Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification

Connective tissue disease related interstitial lung diseases and idiopathic pulmonary fibrosis: provisional core sets of domains and instruments for use in clinical trials

Rationale Clinical trial design in interstitial lung diseases (ILDs) has been hampered by lack of consensus on appropriate outcome measures for reliably assessing treatment response. In the setting of connective tissue diseases (CTDs), some measures of ILD disease activity and severity may be confounded by non-pulmonary comorbidities. Methods The Connective Tissue Disease associated Interstitial Lung Disease (CTD-ILD) working group of Outcome Measures in Rheumatology—a non-profit international organisation dedicated to consensus methodology in identification of outcome measures—conducted a series of investigations which included a Delphi process including >248 ILD medical experts as well as patient focus groups culminating in a nominal group panel of ILD experts and patients. The goal was to define and develop a consensus on the status of outcome measure candidates for use in randomised controlled trials in CTD-ILD and idiopathic pulmonary fibrosis (IPF). Results A core set comprising specific measures in the domains of lung physiology, lung imaging, survival, dyspnoea, cough and health-related quality of life is proposed as appropriate for consideration for use in a hypothetical 1-year multicentre clinical trial for either CTD-ILD or IPF. As many widely used instruments were found to lack full validation, an agenda for future research is proposed. Conclusion Identification of consensus preliminary domains and instruments to measure them was attained and is a major advance anticipated to facilitate multicentre RCTs in the field

Search for the Weak Decay of an H Dibaryon

We have searched for a neutral $H$ dibaryon decaying via $H\to\Lambda n$ and $H\to\Sigma^0 n$. Our search has yielded two candidate events from which we set an upper limit on the $H$ production cross section. Normalizing to the inclusive $\Lambda$ production cross section, we find $(d\sigma_H/d\Omega) / (d\sigma_\Lambda/d\Omega) < 6.3\times 10^{-6}$ at 90% C.L., for an $H$ of mass $\approx$ 2.15 GeV/$c^2$.Comment: 11 pages, 6 postscript figures, epsfig, aps, preprint, revte

Cerebral Microdialysate Metabolite Monitoring using Mid-infrared Spectroscopy.

Funder: Wellcome TrustThe brains of patients suffering from traumatic brain-injury (TBI) undergo dynamic chemical changes in the days following the initial trauma. Accurate and timely monitoring of these changes is of paramount importance for improved patient outcome. Conventional brain-chemistry monitoring is performed off-line by collecting and manually transferring microdialysis samples to an enzymatic colorimetric bedside analyzer every hour, which detects and quantifies the molecules of interest. However, off-line, hourly monitoring means that any subhourly neurochemical changes, which may be detrimental to patients, go unseen and thus untreated. Mid-infrared (mid-IR) spectroscopy allows rapid, reagent-free, molecular fingerprinting of liquid samples, and can be easily integrated with microfluidics. We used mid-IR transmission spectroscopy to analyze glucose, lactate, and pyruvate, three relevant brain metabolites, in the extracellular brain fluid of two TBI patients, sampled via microdialysis. Detection limits of 0.5, 0.2, and 0.1 mM were achieved for pure glucose, lactate, and pyruvate, respectively, in perfusion fluid using an external cavity-quantum cascade laser (EC-QCL) system with an integrated transmission flow-cell. Microdialysates were collected hourly, then pooled (3-4 h), and measured consecutively using the standard ISCUSflex analyzer and the EC-QCL system. There was a strong correlation between the compound concentrations obtained using the conventional bedside analyzer and the acquired mid-IR absorbance spectra, where a partial-least-squares regression model was implemented to compute concentrations. This study demonstrates the potential utility of mid-IR spectroscopy for continuous, automated, reagent-free, and online monitoring of the dynamic chemical changes in TBI patients, allowing a more timely response to adverse brain metabolism and consequently improving patient outcomes

Natural Selection of Immune and Metabolic Genes Associated with Health in Two Lowland Bolivian Populations

A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype–phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF &lt;5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants