Individual-specific Variation Research Articles

Shared and unique patterns of autonomous human endogenous retrovirus loci transcriptomes in CD14 + monocytes from individuals with physical trauma or infection with COVID-19

Since previous studies have suggested that the RNAs of human endogenous retrovirus (HERV) might be involved in regulating innate immunity, it is important to investigate the HERV transcriptome patterns in innate immune cell types such as CD14 + monocytes. Using single cell RNA-seq datasets from resting or stimulated PBMCs mapped to 3,220 known discrete autonomous proviral HERV loci, we found individual-specific variation in HERV transcriptomes between HERV loci in CD14 + monocytes. Analysis of paired datasets from the same individual that were cultured in vitro with LPS or without (i.e. control) revealed 36 HERV loci in CD14 + monocytes that were detected only after activation. To extend our analysis to in vivo activated CD14 + monocytes, we used two scRNA-seq datasets from studies that had demonstrated activation of circulating CD14 + monocytes in patients with physical trauma or patients hospitalized with COVID-19 infections. For direct comparison between the trauma and COVID-19 datasets, we first analyzed 1.625 billion sequence reads from a composite pangenome control of 21 normal individuals. Comparison of the sequence read depth of HERV loci in the trauma or COVID-19 samples to the pangenome control revealed that 39 loci in the COVID-19 and 11 HERV loci in the trauma samples were significantly different (Mann-Whitney U test), with 9 HERV loci shared between the COVID-19 and trauma datasets. The capacity to compare HERV loci transcriptome patterns in innate immune cells, like CD14 + monocytes, across different pathological conditions will lead to greater understanding of the physiological role of HERV expression in health and disease.

Predicting an individual’s functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects

Abstract Several recent studies have optimized deep neural networks to learn high-dimensional relationships linking structural and functional connectivity across the human connectome. However, the extent to which these models recapitulate individual-specific characteristics of resting-state functional brain networks remains unclear. A core concern relates to whether current individual predictions outperform simple benchmarks such as group averages and null conditions. Here, we consider two measures to statistically evaluate whether functional connectivity predictions capture individual effects. We revisit our previously published functional connectivity predictions for 1,000 healthy adults and provide multiple lines of evidence supporting that our predictions successfully capture subtle individual-specific variation in connectivity. While predicted individual effects are statistically significant and outperform several benchmarks, we find that effect sizes are small (i.e., 8%–11% improvement relative to group-average benchmarks). As such, initial expectations about individual prediction performance expressed by us and others may require moderation. We conclude that individual predictions can significantly outperform appropriate benchmark conditions and we provide several recommendations for future studies in this area. Future studies should statistically assess the individual prediction performance of their models using one of the measures and benchmarks provided here.

To Explore the Putative Molecular Targets of Diabetic Nephropathy and their Inhibition Utilizing Potential Phytocompounds.

This review critically addresses the putative molecular targets of Diabetic Nephropathy (DN) and screens effective phytocompounds that can be therapeutically beneficial, and highlights their mechanistic modalities of action. DN has become one of the most prevalent complications of clinical hyperglycemia, with individual-specific variations in the disease spectrum that leads to fatal consequences. Diverse etiologies involving oxidative and nitrosative stress, activation of polyol pathway, inflammasome formation, Extracellular Matrix (ECM) modifications, fibrosis, and change in dynamics of podocyte functional and mesangial cell proliferation adds up to the clinical complexity of DN. Current synthetic therapeutics lacks target-specific approach, and is associated with the development of inevitable residual toxicity and drug resistance. Phytocompounds provides a vast diversity of novel compounds that can become an alternative therapeutic approach to combat the DN. Relevant publications were searched and screened from research databases like GOOGLE SCHOLAR, PUBMED and SCISEARCH. Out of 4895 publications, the most relevant publications were selected and included in this article. This study critically reviews over 60 most promising phytochemical and provides with their molecular targets, that can be of pharmacological significance in context to current treatment and concomitant research in DN. This review highlights those most promising phytocompounds that have the potential of becoming new safer naturally-sourced therapeutic candidates and demands further attention at clinical level.

Neural Mechanisms Determining the Duration of Task-free, Self-paced Visual Perception.

Humans spend hours each day spontaneously engaging with visual content, free from specific tasks and at their own pace. Currently, the brain mechanisms determining the duration of self-paced perceptual behavior remain largely unknown. Here, participants viewed naturalistic images under task-free settings and self-paced each image's viewing duration while undergoing EEG and pupillometry recordings. Across two independent data sets, we observed large inter- and intra-individual variability in viewing duration. However, beyond an image's presentation order and category, specific image content had no consistent effects on spontaneous viewing duration across participants. Overall, longer viewing durations were associated with sustained enhanced posterior positivity and anterior negativity in the ERPs. Individual-specific variations in the spontaneous viewing duration were consistently correlated with evoked EEG activity amplitudes and pupil size changes. By contrast, presentation order was selectively correlated with baseline alpha power and baseline pupil size. Critically, spontaneous viewing duration was strongly predicted by the temporal stability in neural activity patterns starting as early as 350msec after image onset, suggesting that early neural stability is a key predictor for sustained perceptual engagement. Interestingly, neither bottom-up nor top-down predictions about image category influenced spontaneous viewing duration. Overall, these results suggest that individual-specific factors can influence perceptual processing at a surprisingly early time point and influence the multifaceted ebb and flow of spontaneous human perceptual behavior in naturalistic settings.

Anatomo-functional correspondence in the voice-selective regions of human prefrontal cortex

Group level analyses of functional regions involved in voice perception show evidence of 3 sets of bilateral voice-sensitive activations in the human prefrontal cortex, named the anterior, middle and posterior Frontal Voice Areas (FVAs). However, the relationship with the underlying sulcal anatomy, highly variable in this region, is still unknown. We examined the inter-individual variability of the FVAs in conjunction with the sulcal anatomy. To do so, anatomical and functional MRI scans from 74 subjects were analyzed to generate individual contrast maps of the FVAs and relate them to each subject's manually labeled prefrontal sulci. We report two major results. First, the frontal activations for the voice are significantly associated with the sulcal anatomy. Second, this correspondence with the sulcal anatomy at the individual level is a better predictor than coordinates in the MNI space. These findings offer new perspectives for the understanding of anatomical-functional correspondences in this complex cortical region. They also shed light on the importance of considering individual-specific variations in subject's anatomy.

Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts

Drug discovery for diseases such as Parkinson’s disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and deep learning. We applied this platform to primary fibroblasts from 91 Parkinson’s disease patients and matched healthy controls, creating the largest publicly available Cell Painting image dataset to date at 48 terabytes. We use fixed weights from a convolutional deep neural network trained on ImageNet to generate deep embeddings from each image and train machine learning models to detect morphological disease phenotypes. Our platform’s robustness and sensitivity allow the detection of individual-specific variation with high fidelity across batches and plate layouts. Lastly, our models confidently separate LRRK2 and sporadic Parkinson’s disease lines from healthy controls (receiver operating characteristic area under curve 0.79 (0.08 standard deviation)), supporting the capacity of this platform for complex disease modeling and drug screening applications.

Maximum isometric torque at individually-adjusted joint angles exceeds eccentric and concentric torque in lower extremity joint actions

BackgroundPrevious research indicates the high relevance of optimal joint angles for individual isometric strength assessment. The objective was to compare lower limb peak isometric muscle strength abilities at the strongest joint angles with those of dynamic contractions in healthy young adults.MethodsEighteen young male adults performed maximum concentric, isometric, and eccentric contractions of the ankle, knee, and hip flexors and extensors, and hip adductors and abductors in a randomized sequence on an isokinetic dynamometer (ISOMED 2000). Angular velocity was set at 60°/s. The peak of concentric contraction torque curves was used to define optimal joint angles best suited to generate maximum torque during isometric contractions. Maximum voluntary contraction torque of all contraction conditions was adjusted for limb weight and analyzed via a generalized linear mixed gamma regression model (GLMM).ResultsThe gamma GLMM revealed strongly significant effects for all three categorical covariates (contraction types, muscle group, and test order) (p < 2 times 10^{ - 16}). Eccentric contraction increases the muscle torque (hat{beta }_{k} = 0.147) compared to concentric contraction, and isometric contraction even more (hat{beta }_{k} = 0.258). A moderate individual-specific variation was found (random effects standard deviation sigma_{b} = 0.093).ConclusionThe results support the importance of optimal joint angles for isometric maximum strength assessment. When such conditions are given, isometric contractions can produce higher muscle torques than eccentric contractions in the lower body.

Network variants are similar between task and rest states

Recent work has demonstrated that individual-specific variations in functional networks (termed “network variants”) can be identified in individuals using resting state functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time, suggesting that they may be trait-like markers of individual differences in brain organization. However, while networks variants are reliable at rest, is is still untested whether they are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in task and rest states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

Regression analysis of the illness-death model with a shared frailty when all transition times are interval censored

In biomedical or clinical studies, semi-competing risks data are often encountered in which one type of event may censor an other event, but not vice versa. An illness-death model is proposed to analyze these semi-competing risks data in the presence of interval censoring on both intermediate and terminal events. The Cox proportional hazards model is employed with a frailty effect to incorporate a dependent structure between non-fatal and fatal events and individual-specific variations as well. Weight allocations on sub-intervals of censored intervals are used to construct the modified likelihood functions. Marginalization of the full likelihood is accomplished using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through the iterative quasi-Newton algorithm. The proposed methodology is illustrated with several simulation studies and real data.

Longitudinal increases in somatic mosaicism of the expanded CTG repeat in myotonic dystrophy type 1 are associated with variation in age-at-onset.

In myotonic dystrophy type 1 (DM1), somatic mosaicism of the (CTG)n repeat expansion is age-dependent, tissue-specific and expansion-biased. These features contribute toward variation in disease severity and confound genotype-to-phenotype analyses. To investigate how the (CTG)n repeat expansion changes over time, we collected three longitudinal blood DNA samples separated by 8-15years and used small pool and single-molecule PCR in 43 DM1 patients. We used the lower boundary of the allele length distribution as the best estimate for the inherited progenitor allele length (ePAL), which is itself the best predictor of disease severity. Although in most patients the lower boundary of the allele length distribution was conserved over time, in many this estimate also increased with age, suggesting samples for research studies and clinical trials should be obtained as early as possible. As expected, the modal allele length increased over time, driven primarily by ePAL, age-at-sampling and the time interval. As expected, small expansions <100 repeats did not expand as rapidly as larger alleles. However, the rate of expansion of very large alleles was not obviously proportionally higher. This may, at least in part, be a result of the allele length-dependent increase in large contractions that we also observed. We also determined that individual-specific variation in the increase of modal allele length over time not accounted for by ePAL, age-at-sampling and time was inversely associated with individual-specific variation in age-at-onset not accounted for by ePAL, further highlighting somatic expansion as a therapeutic target in DM1.

Exploring the Biosynthesis of O‐acetylated Sialic Acids using CASD1‐null Mice

Sialic acids (Sias) are a family of nine‐carbon backbone monosaccharides naturally occurring at the outer ends of vertebrate cell surface glycoconjugates. O‐acetyl esters at C4, C7, C8 or C9 of Sias are very common modification of Sias, and can play key roles in a number of biological processes. Cell‐, tissue‐ and individual‐specific variations in Sia O‐acetylation have been reported. Several studies also showed that different cell types incorporated 9(7)‐O‐acetylated Sias differentially into different classes of glycoconjugates. Sialate:O‐acetyltransferase activities were also studied in various systems. But the genetic basis and the regulation mechanisms involved remain largely unknown until the discovery of CASD1 as the first candidate gene responsible for sialate:O‐acetylation in eukaryotic systems, and in vitro studies confirmed the enzymatic activity on CMP‐Neu5Ac. Systemic CASD1 knockout (KO) mice, (Casd1tm1b/tm1b ) showed a marked reduction of 9‐O‐acetylation on blood cells. These mice now provide a tool for us to explore the role of CASD1 in sialate:O‐acetylation of Sias in other tissues, and existence of potential O‐acetyltransferase other than CASD1. A combination of different analytical approaches were used to detect residual O‐acetylation in various tissues and cell types of the CASD1‐deficient mice. 9‐O‐acetyl‐Sia distribution was analyzed by histochemistry staining of wildtype (WT) and CASD1 KO mouse tissues with the recombinant 9‐O‐acetyl‐Sia recognizing probe originated from porcine torovirus (PToV) and its non‐binding mutant (PToV‐mut). Significant loss of PToV staining was seen in multiple tissues from CASD1 KO mice, compared to those from WT mice. This is further confirmed by western blot analysis on tissue samples from the WT and CASD1 homozygous KO mouse probing with PToV. O‐acetyl‐Sia levels in various tissue homogenates from CASD1 KO mice in comparison to WT mice was analyzed by mild acid or sialidase release, 1,2‐diamino‐4,5‐methylenedioxybenzene‐2HCl (DMB) derivatization and HPLC and compared to CASD1 heterozygous mice. Base treatment was also applied to Sias released with acetic acid or sialidase to provide a more accurate quantification of O‐acetyl‐Sias. Marked reduction of 9‐O‐acetyl‐Sias was observed in homozygous CASD1 KO tissue (particularly colon, brain and testis and blood) with a small amount of residual 9‐O‐acetyl‐Sias still found in certain tissue like adrenals and bladders. This work suggested that CASD1 plays a major role in the biosynthesis of 9‐O‐acetyl Sias in different mouse tissue‐ and cell‐types. Whether CASD1 participates in the 4‐O‐acetylation of sialic acids and whether different O‐acetyltransferases work on glycolipid and glycoprotein‐bound sialic acids needs further study. These mice also provide a model system to study the in vivo functions of sialic acid 9(7)‐O‐acetylation.

Metabolism and Pharmacokinetics of Phytochemicals in the Human Body.

Phytochemicals are obtained from various plants and used for the treatment of diseases as both traditional and modern medicines. Poor bioavailability of phytochemicals is a major concern in applying phytochemicals as a therapeutic agent. It is, therefore, necessary to understand the metabolism and pharmacokinetics of phytochemicals for its implication as a therapeutic agent. Articles on the metabolism of phytochemicals from the PubMed database. The articles were classified into the digestion, absorption, metabolism, excretion, toxicity, and bioavailability of phytochemicals and the effect of gut microbiota on the metabolism of phytochemicals. The metabolism of each phytochemical is largely dependent on the individual's digestive ability, membrane transporters, metabolizing enzymes and gut microbiota. Further, the form of the phytochemical and genetic make-up of the individual greatly influences the metabolism of phytochemicals. The metabolism of phytochemicals is mostly depended on the form of phytochemicals and individualspecific variations in the metabolism of phytochemicals. Understanding the metabolism and pharmacokinetics of phytochemicals might help in applying plant-based medicines for the treatment of various diseases.

MountainClimber Identifies Alternative Transcription Start and Polyadenylation Sites in RNA-Seq.

Alternative transcription start (ATS) and alternative polyadenylation (APA) create alternative RNA isoforms and modulate many aspects of RNA expression and protein production. However, ATS and APA remain difficult to detect in RNA sequencing (RNA-seq). Here, we developed mountainClimber, a de novo cumulative-sum-based approach to identify ATS and APA as change points. Unlike many existing methods, mountainClimber runs on a single sample and identifies multiple ATS or APA sites anywhere in the transcript. We analyzed 2,342 GTEx samples (36 tissues, 215 individuals) and found that tissue type is the predominant driver of transcript end variations. 75% and 65% of genes exhibited differential APA and ATS across tissues, respectively. In particular, testis displayed longer 5' untranslated regions (UTRs) and shorter 3' UTRs, often in genes related to testis-specific biology. Overall, we report the largest study of transcript ends across human tissues to our knowledge. mountainClimber is available at github.com/gxiaolab/mountainClimber.

Ontogenesis of the Gut Microbiota Composition in Healthy, Full-Term, Vaginally Born and Breast-Fed Infants over the First 3 Years of Life: A Quantitative Bird's-Eye View.

Early-life intestinal microbiota development is crucial for host’s long-term health and is influenced by many factors including gestational age, birth and feeding modes, birth environment, ethnic/geographical background, etc. However, ‘quantitative’ data on the actual population levels of gut bacterial communities when these influences are controlled for is relatively rare. Herein, we demonstrate a quantitative perspective of microbiota development in natural and healthy milieus, i.e., in healthy, full-term, vaginally born and breast-fed infants (n = 19) born at same clinic. Fecal microbiota at age 1 and 7 days, 1, 3, and 6 months and 3 years is quantified using highly sensitive reverse-transcription-quantitative-PCR assays targeting bacterial rRNA molecules. At day 1, we detect one or more bacteria in all (100%) of the babies, wherein the microbiota is composed mainly of enterobacteria (35%), Bacteroides fragilis group (23%), enterococci (18%), staphylococci (13%), and bifidobacteria (9%). Altogether, facultative anaerobes predominate during first few weeks whereafter obligate anaerobes including bifidobacteria, B. fragilis group, Clostridium coccoides group, and Clostridium leptum subgroup gradually start prevailing. At 3 years, the composition is represented almost entirely (99%) by obligate anaerobes including C. leptum subgroup (34%), bifidobacteria (22%), B. fragilis group (21%), C. coccoides group (17%), Atopobium cluster (4%), and Prevotella (1%). The overall obligate/facultative proportion is 32/68, 37/63, 54/46, 70/30, 64/36, and 99/1% at 1 and 7 days, 1, 3, and 6 months and 3 years, respectively. However, interestingly, considerable individual-specific variations in the obligate/facultative ratios as well as in the proportions of Firmicutes, Bacteroides, Actinobacteria, and Proteobacteria communities are seen among these babies. This disparity even within this highly homogenous cohort manifests the magnitude of diverse patterns of gut microbiota configuration and hence underpins the importance of considering not only the gestational age, birth, and feeding modes, and ethnic/geographical background but also other potential outstanding factors when investigating the elements shaping the early microbiota development. In summary, the data demonstrate a quantitative bird’s-eye view of the ontogenesis of early-life gut microbiota in typically natural and healthy milieus and should be informative and facilitative for future studies exploring various aspects of the human gut microbiota.

Widespread Shortening of 3' Untranslated Regions and Increased Exon Inclusion Are Evolutionarily Conserved Features of Innate Immune Responses to Infection.

The contribution of pre-mRNA processing mechanisms to the regulation of immune responses remains poorly studied despite emerging examples of their role as regulators of immune defenses. We sought to investigate the role of mRNA processing in the cellular responses of human macrophages to live bacterial infections. Here, we used mRNA sequencing to quantify gene expression and isoform abundances in primary macrophages from 60 individuals, before and after infection with Listeria monocytogenes and Salmonella typhimurium. In response to both bacteria we identified thousands of genes that significantly change isoform usage in response to infection, characterized by an overall increase in isoform diversity after infection. In response to both bacteria, we found global shifts towards (i) the inclusion of cassette exons and (ii) shorter 3’ UTRs, with near-universal shifts towards usage of more upstream polyadenylation sites. Using complementary data collected in non-human primates, we show that these features are evolutionarily conserved among primates. Following infection, we identify candidate RNA processing factors whose expression is associated with individual-specific variation in isoform abundance. Finally, by profiling microRNA levels, we show that 3’ UTRs with reduced abundance after infection are significantly enriched for target sites for particular miRNAs. These results suggest that the pervasive usage of shorter 3’ UTRs is a mechanism for particular genes to evade repression by immune-activated miRNAs. Collectively, our results suggest that dynamic changes in RNA processing may play key roles in the regulation of innate immune responses.

Within-Individual Mean Corpuscular Volume Variation

We read with interest “Biological Variations of Hematologic Parameters Determined by UniCel DxH 800 Hematology Analyzer.”.1 Most of the estimates of biologic variation of the common analytes reported by Zhang et al1 were close to previously reported literature values. We are puzzled, however, about the broad intraindividual variation for mean corpuscular volume (MCV; 1.12%). Although compilations of biologic variation published before 2000 indicated intraindividual MCV coefficients of variation (CVs) could exceed 1%, 2 recent studies determined the CV was much lower, either 0.18%2 or 0.34%.3 As a result, the Zhang et al reference change values for MCV are much higher than our intuitive reference change values (perhaps, 2 fL) when we examine sequential patient MCVs measured by analyzers that are much older than the analyzer used by Zhang et al.The larger intraindividual MCV CVs reported before 2000 were likely associated with the use of more-imprecise instrumentation. Today, our analytic variations in MCV measurements are miniscule.4 Reasons for a tripling or quadrupling of the estimated intraindividual CV might include the incorporation of some outlying data, analyzer noise, or even some unusual individual-specific variation. We are wondering if Zhang et al would reexamine their MCV data and correlate any available quality control results with those data. Could this variation have been due to some sporadic instrument or individual source?

Developing “Personality” Taxonomies: Metatheoretical and Methodological Rationales Underlying Selection Approaches, Methods of Data Generation and Reduction Principles

Taxonomic "personality" models are widely used in research and applied fields. This article applies the Transdisciplinary Philosophy-of-Science Paradigm for Research on Individuals (TPS-Paradigm) to scrutinise the three methodological steps that are required for developing comprehensive "personality" taxonomies: 1) the approaches used to select the phenomena and events to be studied, 2) the methods used to generate data about the selected phenomena and events and 3) the reduction principles used to extract the "most important" individual-specific variations for constructing "personality" taxonomies. Analyses of some currently popular taxonomies reveal frequent mismatches between the researchers' explicit and implicit metatheories about "personality" and the abilities of previous methodologies to capture the particular kinds of phenomena toward which they are targeted. Serious deficiencies that preclude scientific quantifications are identified in standardised questionnaires, psychology's established standard method of investigation. These mismatches and deficiencies derive from the lack of an explicit formulation and critical reflection on the philosophical and metatheoretical assumptions being made by scientists and from the established practice of radically matching the methodological tools to researchers' preconceived ideas and to pre-existing statistical theories rather than to the particular phenomena and individuals under study. These findings raise serious doubts about the ability of previous taxonomies to appropriately and comprehensively reflect the phenomena towards which they are targeted and the structures of individual-specificity occurring in them. The article elaborates and illustrates with empirical examples methodological principles that allow researchers to appropriately meet the metatheoretical requirements and that are suitable for comprehensively exploring individuals' "personality".

Among-individual variation in vigilance at the nest in colonial Cliff Swallows

Enhanced vigilance against predation is often an advantage of living in groups, but most studies have not examined individual-specific variation in the propensity to be vigilant among the animals within a group. We studied vigilance at the nest in colonially nesting Cliff Swallows (Petrochelidon pyrrhonota) in southwestern Nebraska in 2011 and 2012, and asked whether differences among individuals were consistent over time, whether vigilance varied among different colonies, and whether there were positive or negative fitness consequences of different levels of vigilance. We found significant among-individual variation in extent of vigilance and some variation among different colony sites. Vigilance also varied with date and nesting stage, but other phenotypic characteristics of a bird had no effect on vigilance. Differences among individuals in vigilance were not strongly related to their reproductive success that season, but more vigilant individuals were more likely to attempt intrusions into their neighbors' nests. Vigilance at the nest may be partly directed at monitoring conspecifics' activities in neighboring nests. This study is among the few that have investigated individual variation in vigilance behavior, a possible index of personality for Cliff Swallows, and the first to measure variation in vigilance for a colonial bird while breeding.

Theoretical framework of population genetics with somatic mutations taken into account: application to copy number variations in humans

Traditionally, population genetics focuses on the dynamics of frequencies of alleles acquired by mutations on germ-lines, because only such mutations are heritable. Typical genotyping experiments, however, use DNA from some somatic tissues such as blood, which harbors somatic mutations at the current generation in addition to germ-line mutations accumulated since the most recent common ancestor of the sample. This common practice may sometimes cause erroneous interpretations of polymorphism data, unless we properly understand the role of somatic mutations in population genetics. We here introduce a very basic theoretical framework of population genetics with somatic mutations taken into account. It is easy to imagine that somatic mutations at the current generation simply add individual-specific variations, as errors in mutation detection do. Our theory quantifies this increment under various conditions. We find that the major contribution of somatic mutations plus errors is to very rare variants, particularly to singletons. The relative contribution is markedly large when mutations are deleterious. Because negative selection also increases rare variants, it is important to distinguish the roles of these mutually confounding factors when we interpret the data, even after correcting for demography. We apply this theory to human copy number variations (CNVs), for which the composite effect of somatic mutations and errors may not be negligible. Using genome-wide CNV data, we demonstrate how the joint action of the two factors, selection and somatic mutations plus errors, shapes the observed pattern of polymorphism.

Salivary concentration of progesterone and cortisol significantly differs across individuals after correcting for blood hormone values

Between-individual variation of salivary progesterone (P4) and cortisol levels does not always closely reflect blood hormone concentrations. This may be partly a function of individual differences in salivary hormone excretion. We tested whether time of day at sampling and ethnicity contributed to individual variation in salivary hormones after adjusting for blood hormone levels. Forty-three Caucasian and 15 Japanese women (18-34 years) collected four sets of matched dried blood spot (DBS) and saliva specimens across a menstrual cycle (N = 232 specimen sets). Linear fixed-effects (LFE) models were used to estimate the effects of diurnal variation and ethnicity on salivary P4 and cortisol while adjusting for DBS levels. For each hormone, women with exclusively positive or negative residuals (unexplained variance) from the LFE models were categorized as high- or low-saliva-to-DBS hormone ratio (SDR; high or low salivary secretors), respectively. We found that salivary P4 (P < 0.05) was significantly higher in early morning compared to the afternoon, after controlling for DBS levels, ethnicity, and BMI. After further adjusting for this diurnal effect, significant individual variation in salivary P4 and cortisol remained: sixteen and nine women, respectively were categorized as low or high salivary secretors for both hormones (P < 0.001), suggesting systematic individual-specific variation of salivary hormonal concentration. We conclude that when saliva is used to quantify P4 or cortisol levels, time of day at sampling should be controlled. Even with this adjustment, salivary P4 and cortisol do not closely mirror between- individual variation of serum P4 and cortisol in a substantial proportion of individuals.