A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies
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Spiritual boredom is associated with over- and underchallenge, lack of value, and reduced motivation
The emotion of boredom has attracted considerable research interest. However, boredom experienced in spiritual contexts (i.e., spiritual boredom) has rarely been investigated. Based on control-value theory (CVT), we investigated the occurrence, antecedents, and motivational effects of spiritual boredom in five different spiritual contexts: yoga, meditation, silence retreats, Catholic sermons, and pilgrimage. For each context, we conducted two independent studies, one including trait and another including state measures. The set of 10 studies included a total sample of N = 1267 adults. We complemented individual study results with an internal meta-analysis. The results showed a mean level of spiritual boredom of (bar{M}) = 1.91 on a scale of 1 to 5. In line with CVT, spiritual boredom was positively related to being overchallenged ((bar{r}) = 0.44) in 9 out of the 10 studies and positively related to being underchallenged ((bar{r}) = 0.44) in all studies. Furthermore, as expected, spiritual boredom was negatively related to perceived value in all studies ((bar{r}) = −0.54). Finally, boredom was negatively related to motivation to engage in spiritual practice ((bar{r}) = −0.46) across studies. Directions for future research and practical implications are discussed.
Phenotypic divergence between individuals with self-reported autistic traits and clinically ascertained autism
While allowing for rapid recruitment of large samples, online research relies heavily on participants’ self-reports of neuropsychiatric traits, foregoing the clinical characterizations available in laboratory settings. Autism spectrum disorder (ASD) research is one example for which the clinical validity of such an approach remains elusive. Here we compared 56 adults with ASD recruited in person and evaluated by clinicians to matched samples of adults recruited through an online platform (Prolific; 56 with high autistic traits and 56 with low autistic traits) and evaluated via self-reported surveys. Despite having comparable self-reported autistic traits, the online high-trait group reported significantly more social anxiety and avoidant symptoms than in-person ASD participants. Within the in-person sample, there was no relationship between self-rated and clinician-rated autistic traits, suggesting they may capture different aspects of ASD. The groups also differed in their social tendencies during two decision-making tasks; the in-person ASD group was less perceptive of opportunities for social influence and acted less affiliative toward virtual characters. These findings highlight the need for a differentiation between clinically ascertained and trait-defined samples in autism research.
Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels
The contribution of rare noncoding genetic variation to common phenotypes is largely unknown, as a result of a historical lack of population-scale whole-genome sequencing data and the difficulty of categorizing noncoding variants into functionally similar groups. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequencing data, consisting of 1.1 billion variants, 123 million noncoding aggregate-based tests and 2,907 circulating protein levels in ~50,000 UK Biobank participants. We identified 604 independent rare noncoding single-variant associations with circulating protein levels. Unlike protein-coding variation, rare noncoding genetic variation was almost as likely to increase or decrease protein levels. Rare noncoding aggregate testing identified 357 conditionally independent associated regions. Of these, 74 (21%) were not detectable by single-variant testing alone. Our findings have important implications for the identification, and role, of rare noncoding genetic variation associated with common human phenotypes, including the importance of testing aggregates of noncoding variants.
Excess of rare noncoding variants in several type 2 diabetes candidate genes among Asian Indian families
Type 2 diabetes (T2D) etiology is highly complex due to its multiple roots of origin. Polygenic risk scores (PRS) based on genome-wide association studies (GWAS) can partially explain T2D risk. Asian Indian people have up to six times higher risk of developing T2D than European people, and underlying causes of this disparity are unknown.
Large-scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy
Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Here, we report results from a large genome-wide association study and multitrait analysis including 5,900 HCM cases, 68,359 controls and 36,083 UK Biobank participants with cardiac magnetic resonance imaging. We identified 70 loci (50 novel) associated with HCM and 62 loci (20 novel) associated with relevant left ventricular traits. Among the prioritized genes in the HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants confer a roughly tenfold increased risk of HCM. Mendelian randomization analyses support a causal role of increased left ventricular contractility in both obstructive and nonobstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, these findings increase our understanding of the genetic basis of HCM, with potential implications for disease management.
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