Finding Needles in the Haystack: Strategies for Uncovering Noncoding Regulatory Variants.

Despite accumulating evidence implicating noncoding variants in human diseases, unraveling their functionality remains a significant challenge. Systematic annotations of the regulatory landscape and the growth of sequence variant data sets have fueled the development of tools and methods to identify causal noncoding variants and evaluate their regulatory effects. Here, we review the latest advances in the field and discuss potential future research avenues to gain a more in-depth understanding of noncoding regulatory variants.

Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia.

Transcriptome-wide association study (TWAS) tools have been applied to conduct proteome-wide association studies (PWASs) by integrating proteomics data with genome-wide association study (GWAS) summary data. The genetic effects of PWAS-identified significant genes are potentially mediated through genetically regulated protein abundance, thus informing the underlying disease mechanisms better than GWAS loci. However, existing TWAS/PWAS tools are limited by considering only one statistical model. We propose an omnibus PWAS pipeline to account for multiple statistical models and demonstrate improved performance by simulation and application studies of Alzheimer disease (AD) dementia. We employ the Aggregated Cauchy Association Test to derive omnibus PWAS (PWAS-O) p values from PWAS p values obtained by three existing tools assuming complementary statistical models-TIGAR, PrediXcan, and FUSION. Our simulation studies demonstrated improved power, with well-calibrated type I error, for PWAS-O over all three individual tools. We applied PWAS-O to studying AD dementia with reference proteomic data profiled from dorsolateral prefrontal cortex of postmortem brains from individuals of European ancestry. We identified 43 risk genes, including 5 not identified by previous studies, which are interconnected through a protein-protein interaction network that includes the well-known AD risk genes TOMM40, APOC1, and APOC2. We also validated causal genetic effects mediated through the proteome for 27 (63%) PWAS-O risk genes, providing insights into the underlying biological mechanisms of AD dementia and highlighting promising targets for therapeutic development. PWAS-O can be easily applied to studying other complex diseases.

BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases.

Genome-wide Association Studies (GWAS) methods have identified individual single-nucleotide polymorphisms (SNPs) significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT (https://github.com/wangjr03/BayesKAT), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.

All human social groups are human, but some are more human than others: A comprehensive investigation of the implicit association of "Human" to US racial/ethnic groups.

All human groups are equally human, but are they automatically represented as such? Harnessing data from 61,377 participants across 13 experiments (six primary and seven supplemental), a sharp dissociation between implicit and explicit measures emerged. Despite explicitly affirming the equal humanity of all racial/ethnic groups, White participants consistently associated Human (relative to Animal) more with White than Black, Hispanic, and Asian groups on Implicit Association Tests (IATs; experiments 1-4). This effect emerged across diverse representations of Animal that varied in valence (pets, farm animals, wild animals, and vermin; experiments 1-2). Non-White participants showed no such Human=Own Group bias (e.g., Black participants on a White-Black/Human-Animal IAT). However, when the test included two outgroups (e.g., Asian participants on a White-Black/Human-Animal IAT), non-White participants displayed Human=White associations. The overall effect was largely invariant across demographic variations in age, religion, and education but did vary by political ideology and gender, with self-identified conservatives and men displaying stronger Human=White associations (experiment 3). Using a variance decomposition method, experiment 4 showed that the Human=White effect cannot be attributed to valence alone; the semantic meaning of Human and Animal accounted for a unique proportion of variance. Similarly, the effect persisted even when Human was contrasted with positive attributes (e.g., God, Gods, and Dessert; experiment 5a). Experiments 5a-b clarified the primacy of Human=White rather than Animal=Black associations. Together, these experiments document a factually erroneous but robust Human=Own Group implicit stereotype among US White participants (and globally), with suggestive evidence of its presence in other socially dominant groups.

Predicting implicit attitudes with natural language data.

Large-scale language datasets and advances in natural language processing offer opportunities for studying people's cognitions and behaviors. We show how representations derived from language can be combined with laboratory-based word norms to predict implicit attitudes for diverse concepts. Our approach achieves substantially higher correlations than existing methods. We also show that our approach is more predictive of implicit attitudes than are explicit attitudes, and that it captures variance in implicit attitudes that is largely unexplained by explicit attitudes. Overall, our results shed light on how implicit attitudes can be measured by combining standard psychological data with large-scale language data. In doing so, we pave the way for highly accurate computational modeling of what people think and feel about the world around them.

Gene-based association tests in family samples using GWAS summary statistics.

Genome-wide association studies (GWAS) have led to rapid growth in detecting genetic variants associated with various phenotypes. Owing to a great number of publicly accessible GWAS summary statistics, and the difficulty in obtaining individual-level genotype data, many existing gene-based association tests have been adapted to require only GWAS summary statistics rather than individual-level data. However, these association tests are restricted to unrelated individuals and thus do not apply to family samples directly. Moreover, due to its flexibility and effectiveness, the linear mixed model has been increasingly utilized in GWAS to handle correlated data, such as family samples. However, it remains unknown how to perform gene-based association tests in family samples using the GWAS summary statistics estimated from the linear mixed model. In this study, we show that, when family size is negligible compared to the total sample size, the diagonal block structure of the kinship matrix makes it possible to approximate the correlation matrix of marginal Z scores by linkage disequilibrium matrix. Based on this result, current methods utilizing summary statistics for unrelated individuals can be directly applied to family data without any modifications. Our simulation results demonstrate that this proposed strategy controls the type 1 error rate well in various situations. Finally, we exemplify the usefulness of the proposed approach with a dental caries GWAS data set.

multiMiAT: an optimal microbiome-based association test for multicategory phenotypes.

Microbes can affect the metabolism and immunity of human body incessantly, and the dysbiosis of human microbiome drives not only the occurrence but also the progression of disease (i.e. multiple statuses of disease). Recently, microbiome-based association tests have been widely developed to detect the association between the microbiome and host phenotype. However, the existing methods have not achieved satisfactory performance in testing the association between the microbiome and ordinal/nominal multicategory phenotypes (e.g. disease severity and tumor subtype). In this paper, we propose an optimal microbiome-based association test for multicategory phenotypes, namely, multiMiAT. Specifically, under the multinomial logit model framework, we first introduce a microbiome regression-based kernel association test for multicategory phenotypes (multiMiRKAT). As a data-driven optimal test, multiMiAT then integrates multiMiRKAT, score test and MiRKAT-MC to maintain excellent performance in diverse association patterns. Massive simulation experiments prove the success of our method. Furthermore, multiMiAT is also applied to real microbiome data experiments to detect the association between the gut microbiome and clinical statuses of colorectal cancer as well as for diverse statuses of Clostridium difficile infections.

A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects.

The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.

Detecting sparse microbial association signals adaptively from longitudinal microbiome data based on generalized estimating equations.

The association between the compositions of microbial communities and various host phenotypes is an important research topic. Microbiome association research addresses multiple domains, such as human disease and diet. Statistical methods for testing microbiome-phenotype associations have been studied recently to determine their ability to assess longitudinal microbiome data. However, existing methods fail to detect sparse association signals in longitudinal microbiome data. In this paper, we developed a novel method, namely aGEEMIHC, which is a data-driven adaptive microbiome higher criticism analysis based on generalized estimating equations to detect sparse microbial association signals from longitudinal microbiome data. aGEEMiHC adopts generalized estimating equations framework that fully considers the correlation among different observations from the same subject in longitudinal data. To be robust to diverse correlation structures for longitudinal data, aGEEMiHC integrates multiple microbiome higher criticism analyses based on generalized estimating equations with different working correlation structures. Extensive simulation experiments demonstrate that aGEEMiHC can control the type I error correctly and achieve superior performance according to a statistical power comparison. We also applied it to longitudinal microbiome data with various types of host phenotypes to demonstrate the stability of our method. aGEEMiHC is also utilized for real longitudinal microbiome data, and we found a significant association between the gut microbiome and Crohn's disease. In addition, our method ranks the significant factors associated with the host phenotype to provide potential biomarkers.

Implicit Sexual Cognitions in Women with Ambiphilic Sexual Attractions: A Comparison to Androphilic and Gynephilic Women.

Previous research using indirect cognitive measures (sometimes referred to as implicit measures) of sexual attraction have shown that women who are attracted to men (androphilic women) show category non-specific responses, whereas those who are attracted to women (gynephilic) show a category-specific bias to women. The purpose of the present study was to examine whether women who explicitly report approximately equal attraction to men and women (ambiphilic) would show similar non-category specific attraction at this implicit level or whether their responses would be more similar to those of gynephilic women. An implicit association task and a priming task were given to 169 women alongside measures of their self-labelled sexual orientation and an explicit measure of their sexual attraction to men and women. The results replicated previous findings of little bias towards either gender in androphilic women and of a strong bias towards females in gynephilic women. The ambiphilic women also showed a strong bias towards females. The findings clearly show that early automatic associations to sex are biased towards females in ambiphilic women and are not consistent with their explicit statements of preference.

Evidence That Pervasive Body Gaze Behavior in Heterosexual Men Is a Social Marker for Implicit, Physiological, and Explicit Sexual Assault Propensities.

Deliberate and effortful attempts to gaze at the bodies of women is emerging as a valuable marker of sexual objectification in men. Some preliminary evidence suggests that pervasive body gaze behavior may also accompany insidious attitudes which can facilitate sexual assault. The present study aimed to further explore this potential by examining pervasive body gaze associations with explicit, implicit, and physiological sexual assault propensity measures. We presented 110 heterosexual male participants with images of fully and partially dressed women with and without injuries while measuring their skin conductance responses. We also captured implicit and explicit sexual assault measures in addition to self-reported pervasive body gaze behavior. Pervasive body gaze behavior was significantly correlated with rape myth acceptance attitudes, prior perpetration of sexual assault, a stronger implicit association between erotica and aggression, and lower physiological reactivity during exposure to partially dressed injured women. These findings suggest that body gaze towards women could be a behavioral marker for inclinations to victim blame, preferences for rough sexual conduct, and a physiological desensitization towards female victims. This study further validates a five item self-reported body gaze measure as a valuable tool for detecting deviant sexual objectification attitudes and affective states. As such, measurement and observation of body gaze behavior could be useful for developing risk assessments, estimating intervention efficacy, and enhancing public awareness.

Born This Way? National Collective Narcissism, Implicit Homophobia, and Homosexual Essentialism in Populist Poland.

Prejudice toward the LGBT community has become prevalent in Poland under the ultraconservative populist government. The results of three studies conducted between 2018 and 2019 (N1 = 879, N2 = 324, and N3 = 374) indicate that Polish collective narcissism-the belief that the exaggerated greatness of the nation is not recognized by others-is associated with implicit homophobia assessed as the intuitive disapproval of gay men and automatic evaluative preference of heterosexuality over homosexuality. Those associations were to a large extent explained by the relationships between collective narcissism and (1) the belief that groups defined by sexual orientations are essentially distinct; (2) the belief that homosexuality is a personal choice, not genetically determined or culturally universal. The experimental results of Study 3 indicated that inducing the belief that non-normative sexuality is genetically determined and culturally universal reduced automatic preference for heterosexuality over homosexuality (but not intuitive disapproval of gay men) across levels of collective narcissism (contrary to predictions). The obtained results complete the picture of the association of narcissistic beliefs about the nation and homophobia emerging from previous studies. National narcissism is linked not only to explicit but also to latent, implicit homophobia likely to be triggered by increased presence of national narcissism in public discourse. Moreover, national narcissism is linked to implicit homophobia, especially via the agentic belief that sexual orientation is a matter of choice. Changing this belief reduces implicit homophobia also among national narcissists.

Perceptions of older and younger adults who wear hearing aids.

OBJECTIVE: To investigate older and younger adults' perceptions of older and younger adults who wear hearing aids. DESIGN: Participants completed two Implicit Association Tests: One with images of older adults (OA-IAT) and one with images of younger adults (YA-IAT), either wearing or not wearing hearing aids. Participants also rated age, attractiveness, and intelligence of younger and older adults pictured with or without a hearing aid. STUDY SAMPLE: Thirty older adults (M age = 70 years, SD = 4.38) and 30 younger adults (M age = 23 years, SD = 3.01) who reported not having hearing aids or a diagnosed hearing impairment. RESULTS: For both IATs, older and younger participants responded faster and more accurately when images of individuals wearing hearing aids were paired with negative words in comparison to positive words. Photo ratings did not vary in relation to the presence or absence of hearing aids for either age group. CONCLUSION: Although the photo rating tasks indicate neutral explicit attitudes towards individuals who wear hearing aids, our interpretation of the IAT results indicates that younger and older adults may hold negative implicit attitudes towards both older and younger hearing aid users.

Using facial expressions instead of response keys in the implicit association test.

Previous research found that when people are instructed to smile toward liked objects and show negative facial expressions toward disliked objects, their facial response is faster and more intense than when they are required to smile toward disliked objects and express negative facial response toward liked objects. The present research tested a technologically innovative indirect evaluation measure that was based on that finding. Participants completed an implicit association test (IAT)-a common indirect measure of evaluation, responding with their emotional facial expressions, rather than by pressing response keys. In two web studies, using emotional facial expression detection through a webcam, we found that the Facial Response IAT (FR-IAT) is a reliable and valid measure of evaluations, comparable to the keyboard IAT. Because facial responses provide more information than key responses, pursuing future improvements of the FR-IAT's methodology, software, and data analysis is a promising direction for enhancing the quality of indirect evaluation measurement. The same methodology and technology may also enhance other indirect measures of evaluation and cognitive tests related to emotion and judgment.

The Course of Anxiety-Specific Cognitive Bias Following Daycare/Inpatient Treatment in Youths with Social Phobia and School Absenteeism.

Social phobia (SP) is a common mental disorder in youth often accompanied by absence from school, which may require daycare or inpatient intervention (DC/IN). Objective: The present explorative study investigates changes in anxiety-specific implicit assumptions and interpretation bias following DC/IN. Methods: The study included 16 youths with SP (M age = 15.8 [SD = 1.24], females: 62.5 %) participating in DC/IN. We assessed the main outcomes using the Implicit Association Test and Affective Misattribution Procedure. Results: A large effect was shown for reducing implicit assumptions of feeling anxious (p = .142; η2p = .171) and for reducing the implicit interpretation bias (p = .137; η2p = .162). No change was indicated by effect size in implicit assumptions of feeling socially rejected (p = .649; η2p = .016). Social phobia symptoms initially correlated with changes in implicit assumptions of feeling anxious (r = .45). Conclusion: Effect sizes indicate that implicit anxiety-specific assumptions and interpretation bias descriptively improved following DC/IN. Thus, DC/IN may lead to meaningful improvements of anxiety-specific cognition in some individuals with high SP symptoms, emphasizing the relevance of cognitive behavioral approaches in the treatment of SP. Several limitations are discussed.

Implicit racial bias among dental hygienists practicing in the United States.

PURPOSE: Provider bias has been shown to be a contributing factor to racial and ethnic disparities observed in health care settings. The purpose of this study was to examine implicit racial bias among dental hygienists. METHODS: A convenience sample of licensed and practicing dental hygienists within the United States was recruited through email and national dental hygiene social media groups via snowball sampling. A two-part survey design was used for data collection. Participants completed a 10-item demographic survey through an online platform and were then routed to the Race Implicit Association Test (IAT). Descriptive statistics and linear regression analyses were used to compare demographic data and implicit racial preference scores (d-scores). RESULTS: Data from 404 licensed dental hygienists were included in this study. Over two-thirds (67.8%) of participants showed a preference for European Americans over African Americans. A significant difference was found between implicit racial preference scores and participant age (Estimate: 0.01, 95% CI: 0.00, 0.01), years worked comparing <5 years to 21 or more years (Estimate: 0.19, 95% CI: -0.30, -0.09) and race comparing non-White to White (Estimate: -0.17, 95% CI: -0.27, -0.07). No difference was found with task order, previous Race IAT experience, or previous self-reported implicit bias training. CONCLUSIONS: Findings suggest that dental hygienists may harbor implicit racial preferences for European Americans over African Americans. Non-White participants had more positive implicit preferences toward African Americans compared to White participants. Further research is needed to determine the extent to which implicit racial biases contribute to disparities in oral health.

Familial Hypocalciuric Hypercalcemia Type 1 and Autosomal-Dominant Hypocalcemia Type 1: Prevalence in a Large Healthcare Population.

The calcium-sensing receptor (CaSR) regulates serum calcium concentrations. CASR loss- or gain-of-function mutations cause familial hypocalciuric hypercalcemia type 1 (FHH1) or autosomal-dominant hypocalcemia type 1 (ADH1), respectively, but the population prevalence of FHH1 or ADH1 is unknown. Rare CASR variants were identified in whole-exome sequences from 51,289 de-identified individuals in the DiscovEHR cohort derived from a single US healthcare system. We integrated bioinformatics pathogenicity triage, mean serum Ca concentrations, and mode of inheritance to identify potential FHH1 or ADH1 variants, and we used a Sequence Kernel Association Test (SKAT) to identify rare variant-associated diseases. We identified predicted heterozygous loss-of-function CASR variants (6 different nonsense/frameshift variants and 12 different missense variants) in 38 unrelated individuals, 21 of whom were hypercalcemic. Missense CASR variants were identified in two unrelated hypocalcemic individuals. Functional studies showed that all hypercalcemia-associated missense variants impaired heterologous expression, plasma membrane targeting, and/or signaling, whereas hypocalcemia-associated missense variants increased expression, plasma membrane targeting, and/or signaling. Thus, 38 individuals with a genetic diagnosis of FHH1 and two individuals with a genetic diagnosis of ADH1 were identified in the 51,289 cohort, giving a prevalence in this population of 74.1 per 100,000 for FHH1 and 3.9 per 100,000 for ADH1. SKAT combining all nonsense, frameshift, and missense loss-of-function variants revealed associations with cardiovascular, neurological, and other diseases. In conclusion, FHH1 is a common cause of hypercalcemia, with prevalence similar to that of primary hyperparathyroidism, and is associated with altered disease risks, whereas ADH1 is a major cause of non-surgical hypoparathyroidism.

Right amygdala and caudate activation patterns predict implicit attitudes toward people with autism spectrum disorders and physical disabilities, respectively.

Attitudes toward people with disabilities tend to be negative, regardless of the visibility of the disorder traits. Individuals with autism spectrum disorder (ASD) experience stigmatization that is rooted in negative attitudes or prejudice toward them because of their social awkwardness. The neural underpinnings of attitudes toward people with disabilities remain unclear. In this study, we focused on implicit attitudes toward people with ASD and physical disabilities, which are more visible than ASD, and investigated whether implicit attitudes were predicted by using neural activity with multivoxel pattern analysis (MVPA) in the prejudice network. Thirty-six, right-handed, Japanese, university students without disabilities participated. Two implicit association tests (IAT) toward people with ASD and physical disabilities revealed negative implicit attitudes. In the MRI scanner, participants performed a one-back task by using the same picture sets of IATs to examine their neural responses toward people with ASD and physical disabilities. According to the MVPA results, activation patterns of the right amygdala and right caudate significantly predicted implicit attitudes toward people with ASD and physical disabilities, respectively. These results suggest that implicit attitudes toward ASD and physical disabilities can be predicted by using neural signals from different regions within the prejudice network.

Regional Measures of Sexual-Orientation Bias Predict Where Same-Gender Couples Live.

Regional explicit and implicit bias are associated with real-world discrimination and marginalization. We extended this research area by focusing on sexual minorities and where same-gender couples live. Using data on 2,939 U.S. counties from Project Implicit and other publicly available sources, we found that measures with known associations with systemic anti-lesbian, gay, and bisexual (anti-LGB) bias are similarly associated with regional implicit and explicit anti-LGB bias. Furthermore, we found that fewer same-gender couples reside in counties with more explicit and implicit anti-LGB bias, above and beyond other factors that likely influence same-gender-couple residency. These findings further suggest that explicit and implicit measures of regional bias are capturing similar, if not the same, construct of a region's culture of bias toward particular groups. Couched specifically within the ongoing systemic political antagonization of the lesbian, gay, bisexual, transgender, queer, plus (LGBTQ+) community, these findings also highlight the importance of considering contextual (in addition to individual) factors that reinforce systemic inequality.

Oppressed Groups Engender Implicit Positivity: Seven Demonstrations Using Novel and Familiar Targets.

Across seven preregistered studies in online adult volunteer samples (N = 5,323), we measured implicit evaluations of social groups following exposure to historical narratives about their oppression. Although the valence of such information is highly negative and its interpretation was left up to participants, implicit evaluations of oppressed groups shifted toward positivity, including in designs involving fictitious, well-known, and even self-relevant targets. The sole deviation from this pattern was observed in an experiment using a vignette about slavery in the United States, in response to which neither White nor Black Americans exhibited any change in implicit race attitudes. In line with propositional perspectives, these findings suggest that implicit evaluations (including, notably, implicit evaluations of well-known and self-relevant social groups) tend to change toward positivity in response to extremely negative information involving past oppression. However, macro-level phenomena, such as public awareness of histories of oppression, can modulate such updating processes.