Plasma protein signatures of adult asthma.

BACKGROUND: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma. METHODS: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)). RESULTS: Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis. CONCLUSION: This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation.

BACKGROUND: Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS). METHODS: We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C). FINDINGS: Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs. INTERPRETATION: Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases. FUNDING: Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex.

Background: Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Methods: Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data. Results: At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations. Conclusions: Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Early-life farm exposures and eczema among adults in the Agricultural Lung Health Study.

Background: Several studies conducted in Europe have suggested a protective association between early-life farming exposures and childhood eczema or atopic dermatitis; few studies have examined associations in adults. Objectives: To investigate associations between early-life exposures and eczema among 3217 adult farmers and farm spouses (mean age 62.8 years) in a case-control study nested within an US agricultural cohort. Methods: We used sampling-weighted logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for associations between early-life exposures and self-reported doctor-diagnosed eczema (273 cases) and polytomous logistic regression to estimate ORs (95%CIs) for a 4-level outcome combining information on eczema and atopy (specific IgE≥0.35). Additionally, we explored genetic and gene-environment associations with eczema. Results: Although early-life farming exposures were not associated with eczema overall, several early-life exposures were associated with a reduced risk of having both eczema and atopy. Notably, results suggest stronger protective associations among individuals with both eczema and atopy than among those with either atopy alone or eczema alone. For example, ORs (95%CIs) for having a mother who did farm work while pregnant were 1.01 (0.60-1.69) for eczema alone and 0.80 (0.65-0.99) for atopy alone, but 0.54 (0.33-0.80) for having both eczema and atopy. A genetic risk score based on previously identified atopic dermatitis variants was strongly positively associated with eczema, and interaction testing suggested protective effects of several early-life farming exposures only in individuals at lower genetic risk. Conclusions: In utero and childhood farming exposures are associated with decreased odds of having eczema with atopy in adults.

Residential Wood Burning and Pulmonary Function in the Agricultural Lung Health Study.

BACKGROUND: In low- and middle-income countries, burning biomass indoors for cooking or heating has been associated with poorer lung function. In high-income countries, wood, a form of biomass, is commonly used for heating in rural areas with increasing prevalence. However, in these settings the potential impact of chronic indoor woodsmoke exposure on pulmonary function is little studied. OBJECTIVE: We evaluated the association of residential wood burning with pulmonary function in case-control study of asthma nested within a U.S. rural cohort. METHODS: Using sample weighted multivariable linear regression, we estimated associations between some and frequent wood burning, both relative to no exposure, in relation to forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio (FEV1/FVC), and fractional exhaled nitric oxide (FeNO). We examined effect modification by smoking or asthma status. RESULTS: Among all participants and within smoking groups, wood burning was not appreciably related to pulmonary function. However, in individuals with asthma (n=1,083), frequent wood burning was significantly associated with lower FEV1 [ß: -164mL; 95% confidence interval (CI): -261, -66mL], FVC (ß: -125mL; 95% CI: -230, -20mL), and FEV1/FVC (ß: -2%; 95% CI: -4, -0.4%), whereas no appreciable association was seen in individuals without asthma (n=1,732). These differences in association by asthma were statistically significant for FEV1 (pinteraction=0.0044) and FEV1/FVC (pinteraction=0.049). Frequent wood burning was also associated with higher FeNO levels in all individuals (n=2,598; ß: 0.1 ln(ppb); 95% CI: 0.02, 0.2), but associations did not differ by asthma or smoking status. DISCUSSION: Frequent exposure to residential wood burning was associated with a measure of airway inflammation (FeNO) among all individuals and with lower pulmonary function among individuals with asthma. This group may wish to reduce wood burning or consider using air filtration devices. https://doi.org/10.1289/EHP10734.

Epigenome-Wide DNA Methylation and Pesticide Use in the Agricultural Lung Health Study.

BACKGROUND: Pesticide exposure is associated with many long-term health outcomes; the potential underlying mechanisms are not well established for most associations. Epigenetic modifications, such as DNA methylation, may contribute. Individual pesticides may be associated with specific DNA methylation patterns but no epigenome-wide association study (EWAS) has evaluated methylation in relation to individual pesticides. OBJECTIVES: We conducted an EWAS of DNA methylation in relation to several pesticide active ingredients. METHODS: The Agricultural Lung Health Study is a case-control study of asthma, nested within the Agricultural Health Study. We analyzed blood DNA methylation measured using Illumina's EPIC array in 1,170 male farmers of European ancestry. For pesticides still on the market at blood collection (2009-2013), we evaluated nine active ingredients for which at least 30 participants reported past and current (within the last 12 months) use, as well as seven banned organochlorines with at least 30 participants reporting past use. We used robust linear regression to compare methylation at individual C-phosphate-G sites (CpGs) among users of a specific pesticide to never users. RESULTS: Using family-wise error rate (p<9×10-8) or false-discovery rate (FDR<0.05), we identified 162 differentially methylated CpGs across 8 of 9 currently marketed active ingredients (acetochlor, atrazine, dicamba, glyphosate, malathion, metolachlor, mesotrione, and picloram) and one banned organochlorine (heptachlor). Differentially methylated CpGs were unique to each active ingredient, and a dose-response relationship with lifetime days of use was observed for most. Significant CpGs were enriched for transcription motifs and 28% of CpGs were associated with whole blood cis-gene expression, supporting functional effects of findings. We corroborated a previously reported association between dichlorodiphenyltrichloroethane (banned in the United States in 1972) and epigenetic age acceleration. DISCUSSION: We identified differential methylation for several active ingredients in male farmers of European ancestry. These may serve as biomarkers of chronic exposure and could inform mechanisms of long-term health outcomes from pesticide exposure. https://doi.org/10.1289/EHP8928.

Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations.

Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation.

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies.

The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.

The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation.

Unaffected relatives of individuals with non-syndromic cleft lip with or without cleft palate (NSCL/P) show distinctive facial features. The presence of this facial endophenotype is potentially an expression of underlying genetic susceptibility to NSCL/P in the larger unselected population. To explore this hypothesis, we first partitioned the face into 63 partially overlapping regions representing global-to-local facial morphology and then defined endophenotypic traits by contrasting the 3D facial images from 264 unaffected parents of individuals with NSCL/P versus 3,171 controls. We observed distinct facial features between parents and controls across 59 global-to-local facial segments at nominal significance (p ≤ 0.05) and 52 segments at Bonferroni corrected significance (p < 1.2 × 10-3), respectively. Next, we quantified these distinct facial features as univariate traits in another dataset of 8,246 unaffected European individuals and performed a genome-wide association study. We identified 29 independent genetic loci that were associated (p < 5 × 10-8) with at least one of the tested endophenotypic traits, and nine genetic loci also passed the study-wide threshold (p < 8.47 × 10-10). Of the 29 loci, 22 were in proximity of loci previously associated with normal facial variation, 18 were near genes that show strong evidence in orofacial clefting (OFC), and another 10 showed some evidence in OFC. Additionally, polygenic risk scores for NSCL/P showed associations with the endophenotypic traits. This study thus supports the hypothesis of a shared genetic architecture of normal facial development and OFC.

Insights into the genetic architecture of the human face.

The human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study meta-analysis of 8,246 European individuals, we identified 203 genome-wide-significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses indicate that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In summary, our analyses provide insights into the understanding of how complex morphological traits are shaped by both individual and coordinated genetic actions.

Robust genome-wide ancestry inference for heterogeneous datasets: illustrated using the 1,000 genome project with 3D facial images.

Estimates of individual-level genomic ancestry are routinely used in human genetics, and related fields. The analysis of population structure and genomic ancestry can yield insights in terms of modern and ancient populations, allowing us to address questions regarding admixture, and the numbers and identities of the parental source populations. Unrecognized population structure is also an important confounder to correct for in genome-wide association studies. However, it remains challenging to work with heterogeneous datasets from multiple studies collected by different laboratories with diverse genotyping and imputation protocols. This work presents a new approach and an accompanying open-source toolbox that facilitates a robust integrative analysis for population structure and genomic ancestry estimates for heterogeneous datasets. We show robustness against individual outliers and different protocols for the projection of new samples into a reference ancestry space, and the ability to reveal and adjust for population structure in a simulated case-control admixed population. Given that visually evident and easily recognizable patterns of human facial characteristics co-vary with genomic ancestry, and based on the integration of three different sources of genome data, we generate average 3D faces to illustrate genomic ancestry variations within the 1,000 Genome project and for eight ancient-DNA profiles, respectively.

Sources of variation in the 3dMDface and Vectra H1 3D facial imaging systems.

As technology advances and collaborations grow, our ability to finely quantify and explore morphological variation in 3D structures can enable important discoveries and insights into clinical, evolutionary, and genetic questions. However, it is critical to explore and understand the relative contribution of potential sources of error to the structures under study. In this study, we isolated the level of error in 3D facial images attributable to four sources, using the 3dMDface and Vectra H1 camera systems. When the two camera systems are used separately to image human participants, this analysis finds an upper bound of error potentially introduced by the use of the 3dMDface or Vectra H1 camera systems, in conjunction with the MeshMonk registration toolbox, at 0.44 mm and 0.40 mm, respectively. For studies using both camera systems, this upper bound increases to 0.85 mm, on average, and there are systematic differences in the representation of the eyelids, nostrils, and mouth by the two camera systems. Our results highlight the need for careful assessment of potential sources of error in 3D images, both in terms of magnitude and position, especially when dealing with very small measurements or performing many tests.

A Multivariate Approach to Determine the Dimensionality of Human Facial Asymmetry.

Many studies have suggested that developmental instability (DI) could lead to asymmetric development, otherwise known as fluctuating asymmetry (FA). Several attempts to unravel the biological meaning of FA have been made, yet the main step in estimating FA is to remove the effects of directional asymmetry (DA), which is defined as the average bilateral asymmetry at the population level. Here, we demonstrate in a multivariate context that the conventional method of DA correction does not adequately compensate for the effects of DA in other dimensions of asymmetry. This appears to be due to the presence of between-individual variation along the DA dimension. Consequently, we propose to decompose asymmetry into its different orthogonal dimensions, where we introduce a new measure of asymmetry, namely fluctuating directional asymmetry (F-DA). This measure describes individual variation in the dimension of DA, and can be used to adequately correct the asymmetry measurements for the presence of DA. We provide evidence that this measure can be useful in disentangling the different dimensions of asymmetry, and further studies on this measure can provide valuable insight into the underlying biological processes leading to these different asymmetry dimensions.

Facial recognition from DNA using face-to-DNA classifiers.

Facial recognition from DNA refers to the identification or verification of unidentified biological material against facial images with known identity. One approach to establish the identity of unidentified biological material is to predict the face from DNA, and subsequently to match against facial images. However, DNA phenotyping of the human face remains challenging. Here, another proof of concept to biometric authentication is established by using multiple face-to-DNA classifiers, each classifying given faces by a DNA-encoded aspect (sex, genomic background, individual genetic loci), or by a DNA-inferred aspect (BMI, age). Face-to-DNA classifiers on distinct DNA aspects are fused into one matching score for any given face against DNA. In a globally diverse, and subsequently in a homogeneous cohort, we demonstrate preliminary, but substantial true (83%, 80%) over false (17%, 20%) matching in verification mode. Consequences of future efforts include forensic applications, necessitating careful consideration of ethical and legal implications for privacy in genomic databases.

MeshMonk: Open-source large-scale intensive 3D phenotyping.

Dense surface registration, commonly used in computer science, could aid the biological sciences in accurate and comprehensive quantification of biological phenotypes. However, few toolboxes exist that are openly available, non-expert friendly, and validated in a way relevant to biologists. Here, we report a customizable toolbox for reproducible high-throughput dense phenotyping of 3D images, specifically geared towards biological use. Given a target image, a template is first oriented, repositioned, and scaled to the target during a scaled rigid registration step, then transformed further to fit the specific shape of the target using a non-rigid transformation. As validation, we use n = 41 3D facial images to demonstrate that the MeshMonk registration is accurate, with 1.26 mm average error, across 19 landmarks, between placements from manual observers and using the MeshMonk toolbox. We also report no variation in landmark position or centroid size significantly attributable to landmarking method used. Though validated using 19 landmarks, the MeshMonk toolbox produces a dense mesh of vertices across the entire surface, thus facilitating more comprehensive investigations of 3D shape variation. This expansion opens up exciting avenues of study in assessing biological shapes to better understand their phenotypic variation, genetic and developmental underpinnings, and evolutionary history.

Facial masculinity does not appear to be a condition-dependent male ornament and does not reflect MHC heterozygosity in humans.

Recent studies have called into question the idea that facial masculinity is a condition-dependent male ornament that indicates immunocompetence in humans. We add to this growing body of research by calculating an objective measure of facial masculinity/femininity using 3D images in a large sample (n = 1,233) of people of European ancestry. We show that facial masculinity is positively correlated with adult height in both males and females. However, facial masculinity scales with growth similarly in males and females, suggesting that facial masculinity is not exclusively a male ornament, as male ornaments are typically more sensitive to growth in males compared with females. Additionally, we measured immunocompetence via heterozygosity at the major histocompatibility complex (MHC), a widely-used genetic marker of immunity. We show that, while height is positively correlated with MHC heterozygosity, facial masculinity is not. Thus, facial masculinity does not reflect immunocompetence measured by MHC heterozygosity in humans. Overall, we find no support for the idea that facial masculinity is a condition-dependent male ornament that has evolved to indicate immunocompetence.

Measuring asymmetry from high-density 3D surface scans: An application to human faces.

Perfect bilateral symmetry is the optimal outcome of the development of bilateral traits in the absence of developmental perturbations. Any random perturbation in this perfect symmetrical state is called Fluctuating Asymmetry (FA). Many studies have been conducted on FA as an indicator of Developmental Instability (DI) and its possible link with stress and individual quality in general and with attractiveness, health and level of masculinity or femininity in humans. Most human studies of facial asymmetry use 2D pictures and a limited number of landmarks. We developed a protocol to utilize high-density 3D scans of human faces to measure the level of asymmetry. A completely symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to validate the mapping precision. The protocol's accuracy in FA calculation is assessed, and results show that a spatially dense approach is more accurate. In addition, it generates an integrated asymmetry estimate across the entire face. Finally, the automatic nature of the protocol provides a great advantage by omitting the tedious step of manual landmark indication on the biological structure of interest.

SNPs Associated With Testosterone Levels Influence Human Facial Morphology.

Many factors influence human facial morphology, including genetics, age, nutrition, biomechanical forces, and endocrine factors. Moreover, facial features clearly differ between males and females, and these differences are driven primarily by the influence of sex hormones during growth and development. Specific genetic variants are known to influence circulating sex hormone levels in humans, which we hypothesize, in turn, affect facial features. In this study, we investigated the effects of testosterone-related genetic variants on facial morphology. We tested 32 genetic variants across 22 candidate genes related to levels of testosterone, sex hormone-binding globulin (SHGB) and dehydroepiandrosterone sulfate (DHEAS) in three cohorts of healthy individuals for which 3D facial surface images were available (Pittsburgh 3DFN, Penn State and ALSPAC cohorts; total n = 7418). Facial shape was described using a recently developed extension of the dense-surface correspondence approach, in which the 3D facial surface was partitioned into a set of 63 hierarchically organized modules. Each variant was tested against each of the facial surface modules in a multivariate genetic association-testing framework and meta-analyzed. Additionally, the association between these candidate SNPs and five facial ratios was investigated in the Pittsburgh 3DFN cohort. Two significant associations involving intronic variants of SHBG were found: both rs12150660 (p = 1.07E-07) and rs1799941 (p = 6.15E-06) showed an effect on mandible shape. Rs8023580 (an intronic variant of NR2F2-AS1) showed an association with the total and upper facial width to height ratios (p = 9.61E-04 and p = 7.35E-04, respectively). These results indicate that testosterone-related genetic variants affect normal-range facial morphology, and in particular, facial features known to exhibit strong sexual dimorphism in humans.