Digital Drugs: an anatomy of new medicines

Medicines are digitalized as aspects of their regulation and use are embodied in or draw from interlinked computerized systems and databases. This paper considers how this development changes the delivery of health care, the pharma industry, and regulatory and professional structures, as it reconfigures the material character of drugs themselves. It draws on the concept of assemblage in presenting a theory-based analysis that explores digital drugs’ ontological status including how they embody benefit and value. The paper addresses three interconnected domains – that of use of drugs (practice), of research (epistemology) and of regulation (structures)

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

The differential diagnosis of chronic daily headaches: an algorithm-based approach

Chronic daily headaches (CDHs) refers to primary headaches that happen on at least 15 days per month, for 4 or more hours per day, for at least three consecutive months. The differential diagnosis of CDHs is challenging and should proceed in an orderly fashion. The approach begins with a search for “red flags” that suggest the possibility of a secondary headache. If secondary headaches that mimic CDHs are excluded, either on clinical grounds or through investigation, the next step is to classify the headaches based on the duration of attacks. If the attacks last less than 4 hours per day, a trigeminal autonomic cephalalgia (TAC) is likely. TACs include episodic and chronic cluster headache, episodic and chronic paroxysmal hemicrania, SUNCT, and hypnic headache. If the duration is ≥4 h, a CDH is likely and the differential diagnosis encompasses chronic migraine, chronic tension-type headache, new daily persistent headache and hemicrania continua. The clinical approach to diagnosing CDH is the scope of this review

Parental origin of sequence variants associated with complex diseases

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldEffects of susceptibility variants may depend on from which parent they are inherited. Although many associations between sequence variants and human traits have been discovered through genome-wide associations, the impact of parental origin has largely been ignored. Here we show that for 38,167 Icelanders genotyped using single nucleotide polymorphism (SNP) chips, the parental origin of most alleles can be determined. For this we used a combination of genealogy and long-range phasing. We then focused on SNPs that associate with diseases and are within 500 kilobases of known imprinted genes. Seven independent SNP associations were examined. Five-one with breast cancer, one with basal-cell carcinoma and three with type 2 diabetes-have parental-origin-specific associations. These variants are located in two genomic regions, 11p15 and 7q32, each harbouring a cluster of imprinted genes. Furthermore, we observed a novel association between the SNP rs2334499 at 11p15 and type 2 diabetes. Here the allele that confers risk when paternally inherited is protective when maternally transmitted. We identified a differentially methylated CTCF-binding site at 11p15 and demonstrated correlation of rs2334499 with decreased methylation of that site.info:eu-repo/grantAgreement/EC/FP7/21807

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Associations between Prenatal Urinary Biomarkers of Phthalate Exposure and Preterm Birth: A Pooled Study of 16 US Cohorts

Importance: Phthalate exposure is widespread among pregnant women and may be a risk factor for preterm birth. Objective: To investigate the prospective association between urinary biomarkers of phthalates in pregnancy and preterm birth among individuals living in the US. Design, Setting, and Participants: Individual-level data were pooled from 16 preconception and pregnancy studies conducted in the US. Pregnant individuals who delivered between 1983 and 2018 and provided 1 or more urine samples during pregnancy were included. Exposures: Urinary phthalate metabolites were quantified as biomarkers of phthalate exposure. Concentrations of 11 phthalate metabolites were standardized for urine dilution and mean repeated measurements across pregnancy were calculated. Main Outcomes and Measures: Logistic regression models were used to examine the association between each phthalate metabolite with the odds of preterm birth, defined as less than 37 weeks of gestation at delivery (n = 539). Models pooled data using fixed effects and adjusted for maternal age, race and ethnicity, education, and prepregnancy body mass index. The association between the overall mixture of phthalate metabolites and preterm birth was also examined with logistic regression. G-computation, which requires certain assumptions to be considered causal, was used to estimate the association with hypothetical interventions to reduce the mixture concentrations on preterm birth. Results: The final analytic sample included 6045 participants (mean [SD] age, 29.1 [6.1] years). Overall, 802 individuals (13.3%) were Black, 2323 (38.4%) were Hispanic/Latina, 2576 (42.6%) were White, and 328 (5.4%) had other race and ethnicity (including American Indian/Alaskan Native, Native Hawaiian, >1 racial identity, or reported as other). Most phthalate metabolites were detected in more than 96% of participants. Higher odds of preterm birth, ranging from 12% to 16%, were observed in association with an interquartile range increase in urinary concentrations of mono-n-butyl phthalate (odds ratio [OR], 1.12 [95% CI, 0.98-1.27]), mono-isobutyl phthalate (OR, 1.16 [95% CI, 1.00-1.34]), mono(2-ethyl-5-carboxypentyl) phthalate (OR, 1.16 [95% CI, 1.00-1.34]), and mono(3-carboxypropyl) phthalate (OR, 1.14 [95% CI, 1.01-1.29]). Among approximately 90 preterm births per 1000 live births in this study population, hypothetical interventions to reduce the mixture of phthalate metabolite levels by 10%, 30%, and 50% were estimated to prevent 1.8 (95% CI, 0.5-3.1), 5.9 (95% CI, 1.7-9.9), and 11.1 (95% CI, 3.6-18.3) preterm births, respectively. Conclusions and Relevance: Results from this large US study population suggest that phthalate exposure during pregnancy may be a preventable risk factor for preterm delivery

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Personalized networks of eating disorder symptoms predicting eating disorder outcomes and remission

Enhanced cognitive–behavioral therapy (CBT-E) is one of the primary evidence-based treatments for adults with eating disorders (EDs). However, up to 50% of individuals do not respond to CBT-E, likely because of the high heterogeneity present even within similar diagnoses. This high heterogeneity, especially in regard to presenting pathology, makes it difficult to develop a treatment based “on averages” and for clinicians to accurately pinpoint which symptoms should be targeted in treatment. As such, new models based at both the group, and individual level, are needed to more accurately refine targets for personalized evidence-based treatments that can lead to full remission. The current study (Expected N = 120 anorexia nervosa, atypical anorexia nervosa, and bulimia nervosa) will build both group and individual longitudinal models of ED behaviors, cognitions, affect, and physiology. We will collect data for 30 days utilizing a mobile application to assess behaviors, cognition, and affect and a sensor wristband that assesses physiology (heart rate, acceleration). We will also collect outcome data at 1- and 6-month follow-ups to assess ED outcomes and remission status. These data will allow for identification of “on average” and “individual” targets that maintain ED pathology and test if these targets predict outcomes, including ED remission