Jörn Lötsch

Goethe-Universität Frankfurt am Main

Heat pain and its modulation by capsaicin varies among subjects in experimental and clinical settings. A plausible cause is a genetic component, of which TRPV1 ion channels, by their response to both heat and capsaicin, are primary candidates. However, TRPA1 channels can heterodimerize with TRPV1 channels and carry genetic variants reported to modu...

Biomedical pain research using cell experiments, laboratory animals or employing studies in human volunteers produces increasingly complex and high-dimensional data, which poses challenges on the analytical tools. These developments were paralleled by the rapid growth of computational science into a multidisciplinary field that uses advanced comput...

The comprehensive assessment of pain-related human phenotypes requires combinations of nociceptive measures that produce complex high-dimensional data, posing challenges to bioinformatic analysis. In this study, we assessed established experimental models of heat hyperalgesia of the skin, consisting of local ultraviolet-B (UV-B) irradiation or caps...

Background: To prevent persistent post-surgery pain, early identification of patients at high risk is a clinical need. Supervised machine-learning techniques were used to test how accurately the patients' performance in a preoperatively performed tonic cold pain test could predict persistent post-surgery pain. Methods: We analysed 763 patients f...

Genes causally involved in human insensitivity to pain provide a unique molecular source of studying the pathophysiology of pain and the development of novel analgesic drugs. The increasing availability of “big data” enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We u...

Background: Random walks describe stochastic processes characterized by a sequence of unpredictable changes in a random variable with no correlation to past changes. This report describes a random walk component of a clinical sensory test of olfactory performance. The precise definition of this stochastic process allows the establishment of precise...

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous studies suggest that lipids may play a role in CIPN. Therefore, the present study aimed to identify the particular types of lipids that are regulated as a consequence of paclitaxel administration and ma...

Recent advances in mathematical modeling and artificial intelligence have challenged the use of traditional regression analysis in biomedical research. This study examined artificial data sets %data set changed to data set throughout for consistency of terminology; please verify OK and biomedical data sets from cancer research using binomial and mu...

Background Psoriatic arthritis (PsA) is a chronic inflammatory systemic disease that is often categorized based on the Disease Activity Score 28 (DAS-28 CRP). However, since DAS28-CRP was originally designed for rheumatoid arthritis, it may not perfectly reflect PsA, and periodic re-evaluation has been recommended. Methods A cohort of 80 PsA patie...

The importance of appropriate visualisation of raw data in biomedical reports, with a focus on pain.

Sex differences in pain perception have been extensively studied, but precision medicine applications such as sex-specific pain pharmacology have barely progressed beyond proof-of-concept. A data set of pain thresholds to mechanical (blunt and punctate pressure) and thermal (heat and cold) stimuli applied to non-sensitized and sensitized (capsaicin...

Selecting the k best features is a common task in machine learning. Typically, a few features have high importance, but many have low importance (right-skewed distribution). This report proposes a numerically precise method to address this skewed feature importance distribution in order to reduce a feature set to the informative minimum of items. C...

Background Random walks describe stochastic processes that result from a sequence of indeterminate changes in a random variable that are not correlated with past changes. This report describes a random walk component of a clinical sensory test of olfactory performance. The formal description of the stochastic process during the clinical test allows...

Background Clustering on projected data is a common component of the analysis of biomedical research datasets. Among projection methods, principal component analysis (PCA) is the most commonly used. It focuses on the dispersion (variance) of the data, whereas clustering attempts to identify concentrations (neighborhoods) within the data. These may...

Background Loss of olfactory function appears to be a typical COVID-19 symptom, at least in early variants of SARS-CoV2. The time that has elapsed since the emergence of COVID-19 now allows us to assess the long-term prognosis of its olfactory impact. Methods Participants (n = 722 of whom n = 464 reported having had COVID-19 dating back with a mod...

Background Selecting the k best features is a common task in machine-learning. Typically, a few variables have high importance, but many have low importance (right skewed distribution). This report proposes a numerically precise method to address this skewed feature importance distribution to reduce a feature set to the informative minimum of items...

Feature selection is a common step in data preprocessing that precedes machine learning to reduce data space and the computational cost of processing or obtaining the data. Filtering out uninformative variables is also important for knowledge discovery. By reducing the data space to only those components that are informative to the class structure,...

Morphine prescribed for analgesia has caused drug-related deaths at an estimated incidence of 0.3% to 4%. Morphine has pharmacological properties that make it particularly difficult to assess the causality of morphine administration with a patient's death, such as its slow transfer between plasma and central nervous sites of action and the existenc...

Bayesian inference is ubiquitous in science and widely used in biomedical research such as cell sorting or {\textquotedbl}omics{\textquotedbl} approaches, as well as in machine learning (ML) and artificial neural networks, and {\textquotedbl}big data{\textquotedbl} applications. However, the calculation is not robust in regions of low evidence. In...

Motivation: Gaussian mixture models (GMMs) are probabilistic models commonly used in biomedi-cal research to detect subgroup structures in data sets with one-dimensional information. Reliable model parameterization requires that the number of modes, i.e., states of the generating process, is known. However, this is rarely the case for empirically m...

Knowledge discovery in biomedical data using supervised methods assumes that the data contain structure relevant to the class structure if a classifier can be trained to assign a case to the correct class better than by guessing. In this setting, acceptance or rejection of a scientific hypothesis may depend critically on the ability to classify cas...

Background: The collection of increasing amounts of data in healthcare has become relevant for pain therapy and research. This poses problems for analyses with classical approaches, which is why artificial intelligence (AI) and machine learning (ML) methods are being included into pain research. Methods: The current literature on AI and ML in the...

The neurobiological mechanisms underlying the effects of delta-9-tetrahydrocannabinol (THC) remain unclear. Here, we examined the spatial acute effect of THC on human on regional brain activation or blood flow (hereafter called ‘activation signal’) in a ‘core’ network of brain regions from 372 participants, tested using a within-subject repeated me...

Background: The categorization of individuals as normosmic, hyposmic, or anosmic from test results of odor threshold, discrimination, and identification may provide a limited view of the sense of smell. The purpose of this study was to expand the clinical diagnostic repertoire by including additional tests. Methods: A random cohort of n = 135 in...

Background: Data transformations are commonly used in bioinformatics data processing in the context of data projection and clustering. The most used Euclidean metric is not scale invariant and therefore occasionally inappropriate for complex, e.g., multimodal distributed variables and may negatively affect the results of cluster analysis. Specifica...

Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabo-lomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, slee...

Background: Persistent postsurgical neuropathic pain (PPSNP) can occur after intraoperative damage to somatosensory nerves, with a prevalence of 29-57% in breast cancer surgery. Proteomics is an active research field in neuropathic pain and the first results support its utility for establishing diagnoses or finding therapy strategies. Methods: 5...

Internalin-B-mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin-B. Here, we propose a method based on hidden Markov modeling and explainable artificial intelligence th...

The use of artificial intelligence (AI) systems in biomedical and clinical settings can disrupt the traditional doctor-patient relationship, which is based on trust and transparency in medical advice and therapeutic decisions. When the diagnosis or selection of a therapy is no longer made solely by the physician, but to a significant extent by a ma...

Because it is associated with central nervous changes, and olfactory dys-function has been reported with increased prevalence among persons with diabetes , this study addressed the question of whether the risk of developing diabetes in the next 10 years is reflected in olfactory symptoms. In a cross-sectional study, in 164 individuals seeking medic...

The evaluation of pharmacological data using machine learning requires high data quality. Therefore, preprocessing of data, i.e., cleaning of analytical laboratory errors, replacement of missing values or outliers, and adequate data transformations before actual data analysis are crucial. Since current tools available for this purpose often require...

Chronic rhinosinusitis (CRS) is often treated by functional endoscopic paranasal sinus surgery, which improves endoscopic parameters and quality-of-life while olfactory function was suggested as a further criterion of treatment success. In a prospective cohort study 37 parameters from four categories were recorded from 60 men and 98 women before an...

Olfactory self-assessments have been analyzed with often negative but also positive conclusions about their usefulness as surrogate for sensory olfactory testing. Patients with nasal polyposis have been highlighted as a well-predisposed group for reliable self-assessment. In a prospective cohort of n = 156 nasal polyposis patients, olfactory thresh...

Motivation: The size of today's biomedical data sets pushes computer equipment to its limits, even for seemingly standard analysis tasks such as data projection or clustering. Reducing large biomedical data by downsampling is therefore a common early step in data processing, often performed as random uniform class-proportional downsampling. In this...

Background: Interactions of drugs with the classical epigenetic mechanism of DNA meth-ylation or histone modification are increasingly being elucidated mechanistically and used to develop novel classes of epigenetic therapeutics. A data science approach is used to synthesize current knowledge on the pharmacological implications of epigenetic regula...

Background: Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and odors according to the extent to which they are perceived differently with reduced sense of smell, as a possible basis for creating olfactory...

Purpose The antifungal drugs ketoconazole and itraconazole reduce serum concentrations of 4β-hydroxycholesterol, which is a validated marker for hepatic cytochrome P450 (CYP) 3A4 activity. We tested the effect of another antifungal triazole agent, fluconazole, on serum concentrations of different sterols and oxysterols within the cholesterol metabo...

R library (code)

Euclidean distance-optimized data transformation for multivariate mining of non-trivial biomedical data (EDO)

The genetic background of pain is becoming increasingly well understood, which opens 14 up possibilities for predicting the individual risk of persistent pain and the use of tailored therapies 15 adapted to the variant pattern of the patient's pain-relevant genes. The individual variant pattern of 16 pain-relevant genes is accessible via next-gener...

Viral rhinitis contributes significantly to olfactory dysfunction, but it is unclear how many patients have other chemosensory symptoms in addition to olfactory loss. This was addressed in the present reanal-ysis of data previously published in Pellegrino et al. 2017. Int Forum Allergy Rhinol. 7(2):185-191, using unsupervised and supervised machine...

With this volume, the peer-reviewed open access journal Biomedinformatics published online on the website [...]

Background: In pain research and clinics, it is common practice to subgroup subjects according to shared pain characteristics. This is often achieved by computer-aided clustering. In response to a recent EU recommendation that computer-aided decision-making should be transparent, we propose an approach that uses machine learning to provide (i) an u...

A non-parametric effect-size measure capturing changes in central tendency and data distribution shape

Motivation: Calculating the magnitude of treatment effects or of differences between two groups is a common task in quantitative science. Standard effect size measures based on differences, such as the commonly used Cohen's, fail to capture the treatment-related effects on the data if the effects were not reflected by the central tendency. The pre...

Background: An important measure in pain research is the intensity of nociceptive stimuli and their cortical representation. However, there is evidence of different cerebral representations of nociceptive stimuli, including the fact that cortical areas recruited during processing of intranasal nociceptive chemical stimuli included those outside the...

Background: Data from biomedical measurements usually include many parameters (variables/features). To reduce efforts of data acquisition or to enhance comprehension, a feature selection method is proposed that combines the ranking of the relative importance of each parameter in random forests classifiers with an item categorization provided by com...

Patients with chronic pain have complex pain profiles and associated problems. Subgroup analysis can help identify key problems. We used a data-based approach to define pain phenotypes and their most relevant associated problems in 320 patients undergoing tertiary pain management. Unsupervised machine learning analysis of parameters "pain intensity...

Genetic association studies have shown their usefulness in assessing the role of ion 16 channels in human thermal pain perception. We used machine learning to construct a complex 17 phenotype from pain thresholds to thermal stimuli and associate it with the genetic information 18 derived from the next generation sequencing (NGS) of 15 ion channel g...

Background Parkinson's disease (PD) causes chronic pain in two‐thirds of patients, in part originating from sensory neuropathies. The aim of the present study was to describe the phenotype of PD‐associated sensory neuropathy and to evaluate its associations with lipid allostasis, the latter motivated by recent genetic studies associating mutations...

Background: Chemosensory loss is a symptom of Parkinson’s disease starting already at preclinical stages. Their appearance without an identifiable etiology therefore indicates a possible early symptom of Parkinson’s disease. Supervised machine-learning was used to identify parameters that predict Parkinson’s disease among patients having sought med...

In the context of data science, data projection and clustering are common procedures. The chosen analysis method is crucial to avoid faulty pattern recognition. It is therefore necessary to know the properties and especially the limitations of projection and clustering algorithms. This report describes a collection of data sets that are grouped tog...

Background: Persistent pain in breast cancer survivors is common. Psychological and sleep-related factors modulate perception, interpretation and coping with pain and may contribute to the clinical phenotype. The present analysis pursued the hypothesis that breast cancer survivors form sub-groups, based on psychological and sleep-related parameters...

Finding subgroups in biomedical data is a key task in biomedical research and precision medicine. Already one-dimensional data, such as many different readouts from cell experiments, preclinical or human laboratory experiments or clinical signs, often reveal a more complex distribution than a single mode. Gaussian mixtures play an important role in...

Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and finally the identification of relevant subgroups. Correct data visualizations and projections from the high-dimensional space to the visualization plane require...

Background: Glial cells in the central nervous system play a key role in neuroinflammation and subsequent central sensitization to pain. They are therefore involved in the development of persistent pain. One of the main sites of interaction of the immune system with persistent pain has been identified as neuro-immune crosstalk at the glial-opioid...

Background: Cannabis proofed to be effective in pain relief, but one major side effect is its influence on memory in humans. Therefore, the role of memory on central processing of nociceptive information was investigated in healthy volunteers. Methods: In a placebo-controlled cross-over study including 22 healthy subjects, the effect of 20 mg oral...

Type Package Title Calculation and Visualization of the Impact Effect Size Measure Description A non-parametric effect size measure capturing changes in central tendency or shape of data distributions for feature selection preceding machine-learning. The package provides the necessary functions to calculate and plot the Impact effect size measure b...

Persistent and in particular neuropathic pain is a major health care problem with still insufficient pharmacological treatment options. This triggered research activities aimed at finding analgesics with a novel mechanism of action. Results of these efforts will need to pass through the phases of drug development , in which experimental human pain...

A right-left dichotomy of olfactory processes has been recognized on several levels of the perception or processing of olfactory input. On a clinical level, the lateralization of components of human olfaction is contrasted by the predominantly birhinal olfactory testing. The present analyses aimed at investigation of the relation of such side-diffe...

Background: Changes in human olfactory function throughout the year appear to be a common perception due to the seasonal oscillations in some etiologies associated with olfactory loss. However, longitudinal data from large cohorts were rarely analysed for temporal patterns of human olfaction apart from oscillations in specific etiologies of olfact...

Schmerz hat eine komplexe Pathophysiologie, die sich in komplexen und heterogenen klinischen Phänotypen ausdrückt. Dies macht die Erforschung von Schmerz und seiner Behandlung zu einem potenziell datenintensiven Thema, bei dessen Bearbeitung große Mengen komplexer Daten aufgenommen werden. Typische Quellen solcher Daten sind Untersuchungen mit funk...

Background: Persistent pain extending beyond 6 months after breast cancer surgery when adjuvant therapies have ended is a recognised phenomenon. The evolution of postsurgery pain is therefore of interest for future patient management in terms of possible prognoses for distinct groups of patients to enable better patient information. Objective(s):...

Early detection of patients with chronic diseases at risk of developing persistent pain is clinically desirable for timely initiation of multimodal therapies. Quality follow-up registries may provide the necessary clinical data; however, their design is not focused on a specific research aim, which poses challenges on the data-analysis strategy. He...

Pain has a complex pathophysiology expressed in multifaceted and heterogeneous clinical phenotypes, making research on pain and its treatment a potentially data-rich field as large amounts of complex data are generated. Typical sources are data derived from functional magnet resonance imaging, complex quantitative sensory testing, next-generation D...

Human cold perception and nociception play an important role in persisting pain. However, species differences in the target temperature of thermosensitive ion channels expressed in peripheral nerve endings have fueled discussions about the mechanism of cold nociception in humans. Most frequently implicated thermosensors are members of the transient...

In clinical practice, with its time constraints, a frequent conclusion is that asking about the ability to smell may suffice to detect olfactory problems. To address this question systematically, 6,049 subjects were asked about how well they can perceive odors, with five possible responses. Partic-ipants presented at a University Department of Otor...

Abtract: Cancer and its surgical treatment are among the most important triggering events for persistent pain, but additional factors need to be present for the clinical manifestation, such as variants in pain-relevant genes. In a cohort of 140 women undergoing breast cancer surgery, assigned based on a three-year follow-up to either a persistent...

Fits Gaussian mixtures by applying evolution. As fitness function a mixture of the chi square test for distributions and a novel measure for approximating the common area under curves between multiple Gaussians is used. The package presents an alternative to the commonly used likelihood maximisation as is used in Expectation maximisation.

Persistent, in particular neuropathic pain affects millions of people worldwide. However, the response rate of patients to existing analgesic drugs is less than 50%. There are several possibilities to increase this response rate, such as optimization of the pharmacokinetic and pharmacodynamic properties of analgesics. Another promising approach is...

An interactive tool to optimize the parameters of a GMM, called “AdaptGauss”, was realized using the freely available R software package (version 3.2.0 for Windows / version 3.2.1 for Linux; http://CRAN.R-project.org/). The newly devolved R library “AdaptGauss” is freely available at https://cran.r-project.org/web/packages/AdaptGauss/index.html. Fo...

Based on accumulating evidence of a role of lipid signaling in many physiological and pathophysiolog-ical processes including psychiatric diseases, the present data driven analysis was designed to gather information needed to develop a prospective biomarker, using a targeted lipidomics approach covering different lipid mediators. Using unsupervised...