Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Localizing Brain Regions Associated with Female Mate Preference Behavior in a Swordtail

Female mate choice behavior is a critical component of sexual selection, yet identifying the neural basis of this behavior is largely unresolved. Previous studies have implicated sensory processing and hypothalamic brain regions during female mate choice and there is a conserved network of brain regions (Social Behavior Network, SBN) that underlies sexual behaviors. However, we are only beginning to understand the role this network has in pre-copulatory female mate choice. Using in situ hybridization, we identify brain regions associated with mate preference in female Xiphophorus nigrensis, a swordtail species with a female choice mating system. We measure gene expression in 10 brain regions (linked to sexual behavior, reward, sensory integration or other processes) and find significant correlations between female preference behavior and gene expression in two telencephalic areas associated with reward, learning and multi-sensory processing (medial and lateral zones of the dorsal telencephalon) as well as an SBN region traditionally associated with sexual response (preoptic area). Network analysis shows that these brain regions may also be important in mate preference and that correlated patterns of neuroserpin expression between regions co-vary with differential compositions of the mate choice environment. Our results expand the emerging network for female preference from one that focused on sensory processing and midbrain sexual response centers to a more complex coordination involving forebrain areas that integrate primary sensory processing and reward.This work was funded by research fellowships from the University of Texas (UT) Ecology, Evolution and Behavior graduate program (to RYW), along with a Reeder Fellowship, UT SRA, UT StartUp funds, National Science Foundation SGER IOS-0813742 and IOS-0843000 (to MEC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Suicide-related care among patients who have experienced an opioid-involved overdose

OBJECTIVE: Our objective was to describe suicide prevention care for individuals prescribed opioids or with opioid use disorder (OUD) and identify opportunities for improving this care. METHODS: Adult patients (n = 65) from four health systems with an opioid-involved overdose and clinicians (n = 21) who had contact with similar patients completed 30-60-min semi-structured interviews. A community advisory board contributed to development of all procedures, and interpretation and summary of findings. RESULTS: Patients were mostly female (59%), White (63%) and non-Hispanic (77%); 52 were prescribed opioids, 49% had diagnosed OUD, and 42% experienced an intentional opioid-involved overdose. Findings included: 1) when prescribed an opioid or treated for OUD, suicide risks were typically not discussed; 2) 35% of those with an intentional opioid-involved overdose and over 80% with an unintentional overdose reported no discussion of suicidal ideation when treated for the overdose; and 3) suicide-related follow-up care was uncommon among those with unintentional overdoses despite suicidal ideation being reported by \u3e20%. Clinicians reported that when prescribing opioids or treating OUD, post-overdose suicide-related screening or counseling was not done routinely. CONCLUSIONS: There were several opportunities to tailor suicide prevention care for patients who were treated for opioid-involved overdoses within health systems

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges

Since their earliest days, humans have been struggling with infectious diseases. Caused by viruses, bacteria, protozoa, or even higher organisms like worms, these diseases depend critically on numerous intricate interactions between parasites and hosts, and while we have learned much about these interactions, many details are still obscure. It is evident that the combined host-parasite dynamics constitutes a complex system that involves components and processes at multiple scales of time, space, and biological organization. At one end of this hierarchy we know of individual molecules that play crucial roles for the survival of a parasite or for the response and survival of its host. At the other end, one realizes that the spread of infectious diseases by far exceeds specific locales and, due to today's easy travel of hosts carrying a multitude of organisms, can quickly reach global proportions. The community of mathematical modelers has been addressing specific aspects of infectious diseases for a long time. Most of these efforts have focused on one or two select scales of a multi-level disease and used quite different computational approaches. This restriction to a molecular, physiological, or epidemiological level was prudent, as it has produced solid pillars of a foundation from which it might eventually be possible to launch comprehensive, multi-scale modeling efforts that make full use of the recent advances in biology and, in particular, the various high-throughput methodologies accompanying the emerging –omics revolution. This special issue contains contributions from biologists and modelers, most of whom presented and discussed their work at the workshop From within Host Dynamics to the Epidemiology of Infectious Disease, which was held at the Mathematical Biosciences Institute at Ohio State University in April 2014. These contributions highlight some of the forays into a deeper understanding of the dynamics between parasites and their hosts, and the consequences of this dynamics for the spread and treatment of infectious diseases