758 participants of the UK Biobank without history of kidney failure. Fitting Cox-proportional hazard models, we compared ability of the identified latent factors to predict overall mortality and mortality by cardiovascular disease (CVD), also considering CVD-specific causes like coronary heart disease and cerebrovascular disease.During 12.5 years of follow-up, 26 327 deceased from any cause, 5 376 died from CVD, 2 908 from CHD, and 1 116 from cerebrovascular disease. We identified two latent factors, EFA1 and EFA2 both representing kidney function variations. When using the CKD-EPI equations, EFA1 performed like eGFRcys, with EFA1 showing slightly larger hazard ratios for overall and CVD-related mortality. At 10-years of follow-up, EFA1 and eGFRcys showed moderate discrimination performance for CVD-related mortality, outperforming all other kidney indices. eGFRcre was the least predictive marker across all outcomes. When using the EKFC equations, eGFRcys performed better than EFA1, all other results remaining similar.While EFA is an attractive approach to capture the complex effects of kidney function, eGFRcys remains the most practical and effective measurement for all-cause and CVD mortality risk prediction.

DOI Quelle

DOI: 10.1093/ckj/sfae207

Journal article2024

Metabolite and protein associations with general health in the population-based CHRIS study

Hantikainen E, Weichenberger CX, Dordevic N, Verri Hernandes V, Foco L, Gögele M, Melotti R, Pattaro C,

Cristian Pattaro, Christian Weichenberger, Martin Gögele, Roberto Melotti, Luisa Foco, Peter P. Pramstaller, Essi Hantikainen

Identifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people's health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity. Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.

DOI Quelle

DOI: 10.1038/s41598-024-75627-3

Conference proceedings article2023

#2906 INTEGRATED KIDNEY MARKERS AND CARDIOVASCULAR MORTALITY: A SURVIVAL ANALYSIS IN UK BIOBANK

Fujii R, Melotti R, Pattaro C

Cristian Pattaro, Roberto Melotti

Background and Aims

The estimated glomerular filtration rate (eGFR) and other kidney function markers are associated with cardiovascular disease (CVD) mortality [1]. It remains unclear whether integrating multiple kidney markers together can improve CVD mortality risk prediction and what would be an appropriate method of integration. In a small general population sample, we recently showed that confirmatory factor analysis (CFA) may predict CVD risk better than single markers, but it did not outperform cystatin C-based eGFR (eGFRcys) [2]. To assess whether our findings were context-dependent and to which extent they may extend to mortality risk assessment, we applied CFA and exploratory factor analysis (EFA), integrating five kidney function markers in the UK Biobank (UKBB) study, comparing risk discrimination for CVD mortality and renal failure mortality versus established eGFR formulas.

Method

We analyzed data from 366,758 UKBB participants (mean age 56.6 years; females 53.7%) without clinical history of kidney failure at baseline. Information on participants’ mortality was collected from the National Health System registry, using ICD-10 codes I00-I99 and N17-N19 to identify CVD mortality and renal failure mortality. We applied CFA and EFA to creatinine-based estimated glomerular filtration rate (eGFRcre), eGFRcys, blood urea nitrogen (BUN), uric acid (UA), and serum albumin (Alb). EFA was fitted using maximum likelihood. Promax rotation was then applied. We fitted Cox regression models to examine the associations of mortality with kidney markers: CFA-based kidney index [CFA]; 1st EFA-based kidney index [EFA1]; 2nd EFA-based kidney index [EFA2]; eGFRcre; eGFRcys; and creatinine- and cystatin C-based eGFR (eGFRcrecys). Models were adjusted for sex, age, body mass index, education, self-reported ancestry, hypertension, diabetes, and tobacco smoking. The receiver operating characteristics (ROC) curve and the DeLong test were used to compare discriminatory ability of each index.

Results

CFA standardized factor loadings (λ) of eGFRcre, eGFRcys, BUN, UA and Alb were 0.81, 0.73, -0.55, -0.39, and 0.12, respectively. EFA identified two factors: EFA1, largely dependent on eGFRcys (λ = 0.85), and EFA2, reflecting BUN (λ = 0.88), eGFRcre (λ = -0.55) and UA (λ = 0.36). Over a median follow-up of 12.5 years, we observed 26,327mortality cases, of which 5,376 and 45 were related to CVD and renal failure. The hazard ratios (HR) and 95% confidence intervals (CI) for CVD mortality and renal failure mortality per each standard deviation change were of 1.22 (1.19–1.25) and 3.53 (2.98–4.18) for eGFRcre, 1.62 (1.57–1.67) and 7.34 (5.82–9.27) for eGFRcys, 1.47 (1.43–1.51) and 4.82 (4.04–5.76) for eGFRcrecys, 1.38 (1.34–1.41) and 2.94 (2.63–3.29) for CFA, 1.61 (1.56–1.66) and 7.54 (5.90–9.64) for EFA1, and 1.33 (1.30–1.35) and 1.98 (1.85–2.12) for EFA2. The area under the curve (AUC) for CVD mortality risk was higher for EFA1 (0.706, 0.699–0.713) than for any other kidney marker, except for eGFRcys (0.709, 0.702–0.716). The kidney failure mortality AUC of EFA1 (0.936, 0.901–0.972) was similar to that of eGFRcys (0.939, 0.905–0.972).

Conclusion

To assess the contribution of kidney function to CVD-related mortality in general population studies of mainly healthy individuals, EFA is a better way than using single markers. However, EFA does not outperform eGFRcys, which, being based on a simpler calculation, remains a better choice for CVD and renal failure mortality risk prediction.

DOI Quelle

DOI: 10.1093/ndt/gfad063a_2906

Journal article2023

Cluster analysis of angiotensin biomarkers to identify antihypertensive drug treatment in population studies

Arisido Woldeyes M, Foco L, Shoemaker R, Melotti R, Delles C, Gögele M, Barolo S, Baron S,

Cristian Pattaro, Martin Gögele, Roberto Melotti, Luisa Foco, Peter P. Pramstaller

Projekt: Molecular profiling of uncontrolled and treatment resistant hypertension in the general population: the HyperProfile study

Background

The recent progress in molecular biology generates an increasing interest in investigating molecular biomarkers as markers of response to treatments. The present work is motivated by a study, where the objective was to explore the potential of the molecular biomarkers of renin-angiotensin-aldosterone system (RAAS) to identify the undertaken antihypertensive treatments in the general population. Population-based studies offer an opportunity to assess the effectiveness of treatments in real-world scenarios. However, lack of quality documentation, especially when electronic health record linkage is unavailable, leads to inaccurate reporting and classification bias.

Method

We present a machine learning clustering technique to determine the potential of measured RAAS biomarkers for the identification of undertaken treatments in the general population. The biomarkers were simultaneously determined through a novel mass-spectrometry analysis in 800 participants of the Cooperative Health Research In South Tyrol (CHRIS) study with documented antihypertensive treatments. We assessed the agreement, sensitivity and specificity of the resulting clusters against known treatment types. Through the lasso penalized regression, we identified clinical characteristics associated with the biomarkers, accounting for the effects of cluster and treatment classifications.

Results

We identified three well-separated clusters: cluster 1 (n = 444) preferentially including individuals not receiving RAAS-targeting drugs; cluster 2 (n = 235) identifying angiotensin type 1 receptor blockers (ARB) users (weighted kappa κ_w = 74%; sensitivity = 73%; specificity = 83%); and cluster 3 (n = 121) well discriminating angiotensin-converting enzyme inhibitors (ACEi) users (κ_w = 81%; sensitivity = 55%; specificity = 90%). Individuals in clusters 2 and 3 had higher frequency of diabetes as well as higher fasting glucose and BMI levels. Age, sex and kidney function were strong predictors of the RAAS biomarkers independently of the cluster structure.

Conclusions

Unsupervised clustering of angiotensin-based biomarkers is a viable technique to identify individuals on specific antihypertensive treatments, pointing to a potential application of the biomarkers as useful clinical diagnostic tools even outside of a controlled clinical setting.

DOI Quelle

DOI: 10.1186/s12874-023-01930-8

Journal article2023

Structural equation modeling (SEM) of kidney function markers and longitudinal CVD risk assessment

Fujii R, Melotti R, Gögele M, Barin L, Ghasemi-Semeskandeh D, Barbieri G, Pramstaller PP, Pattaro C

Cristian Pattaro, Martin Gögele, Roberto Melotti, Peter P. Pramstaller

Lower kidney function is known to enhance cardiovascular disease (CVD) risk. It is unclear which estimated glomerular filtration rate (eGFR) equation best predict an increased CVD risk and if prediction can be improved by integration of multiple kidney function markers. We performed structural equation modeling (SEM) of kidney markers and compared the performance of the resulting pooled indexes with established eGFR equations to predict CVD risk in a 10-year longitudinal population-based design. We split the study sample into a set of participants with only baseline data (n = 647; model-building set) and a set with longitudinal data (n = 670; longitudinal set). In the model-building set, we fitted five SEM models based on serum creatinine or creatinine-based eGFR (eGFRcre), cystatin C or cystatin-based eGFR (eGFRcys), uric acid (UA), and blood urea nitrogen (BUN). In the longitudinal set, 10-year incident CVD risk was defined as a Framingham risk score (FRS)>5% and a pooled cohort equation (PCE)>5%. Predictive performances of the different kidney function indexes were compared using the C-statistic and the DeLong test. In the longitudinal set, a SEM-based estimate of latent kidney function based on eGFRcre, eGFRcys, UA, and BUN showed better prediction performance for both FRS>5% (C-statistic: 0.70; 95% CI: 0.65–0.74) and PCE>5% (C-statistic: 0.75; 95%CI: 0.71–0.79) than other SEM models and different eGFR formulas (DeLong test p-values<3.21×10⁻⁶ for FRS>5% and <1.49×10⁻⁹ for PCE>5%, respectively). However, the new derived marker could not outperform eGFRcys (DeLong test p-values = 0.88 for FRS>5% and 0.20 for PCE>5%, respectively). SEM is a promising approach to identify latent kidney function signatures. However, for incident CVD risk prediction, eGFRcys could still be preferrable given its simpler derivation.

DOI Quelle

DOI: 10.1371/journal.pone.0280600

Journal article2023

Trends and symptoms of SARS-CoV-2 infection: a longitudinal study on an Alpine population representative sample

Barbieri G, Pizzato M, Gögele M, Giardiello D, Weichenberger CX, Foco L, Bottigliengo D, Bertelli C,

Cristian Pattaro, Christian Weichenberger, Martin Gögele, Roberto Melotti, Luisa Foco, Peter P. Pramstaller, Rebecca Lundin

Projekt: PACE: Partnership to Accelerate Covid-19 rEsearch in South Tyrol

Objectives The continuous monitoring of SARS-CoV-2 infection waves and the emergence of novel pathogens pose a challenge for effective public health surveillance strategies based on diagnostics. Longitudinal population representative studies on incident events and symptoms of SARS-CoV-2 infection are scarce. We aimed at describing the evolution of the COVID-19 pandemic during 2020 and 2021 through regular monitoring of self-reported symptoms in an Alpine community sample.

Design To this purpose, we designed a longitudinal population representative study, the Cooperative Health Research in South Tyrol COVID-19 study.

Participants and outcome measures A sample of 845 participants was retrospectively investigated for active and past infections with swab and blood tests, by August 2020, allowing adjusted cumulative incidence estimation. Of them, 700 participants without previous infection or vaccination were followed up monthly until July 2021 for first-time infection and symptom self-reporting: COVID-19 anamnesis, social contacts, lifestyle and sociodemographic data were assessed remotely through digital questionnaires. Temporal symptom trajectories and infection rates were modelled through longitudinal clustering and dynamic correlation analysis. Negative binomial regression and random forest analysis assessed the relative importance of symptoms.

Results At baseline, the cumulative incidence of SARS-CoV-2 infection was 1.10% (95% CI 0.51%, 2.10%). Symptom trajectories mimicked both self-reported and confirmed cases of incident infections. Cluster analysis identified two groups of high-frequency and low-frequency symptoms. Symptoms like fever and loss of smell fell in the low-frequency cluster. Symptoms most discriminative of test positivity (loss of smell, fatigue and joint-muscle aches) confirmed prior evidence.

Conclusions Regular symptom tracking from population representative samples is an effective screening tool auxiliary to laboratory diagnostics for novel pathogens at critical times, as manifested in this study of COVID-19 patterns. Integrated surveillance systems might benefit from more direct involvement of citizens’ active symptom tracking.

DOI Quelle

DOI: 10.1136/bmjopen-2023-072650

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Conference proceedings article2023

#2906 INTEGRATED KIDNEY MARKERS AND CARDIOVASCULAR MORTALITY: A SURVIVAL ANALYSIS IN UK BIOBANK

Fujii R, Melotti R, Pattaro C

Cristian Pattaro, Roberto Melotti

Background and Aims

Method

Results

Conclusion

DOI Quelle

DOI: 10.1093/ndt/gfad063a_2906