Human Semaphorin 3 Variants Link Melanocortin Circuit Development and Energy Balance.

Hypothalamic melanocortin neurons play a pivotal role in weight regulation. Here, we examined the contribution of Semaphorin 3 (SEMA3) signaling to the development of these circuits. In genetic studies, we found 40 rare variants in SEMA3A-G and their receptors (PLXNA1-4; NRP1-2) in 573 severely obese individuals; variants disrupted secretion and/or signaling through multiple molecular mechanisms. Rare variants in this set of genes were significantly enriched in 982 severely obese cases compared to 4,449 controls. In a zebrafish mutagenesis screen, deletion of 7 genes in this pathway led to increased somatic growth and/or adiposity demonstrating that disruption of Semaphorin 3 signaling perturbs energy homeostasis. In mice, deletion of the Neuropilin-2 receptor in Pro-opiomelanocortin neurons disrupted their projections from the arcuate to the paraventricular nucleus, reduced energy expenditure, and caused weight gain. Cumulatively, these studies demonstrate that SEMA3-mediated signaling drives the development of hypothalamic melanocortin circuits involved in energy homeostasis.

Opportunities and challenges for the use of common controls in sequencing studies.

Genome-wide association studies using large-scale genome and exome sequencing data have become increasingly valuable in identifying associations between genetic variants and disease, transforming basic research and translational medicine. However, this progress has not been equally shared across all people and conditions, in part due to limited resources. Leveraging publicly available sequencing data as external common controls, rather than sequencing new controls for every study, can better allocate resources by augmenting control sample sizes or providing controls where none existed. However, common control studies must be carefully planned and executed as even small differences in sample ascertainment and processing can result in substantial bias. Here, we discuss challenges and opportunities for the robust use of common controls in high-throughput sequencing studies, including study design, quality control and statistical approaches. Thoughtful generation and use of large and valuable genetic sequencing data sets will enable investigation of a broader and more representative set of conditions, environments and genetic ancestries than otherwise possible.

KSR2 mutations are associated with obesity, insulin resistance, and impaired cellular fuel oxidation.

Kinase suppressor of Ras 2 (KSR2) is an intracellular scaffolding protein involved in multiple signaling pathways. Targeted deletion of Ksr2 leads to obesity in mice, suggesting a role in energy homeostasis. We explored the role of KSR2 in humans by sequencing 2,101 individuals with severe early-onset obesity and 1,536 controls. We identified multiple rare variants in KSR2 that disrupt signaling through the Raf-MEKERK pathway and impair cellular fatty acid oxidation and glucose oxidation in transfected cells; effects that can be ameliorated by the commonly prescribed antidiabetic drug, metformin. Mutation carriers exhibit hyperphagia in childhood, low heart rate, reduced basal metabolic rate and severe insulin resistance. These data establish KSR2 as an important regulator of energy intake, energy expenditure, and substrate utilization in humans. Modulation of KSR2-mediated effects may represent a novel therapeutic strategy for obesity and type 2 diabetes.

RAREsim: A simulation method for very rare genetic variants.

Identification of rare-variant associations is crucial to full characterization of the genetic architecture of complex traits and diseases. Essential in this process is the evaluation of novel methods in simulated data that mirror the distribution of rare variants and haplotype structure in real data. Additionally, importing real-variant annotation enables in silico comparison of methods, such as rare-variant association tests and polygenic scoring methods, that focus on putative causal variants. Existing simulation methods are either unable to employ real-variant annotation or severely under- or overestimate the number of singletons and doubletons, thereby reducing the ability to generalize simulation results to real studies. We present RAREsim, a flexible and accurate rare-variant simulation algorithm. Using parameters and haplotypes derived from real sequencing data, RAREsim efficiently simulates the expected variant distribution and enables real-variant annotations. We highlight RAREsim's utility across various genetic regions, sample sizes, ancestries, and variant classes.

Summix: A method for detecting and adjusting for population structure in genetic summary data.

Publicly available genetic summary data have high utility in research and the clinic, including prioritizing putative causal variants, polygenic scoring, and leveraging common controls. However, summarizing individual-level data can mask population structure, resulting in confounding, reduced power, and incorrect prioritization of putative causal variants. This limits the utility of publicly available data, especially for understudied or admixed populations where additional research and resources are most needed. Although several methods exist to estimate ancestry in individual-level data, methods to estimate ancestry proportions in summary data are lacking. Here, we present Summix, a method to efficiently deconvolute ancestry and provide ancestry-adjusted allele frequencies (AFs) from summary data. Using continental reference ancestry, African (AFR), non-Finnish European (EUR), East Asian (EAS), Indigenous American (IAM), South Asian (SAS), we obtain accurate and precise estimates (within 0.1%) for all simulation scenarios. We apply Summix to gnomAD v.2.1 exome and genome groups and subgroups, finding heterogeneous continental ancestry for several groups, including African/African American (∼84% AFR, ∼14% EUR) and American/Latinx (∼4% AFR, ∼5% EAS, ∼43% EUR, ∼46% IAM). Compared to the unadjusted gnomAD AFs, Summix's ancestry-adjusted AFs more closely match respective African and Latinx reference samples. Even on modern, dense panels of summary statistics, Summix yields results in seconds, allowing for estimation of confidence intervals via block bootstrap. Given an accompanying R package, Summix increases the utility and equity of public genetic resources, empowering novel research opportunities.

Zinc Supplementation Initiated Prior to or During Pregnancy Modestly Impacted Maternal Status and High Prevalence of Hypozincemia in Pregnancy and Lactation: The Women First Preconception Maternal Nutrition Trial.

BACKGROUND: Data regarding effects of small-quantity-lipid-based nutrient supplements (SQ-LNS) on maternal serum zinc concentrations (SZC) in pregnancy and lactation are limited. OBJECTIVES: The objectives of this study were to evaluate the effect of preconception compared with prenatal zinc supplementation (compared with control) on maternal SZC and hypozincemia during pregnancy and early lactation in women in low-resource settings, and assess associations with birth anthropometry. METHODS: From ∼100 women/arm at each of 3 sites (Guatemala, India, and Pakistan) of the Women First Preconception Maternal Nutrition trial, we compared SZC at 12- and 34-wk gestation (n = 651 and 838, respectively) and 3-mo postpartum (n = 742) in women randomly assigned to daily SQ-LNS containing 15 mg zinc from ≥3 mo before conception (preconception, arm 1), from ∼12 wk gestation through delivery (early pregnancy, arm 2) or not at all (control, arm 3). Birth anthropometry was examined for newborns with ultrasound-determined gestational age. Statistical analyses were performed separately for each time point. RESULTS: At 12-wk gestation and 3-mo postpartum, no statistical differences in mean SZC were observed among arms. At 34-wk, mean SZC for arms 1 and 2 were significantly higher than for arm 3 (50.3, 50.8, 47.8 µg/dL, respectively; P = 0.005). Results were not impacted by correction for inflammation or albumin concentrations. Prevalence of hypozincemia at 12-wk (<56 µg/dL) was 23% in Guatemala, 26% in India, and 65% in Pakistan; at 34 wk (<50 µg/dL), 36% in Guatemala, 48% in India, and 74% in Pakistan; and at 3-mo postpartum (<66 µg/dL) 79% in Guatemala, 91% in India, and 92% in Pakistan. Maternal hypozincemia at 34-wk was associated with lower birth length-for-age Z-scores (all sites P = 0.013, Pakistan P = 0.008) and weight-for-age Z-scores (all sites P = 0.017, Pakistan P = 0.022). CONCLUSIONS: Despite daily zinc supplementation for ≥7 mo, high rates of maternal hypozincemia were observed. The association of hypozincemia with impaired fetal growth suggests widespread zinc deficiency in these settings. This trial is registered at clinicaltrials.gov as #NCT01883193.

Salmon Food-Specific Compounds and Their Metabolites Increase in Human Plasma and Are Associated with Cardiometabolic Health Indicators Following a Mediterranean-Style Diet Intervention.

BACKGROUND: Nutrimetabolomics allows for the comprehensive analysis of foods and human biospecimens to identify biomarkers of intake and begin to probe their associations with health. Salmon contains hundreds of compounds that may provide cardiometabolic benefits. OBJECTIVES: We used untargeted metabolomics to identify salmon food-specific compounds (FSCs) and their predicted metabolites that were found in plasma after a salmon-containing Mediterranean-style (MED) diet intervention. Associations between changes in salmon FSCs and changes in cardiometabolic health indicators (CHIs) were also explored. METHODS: For this secondary analysis of a randomized, crossover, controlled feeding trial, 41 participants consumed MED diets with 2 servings of salmon per week for 2 5-wk periods. CHIs were assessed, and fasting plasma was collected pre- and postintervention. Plasma, salmon, and 99 MED foods were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Compounds were characterized as salmon FSCs if detected in all salmon replicates but none of the other foods. Metabolites of salmon FSCs were predicted using machine learning. For salmon FSCs and metabolites found in plasma, linear mixed-effect models were used to assess change from pre- to postintervention and associations with changes in CHIs. RESULTS: Relative to the other 99 MED foods, there were 508 salmon FSCs with 237 unique metabolites. A total of 143 salmon FSCs and 106 metabolites were detected in plasma. Forty-eight salmon FSCs and 30 metabolites increased after the intervention (false discovery rate <0.05). Increases in 2 annotated salmon FSCs and 2 metabolites were associated with improvements in CHIs, including total cholesterol, low-density lipoprotein cholesterol, triglycerides, and apolipoprotein B. CONCLUSIONS: A data-driven nutrimetabolomics strategy identified salmon FSCs and their predicted metabolites that were detectable in plasma and changed after consumption of a salmon-containing MED diet. Findings support this approach for the discovery of compounds in foods that may serve, upon further validation, as biomarkers or act as bioactive components influential to health. The trials supporting this work were registered at NCT02573129 (Mediterranean-style diet intervention) and NCT05500976 (ongoing clinical trial).

Genetic architecture of human thinness compared to severe obesity.

The variation in weight within a shared environment is largely attributable to genetic factors. Whilst many genes/loci confer susceptibility to obesity, little is known about the genetic architecture of healthy thinness. Here, we characterise the heritability of thinness which we found was comparable to that of severe obesity (h2 = 28.07 vs 32.33% respectively), although with incomplete genetic overlap (r = -0.49, 95% CI [-0.17, -0.82], p = 0.003). In a genome-wide association analysis of thinness (n = 1,471) vs severe obesity (n = 1,456), we identified 10 loci previously associated with obesity, and demonstrate enrichment for established BMI-associated loci (pbinomial = 3.05x10-5). Simulation analyses showed that different association results between the extremes were likely in agreement with additive effects across the BMI distribution, suggesting different effects on thinness and obesity could be due to their different degrees of extremeness. In further analyses, we detected a novel obesity and BMI-associated locus at PKHD1 (rs2784243, obese vs. thin p = 5.99x10-6, obese vs. controls p = 2.13x10-6 pBMI = 2.3x10-13), associations at loci recently discovered with much larger sample sizes (e.g. FAM150B and PRDM6-CEP120), and novel variants driving associations at previously established signals (e.g. rs205262 at the SNRPC/C6orf106 locus and rs112446794 at the PRDM6-CEP120 locus). Our ability to replicate loci found with much larger sample sizes demonstrates the value of clinical extremes and suggest that characterisation of the genetics of thinness may provide a more nuanced understanding of the genetic architecture of body weight regulation and may inform the identification of potential anti-obesity targets.

The UK10K project identifies rare variants in health and disease.

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.

ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls.

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.

Improved first trimester maternal iodine status with preconception supplementation: The Women First Trial.

Maternal iodine (I) status is critical in embryonic and foetal development. We examined the effect of preconception iodine supplementation on maternal iodine status and on birth outcomes. Non-pregnant women in Guatemala, India and Pakistan (n ~ 100 per arm per site) were randomized ≥ 3 months prior to conception to one of three intervention arms: a multimicronutrient-fortified lipid-based nutrient supplement containing 250-µg I per day started immediately after randomization (Arm 1), the same supplement started at ~12 weeks gestation (Arm 2) and no intervention supplement (Arm 3). Urinary I (µg/L) to creatinine (mg/dl) ratios (I/Cr) were determined at 12 weeks for Arm 1 versus Arm 2 (before supplement started) and 34 weeks for all arms. Generalized linear models were used to assess the relationship of I/Cr with arm and with newborn anthropometry. At 12 weeks gestation, adjusted mean I/Cr (µg/g) for all sites combined was significantly higher for Arm 1 versus Arm 2: (203 [95% CI: 189, 217] vs. 163 [95% CI: 152, 175], p < 0.0001). Overall adjusted prevalence of I/Cr < 150 µg/g was also lower in Arm 1 versus Arm 2: 32% (95% CI: 26%, 38%) versus 43% (95% CI: 37%, 49%) (p = 0.0052). At 34 weeks, adjusted mean I/Cr for Arm 1 (235, 95% CI: 220, 252) and Arm 2 (254, 95% CI: 238, 272) did not differ significantly but were significantly higher than Arm 3 (200, 95% CI: 184, 218) (p < 0.0001). Nominally significant positive associations were observed between I/Cr at 12 weeks and birth length and head circumference z-scores (p = 0.028 and p = 0.005, respectively). These findings support the importance of first trimester iodine status and suggest need for preconception supplementation beyond salt iodization alone.

Insight into genetic regulation of miRNA in mouse brain.

BACKGROUND: micro RNA (miRNA) are important regulators of gene expression and may influence phenotypes and disease traits. The connection between genetics and miRNA expression can be determined through expression quantitative loci (eQTL) analysis, which has been extensively used in a variety of tissues, and in both human and model organisms. miRNA play an important role in brain-related diseases, but eQTL studies of miRNA in brain tissue are limited. We aim to catalog miRNA eQTL in brain tissue using miRNA expression measured on a recombinant inbred mouse panel. Because samples were collected without any intervention or treatment (naïve), the panel allows characterization of genetic influences on miRNAs' expression levels. We used brain RNA expression levels of 881 miRNA and 1416 genomic locations to identify miRNA eQTL. To address multiple testing, we employed permutation p-values and subsequent zero permutation p-value correction. We also investigated the underlying biology of miRNA regulation using additional analyses, including hotspot analysis to search for regions controlling multiple miRNAs, and Bayesian network analysis to identify scenarios where a miRNA mediates the association between genotype and mRNA expression. We used addiction related phenotypes to illustrate the utility of our results. RESULTS: Thirty-eight miRNA eQTL were identified after appropriate multiple testing corrections. Ten of these miRNAs had target genes enriched for brain-related pathways and mapped to four miRNA eQTL hotspots. Bayesian network analysis revealed four biological networks relating genetic variation, miRNA expression and gene expression. CONCLUSIONS: Our extensive evaluation of miRNA eQTL provides valuable insight into the role of miRNA regulation in brain tissue. Our miRNA eQTL analysis and extended statistical exploration identifies miRNA candidates in brain for future study.

Different Growth Patterns Persist at 24 Months of Age in Formula-Fed Infants Randomized to Consume a Meat- or Dairy-Based Complementary Diet from 5 to 12 Months of Age.

OBJECTIVE: To test the long-term effect on growth status at 24 months of age in formula-fed infants who were randomized to consume a meat- or dairy-based complementary diet from 5 to 12 months of age. STUDY DESIGN: Observational assessments, including anthropometric, dietary, and blood biomarkers, were conducted at 24 months of age, 1 year after the intervention ended. RESULTS: The retention rate at 24 months of age was 84% for the meat group and 81% for the dairy group. Mean (±SD) protein intakes at 24 months of age were 4.1 ± 1.2 and 4.0 ± 1.1 g/kmeat (n = 27) and dairy (n = 26) groups, respectively, and comparable with the estimates of US population intake. At 24 months of age, weight-for-age z score did not differ significantly between groups and was similar to that at 12 months. Length-for-age z score remained significantly higher in the meat group compared with the dairy group, and the average length was 1.9 cm greater in the meat group. Weight-for-length z score also did not differ significantly between groups. Insulin-like growth factor 1 significantly increased from 12 to 24 months of age in both groups, but insulin-like growth factor-binding protein 3 and blood urea nitrogen did not change significantly from 12 to 24 months of age and were comparable between groups. CONCLUSIONS: The protein source-induced distinctive growth patterns observed during infancy persisted at 24 months of age, suggesting a potential long-term impact of early protein quality on growth trajectories in formula-fed infants. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02142647.

Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes.

Genome-wide association studies (GWAS) have uncovered many genetic associations for cardiovascular disease (CVD). However, data are limited regarding causal genetic variants within implicated loci. We sought to identify regulatory variants (cis- and trans-eQTLs) affecting expression levels of 93 genes selected by their proximity to SNPs with significant associations in prior GWAS for CVD traits. Expression levels were measured by qRT-PCR in leukocytes from 1846 Framingham Heart Study participants. An additive genetic model was applied to 2.5 million imputed SNPs for each gene. Approximately 45% of genes (N = 38) harbored at least one cis-eSNP after a regional multiple-test adjustment. Applying a more rigorous significance threshold (P < 5 × 10(-8)), we found the expression level of 10 genes was significantly associated with more than one cis-eSNP. The top cis-eSNPs for 7 of these 10 genes exhibited moderate-to-strong association with ≥ 1 CVD clinical phenotypes. Several eSNPs or proxy SNPs (r(2) = 1) were replicated by other eQTL studies. After adjusting for the lead GWAS SNPs for the 10 genes, expression variances explained by top cis-eSNPs were attenuated markedly for LPL, FADS2 and C6orf184, suggesting a shared genetic basis for the GWAS and expression trait. A significant association between cis-eSNPs, gene expression and lipid levels was discovered for LPL and C6orf184. In conclusion, strong cis-acting variants are localized within nearly half of the GWAS loci studied, with particularly strong evidence for a regulatory role of the top GWAS SNP for expression of LPL, FADS2 and C6orf184.

Progress in methods for rare variant association.

Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, methods for rare variant association have been an active area of research for the past decade. Here, we provide a survey of the current literature and developments from the Genetics Analysis Workshop 19 (GAW19) Collapsing Rare Variants working group. In particular, we present the generalized linear regression framework and associated score statistic for the 2 major types of methods: burden and variance components methods. We further show that by simply modifying weights within these frameworks we arrive at many of the popular existing methods, for example, the cohort allelic sums test and sequence kernel association test. Meta-analysis techniques are also described. Next, we describe the 6 contributions from the GAW19 Collapsing Rare Variants working group. These included development of new methods, such as a retrospective likelihood for family data, a method using genomic structure to compare cases and controls, a haplotype-based meta-analysis, and a permutation-based method for combining different statistical tests. In addition, one contribution compared a mega-analysis of family-based and population-based data to meta-analysis. Finally, the power of existing family-based methods for binary traits was compared. We conclude with suggestions for open research questions.

Characterizing substructure via mixture modeling in large-scale genetic summary statistics.

Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.

mini-MED: study protocol for a randomized, multi-intervention, semi-controlled feeding trial of a Mediterranean-amplified vs. habitual Western dietary pattern for the evaluation of food-specific compounds and cardiometabolic health.

BACKGROUND: Diet is among the most influential lifestyle factors impacting chronic disease risk. Nutrimetabolomics, the application of metabolomics to nutrition research, allows for the detection of food-specific compounds (FSCs) that can be used to connect dietary patterns, such as a Mediterranean-style (MED) diet, to health. This validation study is based upon analyses from a controlled feeding MED intervention, where our team identified FSCs from eight foods that can be detected in biospecimens after consumption and may therefore serve as food intake biomarkers. METHODS: Individuals with overweight/obesity who do not habitually consume a MED dietary pattern will complete a 16-week randomized, multi-intervention, semi-controlled feeding study of isocaloric dietary interventions: (1) MED-amplified dietary pattern, containing 500 kcal/day from eight MED target foods: avocado, basil, cherry, chickpea, oat, red bell pepper, walnut, and a protein source (alternating between salmon or unprocessed, lean beef), and (2) habitual/Western dietary pattern, containing 500 kcal/day from six non-MED target foods: cheesecake, chocolate frozen yogurt, refined grain bread, sour cream, white potato, and unprocessed, lean beef. After a 2-week washout, participants complete four, 4-week intervention periods, with biospecimen sampling and outcome assessments at baseline and at intervention weeks 4, 8, 12, and 16. The primary outcome is change in the relative abundance of FSCs from the eight MED target foods in participant biospecimens from baseline to the end of each intervention period. Secondary outcomes include mean change in cardiometabolic health indicators, inflammatory markers, and adipokines. Exploratory outcomes include change in diversity and community composition of the gut microbiota. DISCUSSION: Our stepwise strategy, beginning with identification of FSCs in whole diets and biospecimens, followed by relating these to health indicators will lead to improved methodology for assessment of dietary patterns and a better understanding of the relationship between food and health. This study will serve as a first step toward validating candidate food intake biomarkers and allow for assessment of relationships with cardiometabolic health. The identification of food intake biomarkers is critical to future research and has implications spanning health promotion and disease prevention for many chronic conditions. TRIAL REGISTRATION: Registered at ClinicalTrials.gov: NCT05500976 ; Date of registration: August 15, 2022.

HLA-DPB1*13:01 associates with enhanced, and KIR2DS4*001 with diminished protection from developing severe COVID-19.

Extreme polymorphism of HLA and killer-cell immunoglobulin-like receptors (KIR) differentiates immune responses across individuals. Additional to T cell receptor interactions, subsets of HLA class I act as ligands for inhibitory and activating KIR, allowing natural killer (NK) cells to detect and kill infected cells. We investigated the impact of HLA and KIR polymorphism on the severity of COVID-19. High resolution HLA class I and II and KIR genotypes were determined from 403 non-hospitalized and 1575 hospitalized SARS-CoV-2 infected patients from Italy collected in 2020. We observed that possession of the activating KIR2DS4*001 allotype is associated with severe disease, requiring hospitalization (OR = 1.48, 95% CI 1.20-1.85, pc = 0.017), and this effect is greater in individuals homozygous for KIR2DS4*001 (OR = 3.74, 95% CI 1.75-9.29, pc = 0.003). We also observed the HLA class II allotype, HLA-DPB1*13:01 protects SARS-CoV-2 infected patients from severe disease (OR = 0.49, 95% CI 0.33-0.74, pc = 0.019). These association analyses were replicated using logistic regression with sex and age as covariates. Autoantibodies against IFN-α associated with COVID-19 severity were detected in 26% of 156 hospitalized patients tested. HLA-C*08:02 was more frequent in patients with IFN-α autoantibodies than those without, and KIR3DL1*01502 was only present in patients lacking IFN-α antibodies. These findings suggest that KIR and HLA polymorphism is integral in determining the clinical outcome following SARS-CoV-2 infection, by influencing the course both of innate and adaptive immunity.

Maternal nutritional status modifies heat-associated growth restriction in women with chronic malnutrition.

Rapid changes in the global climate are deepening existing health disparities from resource scarcity and malnutrition. Rising ambient temperatures represent an imminent risk to pregnant women and infants. Both maternal malnutrition and heat stress during pregnancy contribute to poor fetal growth, the leading cause of diminished child development in low-resource settings. However, studies explicitly examining interactions between these two important environmental factors are lacking. We leveraged maternal and neonatal anthropometry data from a randomized controlled trial focused on improving preconception maternal nutrition (Women First Preconception Nutrition trial) conducted in Thatta, Pakistan, where both nutritional deficits and heat stress are prevalent. Multiple linear regression of ambient temperature and neonatal anthropometry at birth (n = 459) showed a negative association between daily maximal temperatures in the first trimester and Z-scores of birth length and head circumference. Placental mRNA-sequencing and protein analysis showed transcriptomic changes in protein translation, ribosomal proteins, and mTORC1 signaling components in term placenta exposed to excessive heat in the first trimester. Targeted metabolomic analysis indicated ambient temperature associated alterations in maternal circulation with decreases in choline concentrations. Notably, negative impacts of heat on birth length were in part mitigated in women randomized to comprehensive maternal nutritional supplementation before pregnancy suggesting potential interactions between heat stress and nutritional status of the mother. Collectively, the findings bridge critical gaps in our current understanding of how maternal nutrition may provide resilience against adverse effects of heat stress in pregnancy.

TAA repeat variation in the GRIK2 gene does not influence age at onset in Huntington's disease.

Huntington's disease is a neurodegenerative disorder caused by an expanded CAG trinucleotide repeat whose length is the major determinant of age at onset but remaining variation appears to be due in part to the effect of genetic modifiers. GRIK2, which encodes GluR6, a mediator of excitatory neurotransmission in the brain, has been suggested in several studies to be a modifier gene based upon a 3' untranslated region TAA trinucleotide repeat polymorphism. Prior to investing in detailed studies of the functional impact of this polymorphism, we sought to confirm its effect on age at onset in a much larger dataset than in previous investigations. We genotyped the HD CAG repeat and the GRIK2 TAA repeat in DNA samples from 2,911 Huntington's disease subjects with known age at onset, and tested for a potential modifier effect of GRIK2 using a variety of statistical approaches. Unlike previous reports, we detected no evidence of an influence of the GRIK2 TAA repeat polymorphism on age at motor onset. Similarly, the GRIK2 polymorphism did not show significant modifier effect on psychiatric and cognitive age at onset in HD. Comprehensive analytical methods applied to a much larger sample than in previous studies do not support a role for GRIK2 as a genetic modifier of age at onset of clinical symptoms in Huntington's disease.