The Multiscale Backbone of the Human Phenotype Network Based on Biological Pathways

Background: Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. Results: The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. Conclusions: We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases’ common biology, and in the elaboration of diagnosis and treatments

Swirls and scoops: Ice base melt revealed by multibeam imagery of an Antarctic ice shelf

Knowledge gaps about how the ocean melts Antarctica’s ice shelves, borne from a lack of observations, lead to large uncertainties in sea level predictions. Using high-resolution maps of the underside of Dotson Ice Shelf, West Antarctica, we reveal the imprint that ice shelf basal melting leaves on the ice. Convection and intermittent warm water intrusions form widespread terraced features through slow melting in quiescent areas, while shear-driven turbulence rapidly melts smooth, eroded topographies in outflow areas, as well as enigmatic teardrop-shaped indentations that result from boundary-layer flow rotation. Full-thickness ice fractures, with bases modified by basal melting and convective processes, are observed throughout the area. This new wealth of processes, all active under a single ice shelf, must be considered to accurately predict future Antarctic ice shelf melt

Evolutionary Triangulation: Informing Genetic Association Studies with Evolutionary Evidence

Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disease, and ignored other factors for evaluation. For example, evolution is a factor that has shaped disease risk, changing allele frequencies as human populations migrated into and inhabited new environments. Since many common variants differ among populations in frequency, as does disease prevalence, we hypothesized that patterns of disease and population structure, taken together, will inform association studies. Thus, the population distributions of allelic risk variants should reflect the distributions of their associated diseases. Evolutionary Triangulation (ET) exploits this evolutionary differentiation by comparing population structure among three populations with variable patterns of disease prevalence. By selecting populations based on patterns where two have similar rates of disease that differ substantially from a third, we performed a proof of principle analysis for this method. We examined three disease phenotypes, lactase persistence, melanoma, and Type 2 diabetes mellitus. We show that for lactase persistence, a phenotype with a simple genetic architecture, ET identifies the key gene, lactase. For melanoma, ET identifies several genes associated with this disease and/or phenotypes related to it, such as skin color genes. ET was less obviously successful for Type 2 diabetes mellitus, perhaps because of the small effect sizes in known risk loci and recent environmental changes that have altered disease risk. Alternatively, ET may have revealed new genes involved in conferring disease risk for diabetes that did not meet nominal GWAS significance thresholds. We also compared ET to another method used to filter for phenotype associated genes, population branch statistic (PBS), and show that ET performs better in identifying genes known to associate with diseases appropriately distributed among populations. Our results indicate that ET can filter association results to improve our ability to discover disease loci

The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

BackgroundAs global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease’s etiology and response to drugs. ObjectiveWe designed the Alzheimer’s Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics. MethodsWe designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base. ResultsAlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones. ConclusionsAlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge

Correction: Whole exome sequencing reveals HSPA1L as a genetic risk factor for spontaneous preterm birth.

[This corrects the article DOI: 10.1371/journal.pgen.1007394.]

Whole exome sequencing reveals <i>HSPA1L</i> as a genetic risk factor for spontaneous preterm birth

<div><p>Preterm birth is a leading cause of morbidity and mortality in infants. Genetic and environmental factors play a role in the susceptibility to preterm birth, but despite many investigations, the genetic basis for preterm birth remain largely unknown. Our objective was to identify rare, possibly damaging, nucleotide variants in mothers from families with recurrent spontaneous preterm births (SPTB). DNA samples from 17 Finnish mothers who delivered at least one infant preterm were subjected to whole exome sequencing. All mothers were of northern Finnish origin and were from seven multiplex families. Additional replication samples of European origin consisted of 93 Danish sister pairs (and two sister triads), all with a history of a preterm delivery. Rare exonic variants (frequency <1%) were analyzed to identify genes and pathways likely to affect SPTB susceptibility. We identified rare, possibly damaging, variants in genes that were common to multiple affected individuals. The glucocorticoid receptor signaling pathway was the most significant (p<1.7e-8) with genes containing these variants in a subgroup of ten Finnish mothers, each having had 2–4 SPTBs. This pathway was replicated among the Danish sister pairs. A gene in this pathway, heat shock protein family A (Hsp70) member 1 like (<i>HSPA1L</i>), contains two likely damaging missense alleles that were found in four different Finnish families. One of the variants (rs34620296) had a higher frequency in cases compared to controls (0.0025 <i>vs</i>. 0.0010, p = 0.002) in a large preterm birth genome-wide association study (GWAS) consisting of mothers of general European ancestry. Sister pairs in replication samples also shared rare, likely damaging <i>HSPA1L</i> variants. Furthermore, <i>in silico</i> analysis predicted an additional phosphorylation site generated by rs34620296 that could potentially affect chaperone activity or HSPA1L protein stability. Finally, <i>in vitro</i> functional experiment showed a link between HSPA1L activity and decidualization. In conclusion, rare, likely damaging, variants in <i>HSPA1L</i> were observed in multiple families with recurrent SPTB.</p></div

Pathway results for Danish sister pairs (n = 93); showing only genes related to the Discovery findings.

<p>Pathway results for Danish sister pairs (n = 93); showing only genes related to the Discovery findings.</p

Effects of <i>HSPA1L</i> variants on protein sequence and structure.

<p>(A) HSPA1L is a 641-amino acid protein that consist of two major functional domains; an N-terminal nucleotide-binding domain and a C-terminal substrate-binding domain, that are connected with interdomain linker. Locations of four <i>HSPA1L</i> variants from whole exome sequencing (Discovery and Replication findings) are shown in the protein sequence. Purple diamonds represent ATP nucleotide-binding sites at positions 14−17, 204−206, 270−277 and 341−344. Green circles denote the additional phosphorylation site generated by Ala268Thr and the existing one T267-p. (B) <i>In silico</i> comparison of higher order assembly of reference and modified (Ala268Thr) HSPA1L protein models containing an ADP molecule. Overlayed reference and Ala268Thr molecules are presented as gold and light blue rounded ribbon structures, respectively. The interacting ADP molecule is shown as a stick model. (C) Closeup view of the intermolecular contact interface of HSPA1L bound to the ADP molecule. Key interacting residues (amino acids) are shown and their corresponding side chains are presented as stick molecules; nitrogen and oxygen atoms are indicated in blue and red, respectively. All interacting residues; THR16, TYR17, GLU270, LYS273, ARG274, SER277 (not shown in figure) and ASP368, that bind to the ADP ligand showed small changes in the chemical bond lengths. Only changes of ≥0.002Å are shown in the figure (+/- lenght of Ala268Thr structure in relation to reference structure).</p

HSPA1L and GR protein levels in decidualized human endometrial stromal fibroblasts.

<p>Cultured ESFs were transfected with WT or Ala268Thr <i>HSPA1L</i>-pcDNA3.1 constructs or with empty pcDNA3.1 vector (control). Cells were treated with decidualization media supplemented with 100nM dexamethasone (glucocorticoids) for 72h. Both cytosolic and nuclear protein were extracted, and HSPA1L and GR protein levels were measured by Western blot. Band intensity of HSPA1L or GR was normalized to band intensity of the corresponding β-actin. Cytosolic (A) and nuclear (B) HSPA1L levels as well as cytosolic (C) and nuclear (D) GR levels are shown for control (empty vector), WT and Ala268Thr sample groups. Each experiment was performed as triplicates in three different passages (n = 9 each group, except n = 8 for nuclear control group) and bars represent mean + SEM. Significant p-value <0.05 is presented with an asterisk. Cytosolic GR levels were significantly higher (p = 0.04) in the WT compared to the Ala268Thr group as well as in the WT compared to the control group (p = 0.04).</p