Genomics in neurodevelopmental disorders: an avenue to personalized medicine

Despite the remarkable number of scientific breakthroughs of the last 100 years, the treatment of neurodevelopmental disorders (e.g., autism spectrum disorder, intellectual disability) remains a great challenge. Recent advancements in genomics, such as whole-exome or whole-genome sequencing, have enabled scientists to identify numerous mutations underlying neurodevelopmental disorders. Given the few hundred risk genes that have been discovered, the etiological variability and the heterogeneous clinical presentation, the need for genotype — along with phenotype- based diagnosis of individual patients has become a requisite. In this review we look at recent advancements in genomic analysis and their translation into clinical practice

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

Relative amino acid composition signatures of organisms and environments

BACKGROUND: Identifying organism-environment interactions at the molecular level is crucial to understanding how organisms adapt to and change the chemical and molecular landscape of their habitats. In this work we investigated whether relative amino acid compositions could be used as a molecular signature of an environment and whether such a signature could also be observed at the level of the cellular amino acid composition of the microorganisms that inhabit that environment. METHODOLOGIES/PRINCIPAL FINDINGS: To address these questions we collected and analyzed environmental amino acid determinations from the literature, and estimated from complete genomic sequences the global relative amino acid abundances of organisms that are cognate to the different types of environment. Environmental relative amino acid abundances clustered into broad groups (ocean waters, host-associated environments, grass land environments, sandy soils and sediments, and forest soils), indicating the presence of amino acid signatures specific for each environment. These signatures correlate to those found in organisms. Nevertheless, relative amino acid abundance of organisms was more influenced by GC content than habitat or phylogeny. CONCLUSIONS: Our results suggest that relative amino acid composition can be used as a signature of an environment. In addition, we observed that the relative amino acid composition of organisms is not highly determined by environment, reinforcing previous studies that find GC content to be the major factor correlating to amino acid composition in living organisms.AM was supported by Fundação para a Ciência e a Tecnologia, Portugal, through the postdoctoral grant SFRH/BPD/72256/2010. RA was partially supported by the Ministerio de Ciencia e Innovación (Spain) through grant BFU2010-17704, and by the Generalitat de Catalunya through a grant for research group 2009SGR809. MAS was supported in part by a grant from the US Public Health Service (RO1-GM30054). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Authors wish to thank Albert Sorribas, Enrique Herrero and Ester Vilaprinyo for critical reading of the manuscript and Ester Vilaprinyo for assistance with Wolfram Mathematica software.publishe

Preference for facial averageness: evidence for a common mechanism in human and macaque infants

Human adults and infants show a preference for average faces, which could stem from a general processing mechanism and may be shared among primates. However, little is known about preference for facial averageness in monkeys. We used a comparative developmental approach and eye-tracking methodology to assess visual attention in human and macaque infants to faces naturally varying in their distance from a prototypical face. In Experiment 1, we examined the preference for faces relatively close to or far from the prototype in 12-month-old human infants with human adult female faces. Infants preferred faces closer to the average than faces farther from it. In Experiment 2, we measured the looking time of 3-month-old rhesus macaques (Macaca mulatta) viewing macaque faces varying in their distance from the prototype. Like human infants, macaque infants looked longer to faces closer to the average. In Experiments 3 and 4, both species were presented with unfamiliar categories of faces (i.e., macaque infants tested with adult macaque faces; human infants and adults tested with infant macaque faces) and showed no prototype preferences, suggesting that the prototypicality effect is experience-dependent. Overall, the findings suggest a common processing mechanism across species, leading to averageness preferences in primates

Fastloc-GPS reveals daytime departure and arrival during long-distance migration and the use of different resting strategies in sea turtles

Determining the time of day that animals initiate and end migration, as well as variation in diel movement patterns during migration, provides insights into the types of strategy used to maximise energy efficiency and ensure successful completion of migration. However, obtaining this level of detail has been difficult for long-distance migratory marine species. Thus, we investigated whether the large volume of highly accurate locations obtained by Argos-linked Fastloc-GPS transmitters could be used to identify the time of day that adult green (n = 8 turtles, 9487 locations) and loggerhead (n = 46 turtles, 47,588 locations) sea turtles initiate and end migration, along with potential resting strategies during migration. We found that departure from and arrival at breeding, stopover and foraging sites consistently occurred during the daytime, which is consistent with previous findings suggesting that turtles might use solar visual cues for orientation. Only seven turtles made stopovers (of up to 6 days and all located close to the start or end of migration) during migration, possibly to rest and/or refuel; however, observations of day versus night speed of travel indicated that turtles might use other mechanisms to rest. For instance, turtles travelled 31% slower at night compared to day during their oceanic crossings. Furthermore, within the first 24 h of entering waters shallower than 100 m towards the end of migration, some individuals travelled 72% slower at night, repeating this behaviour intermittently (each time for a one-night duration at 3–6 day intervals) until reaching the foraging grounds. Thus, access to data-rich, highly accurate Argos-linked Fastloc-GPS provided information about differences in day versus night activity at different stages in migration, allowing us, for the first time, to compare the strategies used by a marine vertebrate with terrestrial land-based and flying species