A universal language for finding mass spectrometry data patterns
Damiani T, Jarmusch AK, Aron AT, Petras D, Phelan VV, Zhao HN, Bittremieux W, Acharya DD,
DOI: 10.1038/s41592-025-02660-z
Senior Researcher
Institute for Biomedicine
External links:
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Damiani T, Jarmusch AK, Aron AT, Petras D, Phelan VV, Zhao HN, Bittremieux W, Acharya DD,
DOI: 10.1038/s41592-025-02660-z
Vangeenderhuysen P, Vynck M, Pomian B, De Windt K, Callemeyn E, De Paepe E, De Commer L, Raes J,
DOI: 10.1021/acs.analchem.5c00567
Witting M, Rainer J
DOI: 10.1007/978-1-0716-4334-1_4
Ghasemi-Semeskandeh D, König E, Foco L, Dordevic N, Gögele M, Rainer J, Ralser M, Acoba D,
Cristian Pattaro, Martin Gögele, Luisa Foco, Peter P. Pramstaller, Eva König, Johannes Rainer
Genome-wide association studies (GWAS) identified a locus on chromosome 4q21.1, spanning the Family With Sequence Similarity 47 Member E (FAM47E), Starch Binding Domain 1 (STBD1), Coiled-Coil Domain Containing 158 (CCDC158), and Shroom Family Member 3 (SHROOM3) genes, to be associated with kidney function markers. Functional studies implicated SHROOM3 as the effector gene, demonstrating its developmental role to guarantee podocyte barrier integrity. However, the locus has also been associated with other clinical traits, including electrolytes, hematological, cardiovascular, and neurological traits, not all of which can be easily traced to the regulation of kidney function. We therefore conducted a systematic analysis of the whole locus’ genetic profiles (haplotypes) to assess which phenotypic profiles they were associated with.
For the 4 genes, we reconstructed haplotypes spanning 71 exonic and intronic variants for 12,834 participants in the Cooperative Health Research in South Tyrol (CHRIS) study based on genotypes imputed on a local whole-exome sequencing (WES) reference panel. Haplotypes were tested for associations with 72 clinical traits, 170 serum metabolites, and 148 plasma protein concentrations, using linear regression models.
We identified 11 haplotypes with a population frequency between 2% and 24%. Compared with the most common haplotype, most haplotypes were associated with higher creatinine-based estimated glomerular filtration rate (eGFR) and lower serum magnesium levels. In addition, specific haplotypes were also associated with biologically diverse groups of traits, including albuminuria, blood pressure, red blood cell traits, carnitines, and amino acids. Cluster analysis highlighted the existence of distinct genetic profiles in which individuals with specific haplotypes presented with specific phenotypic and metabolic signatures.
The genetic variability of the FAM47E–SHROOM3 locus indicates the existence of population subgroups with distinct biomarker profiles.
DOI: 10.1016/j.ekir.2025.02.018
Garcia-Aloy M, Rainer J, Franceschi P
DOI: 10.1007/978-1-0716-4334-1_5
Soneson C, Shepherd L, Ramos M, Rue-Albrecht K, Rainer J, Pagès H, Carey VJ
DOI: 10.1371/journal.pcbi.1012856
Dordevic N, Dierks C, Hantikainen E, Farztdinov V, Amari F, Verri Hernandes V, De Grandi A, Domingues FS,
Peter P. Pramstaller, Alessandro De Grandi, Essi Hantikainen, Johannes Rainer
Background: The study of circulating blood proteins in population cohorts offers new avenues to explore lifestyle-related and genetic influences describing and shaping human health.
Methods: Utilizing high-throughput mass spectrometry, we quantified 148 highly abundant proteins, functioning in the innate and adaptive immune system, coagulation and nutrient transport in 3632 blood plasma, and 500 serum samples from the CHRIS and BASE-II cross-sectional population studies, respectively. Through multiple regression analyses, we aimed to identify the main factors influencing the circulating proteome at population level.
Results: Many demographic covariates and common medications affect the concentration of high-abundant plasma proteins, but the most significant changes are linked to the use of hormonal contraceptives (HCU). HCU particularly alters amongst others the levels of Angiotensinogen and Transcortin. We robustly replicated these findings in the BASE-II cohort. Furthermore, our results indicate that combined hormonal contraceptives with ethinylestradiol have a stronger effect compared to bioidentical estrogens. Our analysis detects no lasting impact of hormonal contraceptives on the plasma proteome.
Conclusions: HCU is the dominant factor reshaping the high-abundant circulating blood proteome in two population studies. Given the high prevalence of HCU among young women, it is essential to account for this treatment in human proteome studies to avoid misinterpreting its impact as sex- or age-related effects. Although we did not investigate the influence of HCU-induced proteomic changes on human health, our data suggest that future studies on this topic are warranted.
DOI: 10.1038/s43856-025-00856-0
Ghasemi-Semeskandeh D, Foco L, Fujii R, Rainer J, Mohadeseh F, Ralser M, Domingues FS, Pramstaller PP,
Cristian Pattaro, Luisa Foco, Peter P. Pramstaller, Johannes Rainer
Genome-wide association studies (GWAS) generated thousands of loci associated with complex traits and diseases. However, to characterize of the pleiotropic, molecular and population genetic bounds of uncovered loci, investigations are conducted, that remain conceptually and practically separated. Also in the best case, such investigations proceed by one locus at a time. To address these limitations, we introduce an efficient and reproducible Snakemake pipeline for executing haplotype-based association analysis on GWAS-identified genetic loci, which is especially helpful in samples enriched with molecular omics data. Haplomics takes as input the genetic coordinates of each locus along with all available clinical and molecular phenotypes, the necessary covariates, and VCF genotype files, to reconstruct haplotypes and test them for associations with the phenotypes. The reconstructed haplotypes, the annotation of included variants, and association results are graphically displayed in an HTML report. We tested Haplomics in population-based study sample encompassing 391 traits, including 72 clinical markers, 171 serum metabolites, 148 plasma protein concentrations, and whole-exome sequencing (WES) imputed genotypes. We estimated WES-based haplotypes at 11 kidney function genetic loci from a GWAS and conducted association analyses throughout, identifying 19 significant associations after multiple testing correction. Haplomics is a scalable, easy-to-use and fast haplotype reconstruction and association pipeline that makes it possible to jointly conduct molecular and population-genetic characterization of multiple GWAS loci in unified analysis framework.
DOI: 10.1101/2025.06.12.25329492
Hantikainen E, Dordevic N, Neunhaeuserer D, Pramstaller PP, Rainer J, Gatterer H
Peter P. Pramstaller, Essi Hantikainen, Johannes Rainer, Hannes Gatterer
Projekt: Auswirkungen einer moderaten Höhenexposition auf gesunde Menschen
Introduction: Residing at moderate altitudes has been associated with various health benefits also affecting mortality risk. This study investigates life expectancy and disease-specific mortality rates among populations in the Italian Alps and in northern Italian lowland regions. Additionally, cardiometabolic health and serum metabolite concentrations of residents in an Alpine province across three distinct elevation zones (<1,000 m, 1,000-1,500 m, and >1,500 m above sea level) are studied.
Methods: Data on life expectancy and mortality rate (per ten thousand) were retrieved from the ISTAT database for 6 provinces located in the Italian Alps and 6 provinces at sea level near the Alps. Using cross-sectional data from a sub-sample of the Cooperative Health Research in South Tyrol (CHRIS) study (n=6,292), we fitted multivariable adjusted logistic regression models to investigate associations between altitude and cardiometabolic health, determined by the Cumulative Illness Rating Scale. Moreover, associations between altitude and 175 serum metabolites were evaluated through linear regression models (n=1,447).
Results: Population size and sex distribution were similar between provinces (p>0.485). Life expectancy at 65 years differed between areas (20.8±0.4 vs 20.1±0.3, for Alps vs sea-level, respectively, p=0.026). Mortality rate for diseases of the circulatory system was lower in the Alps than at sea-level (35.3±5.7 vs. 44.5±6.8, respectively, p=0.026). No statistically significant differences were found for mortality (Alps vs. sea-level) from all causes (108.1±15.7 vs. 126.1±15.5, p=0.065), cerebrovascular diseases (8.4±2.5 vs. 12.6±3.1, p=0.065), endocrine, nutritional and metabolic diseases (3.6±1.0 vs. 5.0±1.0, p=0.065), neoplasms (31.1±4.7 vs. 34.3±2.4 p=0.394) and diseases of the respiratory system (8.3±1.7 vs. 8.8±1.7, p=0.589). In the CHRIS study sample, living at moderate vs. low altitude level was associated with lower odds of mild to severe conditions in the hypertension (OR:0.77; 95%CI: 0.62-0.96) and endocrine-metabolic domain (OR:0.77, 95%CI: 0.61-0.97). No differences in blood serum metabolic profiles were observed between people living at different altitude levels.
Conclusions: Living in the Italian Alps seems to have a positive effect on life expectancy and mortality from certain diseases compared to living at sea level in northern Italy. Furthermore, living at moderate altitude conferred some cardiometabolic health benefits in the CHRIS study population, even after corrections for confounding factors. The metabolite profile in a sub-sample did, however, not reveal any significant differences between altitude levels.
DOI: 10.1159/000546975
Thaitumu MN, De Sá E Silva DM, Louail P, Rainer J, Avgerinou G, Petridou A, Mougios V, Theodoridis G,
Projekt: Harmonisierung und Vereinheitlichung der Metabolomics-Analyse in Blutproben
DOI: 10.3390/metabo15010062
De Graeve M, Bittremieux W, Naake T, Huber C, Anagho-Mattanovich M, Hoffmann N, Marchal P, Chrone V,
Projekt: Harmonisierung und Vereinheitlichung der Metabolomics-Analyse in Blutproben
Mass spectrometry (MS) is a key technology used across multiple fields, including biomedical research and life sciences. The data is often times large and complex, and analyses must be tailored to the experimental and instrumental setups. Excellent software libraries for such data analysis are available in both R and Python, including R packages from the RforMassSpectrometry initiative such as Spectra, MsCoreUtils, MetaboAnnotation, and CompoundDb (Rainer et al., 2022), as well as Python libraries like matchms (Huber et al., 2020), spectrum_utils (Bittremieux, 2020), Pyteomics (Goloborodko et al., 2013), and pyOpenMS (Röst et al., 2014). The reticulate R package (Ushey et al., 2025) provides an R interface to Python enabling interoperability between the two programming languages. The open-source SpectriPy R package builds upon reticulate and provides functionality to efficiently translate between R and Python MS data structures. It can convert between R’s Spectra::Spectra and Python’s matchms.Spectrum and spectrum_utils.spectrum.MsmsSpectrum objects and includes functionality to directly apply spectral similarity, filtering, normalization, etc. routines from the Python matchms library on MS data in R. SpectriPy hence enables and simplifies the integration of R and Python for MS data analysis, empowering data analysts to benefit from the full power of algorithms in both programming languages. Furthermore, software developers
can reuse algorithms across languages rather than re-implementing them, enhancing efficiency and collaboration.
DOI: 10.21105/joss.08070
Louail P, Brunius C, Garcia-Aloy M, Kumler W, Storz N, Stanstrup J, Treutler H, Vangeenderhuysen P,
Projekt: Harmonisierung und Vereinheitlichung der Metabolomics-Analyse in Blutproben
DOI: 10.1021/acs.analchem.5c04338