Decanalization and the origin of complex disease

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture.

DOI:http://dx.doi.org/10.7554/eLife.09178.001

Individuals of the same species have similar, but generally not identical, DNA sequences. This ‘genetic variation’ is due to random changes in the DNA—known as mutations—that occur among individuals. These mutations may be passed on to these individuals' offspring, who in turn pass them on to their descendants. Some of these mutations may have a positive or negative effect on the ability of the organisms to survive and reproduce, but others may have no effect at all.

The process by which an embryo forms (which is called embryogenesis) follows a precisely controlled series of events. Within the same species, there is genetic variation in the DNA that programs embryogenesis, but it is not clear what effect this variation has on how the embryo develops. Here, Paaby et al. adapted a genetics technique called a ‘modifier screen’ to study how genetic variation affects the development of a roundworm known as Caenorhabditis elegans.

The experiments show that populations of worms harbor a lot of genetic variation that affects how they tolerate the loss of an important gene. One by one, Paaby et al. interrupted the activity of specific genes that embryos need in order to develop. How this affected the embryo, and whether or not it was able to survive, was due in large part to the naturally-occurring genetic variation in other genes in these worms.

Paaby et al.'s findings serve as a reminder that the effect of a mutation depends on other DNA sequences in the organism. In humans, for example, a gene that causes a genetic disease may produce severe symptoms in one patient but mild symptoms in another. Future experiments will reveal the details of how genetic variation affects embryogenesis, which may also provide new insights into how complex processes in animals evolve over time.

DOI:http://dx.doi.org/10.7554/eLife.09178.002

Abiotic stress does not magnify the deleterious effects of spontaneous mutations

Although the effects of deleterious alleles often are predicted to be greater in stressful environments, there is no theoretical basis for this prediction and the empirical evidence is mixed. Here we characterized the effects of three types of abiotic stress (thermal, oxidative and hyperosmotic) on two sets of nematode (Caenorhabditis elegans) mutation accumulation (MA) lines that differ by threefold in fitness. We compared the survival and egg-to-adult viability between environments (benign and stressful) and between fitness categories (high-fitness MA, low-fitness MA). If the environment and mutation load have synergistic effects on trait means, then the difference between the high and low-fitness MA lines should be larger in stressful environments. Although the stress treatments consistently decreased survival and/or viability, we did not detect significant interactions between fitness categories and environment types. In contrast, we did find consistent evidence for synergistic effects on (micro)environmental variation. The lack of signal in trait means likely reflects the very low starting fitness of some low-fitness MA lines, the potential for cross-stress responses and the context dependence of mutational effects. In addition, the large increases in the environmental variance in the stressful environments may have masked small changes in trait means. These results do not provide evidence for synergism between mutation and stress.

The Role of Epigenetic Change in Autism Spectrum Disorders

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders characterized by problems with social communication, social interaction, and repetitive or restricted behaviors. ASD are comorbid with other disorders including attention deficit hyperactivity disorder, epilepsy, Rett syndrome, and Fragile X syndrome. Neither the genetic nor the environmental components have been characterized well enough to aid diagnosis or treatment of non-syndromic ASD. However, genome-wide association studies have amassed evidence suggesting involvement of hundreds of genes and a variety of associated genetic pathways. Recently, investigators have turned to epigenetics, a prime mediator of environmental effects on genomes and phenotype, to characterize changes in ASD that constitute a molecular level on top of DNA sequence. Though in their infancy, such studies have the potential to increase our understanding of the etiology of ASD and may assist in the development of biomarkers for its prediction, diagnosis, prognosis, and eventually in its prevention and intervention. This review focuses on the first few epigenome-wide association studies of ASD and discusses future directions.

Towards causally cohesive genotype-phenotype modelling for characterization of the soft-tissue mechanics of the heart in normal and pathological geometries

A scientific understanding of individual variation is key to personalized medicine, integrating genotypic and phenotypic information via computational physiology. Genetic effects are often context-dependent, differing between genetic backgrounds or physiological states such as disease. Here, we analyse in silico genotype-phenotype maps (GP map) for a soft-tissue mechanics model of the passive inflation phase of the heartbeat, contrasting the effects of microstructural and other low-level parameters assumed to be genetically influenced, under normal, concentrically hypertrophic and eccentrically hypertrophic geometries. For a large number of parameter scenarios, representing mock genetic variation in low-level parameters, we computed phenotypes describing the deformation of the heart during inflation. The GP map was characterized by variance decompositions for each phenotype with respect to each parameter. As hypothesized, the concentric geometry allowed more low-level parameters to contribute to variation in shape phenotypes. In addition, the relative importance of overall stiffness and fibre stiffness differed between geometries. Otherwise, the GP map was largely similar for the different heart geometries, with little genetic interaction between the parameters included in this study. We argue that personalized medicine can benefit from a combination of causally cohesive genotype-phenotype modelling, and strategic phenotyping that captures effect modifiers not explicitly included in the mechanistic model.

Temperature stress mediates decanalization and dominance of gene expression in Drosophila melanogaster

The regulatory architecture of gene expression remains an area of active research. Here, we studied how the interplay of genetic and environmental variation affects gene expression by exposing Drosophila melanogaster strains to four different developmental temperatures. At 18°C we observed almost complete canalization with only very few allelic effects on gene expression. In contrast, at the two temperature extremes, 13°C and 29°C a large number of allelic differences in gene expression were detected due to both cis- and trans-regulatory effects. Allelic differences in gene expression were mainly dominant, but for up to 62% of the genes the dominance swapped between 13 and 29°C. Our results are consistent with stabilizing selection causing buffering of allelic expression variation in non-stressful environments. We propose that decanalization of gene expression in stressful environments is not only central to adaptation, but may also contribute to genetic disorders in human populations.

Negative feedback buffers effects of regulatory variants

Mechanisms conferring robustness against regulatory variants have been controversial. Previous studies suggested widespread buffering of RNA misexpression on protein levels during translation. We do not find evidence that translational buffering is common. Instead, we find extensive buffering at the level of RNA expression, exerted through negative feedback regulation acting in trans, which reduces the effect of regulatory variants on gene expression. Our approach is based on a novel experimental design in which allelic differential expression in a yeast hybrid strain is compared to allelic differential expression in a pool of its spores. Allelic differential expression in the hybrid is due to cis-regulatory differences only. Instead, in the pool of spores allelic differential expression is not only due to cis-regulatory differences but also due to local trans effects that include negative feedback. We found that buffering through such local trans regulation is widespread, typically compensating for about 15% of cis-regulatory effects on individual genes. Negative feedback is stronger not only for essential genes, indicating its functional relevance, but also for genes with low to middle levels of expression, for which tight regulation matters most. We suggest that negative feedback is one mechanism of Waddington's canalization, facilitating the accumulation of genetic variants that might give selective advantage in different environments.

Genetics of asthma: an introduction for the clinician

Asthma runs in families, and children of asthmatic parents are at increased risk of asthma. Prediction of disease risk is pivotal for the clinician when counselling atopic families. However, this is not always an easy task bearing in mind the vast and ever-increasing knowledge about asthma genetics. The advent of new genotyping technologies has made it possible to sequence in great detail the human genome for asthma-associated variants, and accordingly, recent decades have witnessed an explosion in the number of rare and common variants associated with disease risk. This review presents an overview of methods and advances in asthma genetics in an attempt to help the clinician keep track of the most important knowledge in the field.

On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms

Biologists have long observed that physiological and developmental processes are insensitive, or robust, to many genetic and environmental perturbations. A complete understanding of the evolutionary causes and consequences of this robustness is lacking. Recent progress has been made in uncovering the regulatory mechanisms that underlie environmental robustness in particular. Less is known about robustness to the effects of mutations, and indeed the evolution of mutational robustness remains a controversial topic. The controversy has spread to related topics, in particular the evolutionary relevance of cryptic genetic variation. This review aims to synthesize current understanding of robustness mechanisms and to cut through the controversy by shedding light on what is and is not known about mutational robustness. Some studies have confused mutational robustness with non-additive interactions between mutations (epistasis). We conclude that a profitable way forward is to focus investigations (and rhetoric) less on mutational robustness and more on epistasis.

Higher-order genetic interactions and their contribution to complex traits

The contribution of genetic interactions involving three or more loci to complex traits is poorly understood. These higher-order genetic interactions (HGIs) are difficult to detect in genetic mapping studies, therefore, few examples of them have been described. However, the lack of data on HGIs should not be misconstrued as proof that this class of genetic effect is unimportant. To the contrary, evidence from model organisms suggests that HGIs frequently influence genetic studies and contribute to many complex traits. Here, we review the growing literature on HGIs and discuss the future of research on this topic.

Escape from homeostasis

Many physiological systems, from gene networks to biochemistry to whole organism physiology, exhibit homeostatic mechanisms that keep certain variables within a fairly narrow range. Because homeostatic mechanisms buffer traits against environmental and genetic variation they allow the accumulation of cryptic genetic variation. Homeostatic mechanisms are never perfect and can be destabilized by mutations in genes that alter the kinetics of the underlying mechanism. We use mathematical models to study five diverse mechanisms of homeostasis: thermoregulation; maintenance of homocysteine concentration; neural control by a feed forward circuit; the myogenic response in the kidney; and regulation of extracellular dopamine levels in the brain. In all these cases there are homeostatic regions where the trait is relatively insensitive to genetic or environmental variation, flanked by regions where it is sensitive. Moreover, mutations or environmental changes can place an individual closer to the edge of the homeostatic region, thus predisposing that individual to deleterious effects caused by additional mutations or environmental changes. Mutations and environmental variables can also reduce the size of the homeostatic region, thus releasing potentially deleterious cryptic genetic variation. These considerations of mutations, environment, homeostasis, and escape from homeostasis help to explain why the etiology of so many diseases is complex.

Exploring the origins of asthma: Lessons from twin studies

This thesis explores the contribution of twin studies, particularly those studies originating from the Danish Twin Registry, to the understanding of the aetiology of asthma. First, it is explored how twin studies have established the contribution of genetic and environmental factors to the variation in the susceptibility to asthma, and to the variation in several aspects of the clinical expression of the disease such as its age at onset, its symptomatology, its intermediate phenotypes, and its relationship with other atopic diseases. Next, it is explored how twin studies have corroborated theories explaining asthma's recent increase in prevalence, and last, how these fit with the explanations of the epidemiological trends in other common chronic diseases of modernity.

Non-HLA genes PTPN22, CDK6 and PADI4 are associated with specific autoantibodies in HLA-defined subgroups of rheumatoid arthritis

INTRODUCTION

Genetic susceptibility to complex diseases has been intensively studied during the last decade, yet only signals with small effect have been found leaving open the possibility that subgroups within complex traits show stronger association signals. In rheumatoid arthritis (RA), autoantibody production serves as a helpful discriminator in genetic studies and today anti-citrullinated cyclic peptide (anti-CCP) antibody positivity is employed for diagnosis of disease. The HLA-DRB1 locus is known as the most important genetic contributor for the risk of RA, but is not sufficient to drive autoimmunity and additional genetic and environmental factors are involved. Hence, we addressed the association of previously discovered RA loci with disease-specific autoantibody responses in RA patients stratified by HLA-DRB1*04.

METHODS

We investigated 2178 patients from three RA cohorts from Sweden and Spain for 41 genetic variants and four autoantibodies, including the generic anti-CCP as well as specific responses towards citrullinated peptides from vimentin, alpha-enolase and type II collagen.

RESULTS

Our data demonstrated different genetic associations of autoantibody-positive disease subgroups in relation to the presence of DRB1*04. Two specific subgroups of autoantibody-positive RA were identified. The SNP in PTPN22 was associated with presence of anti-citrullinated enolase peptide antibodies in carriers of HLA-DRB1*04 (Cochran-Mantel-Haenszel test P = 0.0001, P corrected <0.05), whereas SNPs in CDK6 and PADI4 were associated with anti-CCP status in DRB1*04 negative patients (Cochran-Mantel-Haenszel test P = 0.0004, P corrected <0.05 for both markers). Additionally we see allelic correlation with autoantibody titers for PTPN22 SNP rs2476601 and anti-citrullinated enolase peptide antibodies in carriers of HLA-DRB1*04 (Mann Whitney test P = 0.02) and between CDK6 SNP rs42041 and anti-CCP in non-carriers of HLA-DRB1*04 (Mann Whitney test P = 0.02).

CONCLUSION

These data point to alternative pathways for disease development in clinically similar RA subgroups and suggest an approach for study of genetic complexity of disease with strong contribution of HLA.

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits.

Exome sequencing identifies DLG1 as a novel gene for potential susceptibility to Crohn's disease in a Chinese family study

BACKGROUND

Genetic variants make some contributions to inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC). More than 100 susceptibility loci were identified in Western IBD studies, but susceptibility gene has not been found in Chinese IBD patients till now. Sequencing of individuals with an IBD family history is a powerful approach toward our understanding of the genetics and pathogenesis of IBD. The aim of this study, which focuses on a Han Chinese CD family, is to identify high-risk variants and potentially novel loci using whole exome sequencing technique.

METHODS

Exome sequence data from 4 individuals belonging to a same family were analyzed using bioinformatics methods to narrow down the variants associated with CD. The potential risk genes were further analyzed by genotyping and Sanger sequencing in family members, additional 401 healthy controls (HC), 278 sporadic CD patients, 123 UC cases, a pair of monozygotic CD twins and another Chinese CD family.

RESULTS

From the CD family in which the father and daughter were affected, we identified a novel single nucleotide variant (SNV) c.374T>C (p.I125T) in exon 4 of discs large homolog 1 (DLG1), a gene has been reported to play multiple roles in cell proliferation, T cell polarity and T cell receptor signaling. After genotyping among case and controls, a PLINK analysis showed the variant was of significance (P<0.05). 4 CD patients of the other Chinese family bore another non-synonymous variant c.833G>A (p.R278Q) in exon 9 of DLG1.

CONCLUSIONS

We have discovered novel genetic variants in the coding regions of DLG1 gene, the results support that DLG1 is a novel potential susceptibility gene for CD in Chinese patients.

Genetic association of objective sleep phenotypes with a functional polymorphism in the neuropeptide S receptor gene

BACKGROUND

The neuropeptide S receptor (NPSR1) and its ligand neuropeptide S (NPS) have received increased attention in the last few years, as both establish a previously unknown system of neuromodulation. Animal research studies have suggested that NPS may be involved in arousal/wakefulness and may also have a crucial role in sleep regulation. The single nucleotide polymorphism (SNP) rs324981 in NPSR1 has begun to shed light on a function of the NPS-system in human sleep regulation. Due to an amino acid exchange, the T-allele leads to an increased sensitivity of the NPSR1. In the only genome-wide association study to date on circadian sleep parameters in humans, an association was found between rs324981 and regular bedtime. However, the sleep parameters in this study were only measured by self-rating. Therefore, our study aimed to replicate these findings using an objective measure of sleep.

METHODS

The study included n = 393 white subjects (62-79 years) who participated in an actigraphic assessment for determining sleep duration, rest duration, sleep onset, rest onset and sleep onset latency. Genotyping of the SNP rs324981 was performed using the TaqMan OpenArray System.

RESULTS

The genotype at rs324981 was not significantly associated with rest onset (bedtime) or sleep onset (p = .146 and p = .199, respectively). However, the SNP showed a significant effect on sleep- and rest duration (p = .007 and p = .003, respectively). Subjects that were homozygous for the minor T-allele had a significantly decreased sleep- and rest duration compared to A-allele carriers.

CONCLUSION

The results of this study indicate that the sleep pattern in humans is influenced by the NPS-system. However, the previously reported association between bedtime and rs324981 could not be confirmed. The current finding of decreased sleep duration in T/T allele carriers is in accordance with studies in rodents reporting similar results after NPS application.

Chromatin regulators, phenotypic robustness, and autism risk

Though extensively characterized clinically, the causes of autism spectrum disorder (ASD) remain a mystery. ASD is known to have a strong genetic basis, but it is genetically very heterogeneous. Recent studies have estimated that de novo disruptive mutations in hundreds of genes may contribute to ASD. However, it is unclear how it is possible for mutations in so many different genes to contribute to ASD. Recent findings suggest that many of the mutations disrupt genes involved in transcription regulation that are expressed prenatally in the developing brain. De novo disruptive mutations are also more frequent in girls with ASD, despite the fact that ASD is more prevalent in boys. In this paper, we hypothesize that loss of robustness may contribute to ASD. Loss of phenotypic robustness may be caused by mutations that disrupt capacitors that operate in the developing brain. This may lead to the release of cryptic genetic variation that contributes to ASD. Reduced robustness is consistent with the observed variability in expressivity and incomplete penetrance. It is also consistent with the hypothesis that the development of the female brain is more robust, and it may explain the higher rate and severity of disruptive de novo mutations in girls with ASD.

Cryptic genetic variation: evolution's hidden substrate

Cryptic genetic variation (CGV) is invisible under normal conditions, but it can fuel evolution when circumstances change. In theory, CGV can represent a massive cache of adaptive potential or a pool of deleterious alleles that are in need of constant suppression. CGV emerges from both neutral and selective processes, and it may inform about how human populations respond to change. CGV facilitates adaptation in experimental settings, but does it have an important role in the real world? Here, we review the empirical support for widespread CGV in natural populations, including its potential role in emerging human diseases and the growing evidence of its contribution to evolution.

Universal Grammar and Biological Variation: An EvoDevo Agenda for Comparative Biolinguistics

Recent advances in genetics and neurobiology have greatly increased the degree of variation that one finds in what is taken to provide the biological foundations of our species-specific linguistic capacities. In particular, this variation seems to cast doubt on the purportedly homogeneous nature of the language faculty traditionally captured by the concept of "Universal Grammar." In this article we discuss what this new source of diversity reveals about the biological reality underlying Universal Grammar. Our discussion leads us to support (1) certain hypotheses advanced in evolutionary developmental biology that argue for the existence of robust biological mechanisms capable of canalizing variation at different levels, and (2) a bottom-up perspective on comparative cognition. We conclude by sketching future directions for what we call "comparative biolinguistics," specifying which experimental directions may help us succeed in this new research avenue.

Additive, epistatic, and environmental effects through the lens of expression variability QTL in a twin cohort

The expression of a gene can vary across individuals in the general population, as well as between monozygotic twins. This variable expression is assumed to be due to the influence of both genetic and nongenetic factors. Yet little evidence supporting this assumption has been obtained from empirical data. In this study, we used expression data from a large twin cohort to investigate the influences of genetic and nongenetic factors on variable gene expression. We focused on a set of expression variability QTL (evQTL)--i.e., genetic loci associated with the variance, as opposed to the mean, of gene expression. We identified evQTL for 99, 56, and 79 genes in lymphoblastoid cell lines, skin, and fat, respectively. The differences in gene expression, measured by the relative mean difference (RMD), tended to be larger between pairs of dizygotic (DZ) twins than between pairs of monozygotic (MZ) twins, showing that genetic background influenced the expression variability. Furthermore, a more profound RMD was observed between pairs of MZ twins whose genotypes were associated with greater expression variability than the RMD found between pairs of MZ twins whose genotypes were associated with smaller expression variability. This suggests that nongenetic (e.g., environmental) factors contribute to the variable expression. Lastly, we demonstrated that the formation of evQTL is likely due to partial linkages between eQTL SNPs that are additively associated with the mean of gene expression; in most cases, no epistatic effect is involved. Our findings have implications for understanding divergent sources of gene expression variability.

Effect of genetic variation in a Drosophila model of diabetes-associated misfolded human proinsulin

The identification and validation of gene–gene interactions is a major challenge in human studies. Here, we explore an approach for studying epistasis in humans using a Drosophila melanogaster model of neonatal diabetes mellitus. Expression of the mutant preproinsulin (hINS^C96Y) in the eye imaginal disc mimics the human disease: it activates conserved stress-response pathways and leads to cell death (reduction in eye area). Dominant-acting variants in wild-derived inbred lines from the Drosophila Genetics Reference Panel produce a continuous, highly heritable distribution of eye-degeneration phenotypes in a hINS^C96Y background. A genome-wide association study (GWAS) in 154 sequenced lines identified a sharp peak on chromosome 3L, which mapped to a 400-bp linkage block within an intron of the gene sulfateless (sfl). RNAi knockdown of sfl enhanced the eye-degeneration phenotype in a mutant-hINS-dependent manner. RNAi against two additional genes in the heparan sulfate (HS) biosynthetic pathway (ttv and botv), in which sfl acts, also modified the eye phenotype in a hINS^C96Y-dependent manner, strongly suggesting a novel link between HS-modified proteins and cellular responses to misfolded proteins. Finally, we evaluated allele-specific expression difference between the two major sfl-intronic haplotypes in heterozygtes. The results showed significant heterogeneity in marker-associated gene expression, thereby leaving the causal mutation(s) and its mechanism unidentified. In conclusion, the ability to create a model of human genetic disease, map a QTL by GWAS to a specific gene, and validate its contribution to disease with available genetic resources and the potential to experimentally link the variant to a molecular mechanism demonstrate the many advantages Drosophila holds in determining the genetic underpinnings of human disease.

A network-based analysis of the types of coronary artery disease from traditional Chinese medicine perspective: potential for therapeutics and drug discovery

ETHNOPHARMACOLOGICAL RELEVANCE

Coronary heart disease (CAD) is one of the most dangerous threats to human health due to its high incidence and high mortality. CAD has several major types, such as blood stasis and qi deficiency according to the syndromes of diagnosis in traditional Chinese medicine (TCM), which are treated with different herbs or compound prescriptions. However, up to now a deep analysis of the relationship between CAD and its types both at molecular or systems levels is still unavailable, which greatly limits the combination of TCMs with Western drugs to form an integrative/alternative medicine for treatment of the complex disease.

MATERIALS AND METHODS

In this review, we attempt to decipher the underlying mechanisms of major types of CAD by connecting the drugs, targets and diseases to obtain the compound-target-disease associations for reconstructing the biologically-meaningful networks based on systems pharmacology method.

RESULTS

The results indicate that the herbs for eliminating blood stasis have pharmacological activity of dilating blood vessel, improving the microcirculation, reducing blood viscosity and regulating blood lipid, while qi-enhancing herbs have the potential for enhancing energy metabolism and anti-inflammation.

CONCLUSIONS

A systematic exploration of types of CAD may bring out the best between research on drug molecules and TCM phenotypic information, so as to accelerate development of network-based drug discovery as well as to facilitate the therapy of this disease.

Geographical, environmental and pathophysiological influences on the human blood transcriptome

Gene expression variation provides a read-out of both genetic and environmental influences on gene activity. Geographical, genomic and sociogenomic studies have highlighted how life circumstances of an individual modify the expression of hundreds and in some cases thousands of genes in a co-ordinated manner. This review places such results in the context of a conserved set of 90 transcripts known as Blood Informative Transcripts (BIT) that capture the major conserved components of variation in the peripheral blood transcriptome. Pathophysiological states are also shown to associate with the perturbation of transcript abundance along the major axes. Discussion of false negative rates leads us to argue that simple significance thresholds provide a biased perspective on assessment of differential expression that may cloud the interpretation of studies with small sample sizes.

Natural genetic variation determines susceptibility to aggregation or toxicity in a C. elegans model for polyglutamine disease

Background

Monogenic gain-of-function protein aggregation diseases, including Huntington’s disease, exhibit substantial variability in age of onset, penetrance, and clinical symptoms, even between individuals with similar or identical mutations. This difference in phenotypic expression of proteotoxic mutations is proposed to be due, at least in part, to the variability in genetic background. To address this, we examined the role of natural variation in defining the susceptibility of genetically diverse individuals to protein aggregation and toxicity, using the Caenorhabditis elegans polyglutamine model.

Results

Introgression of polyQ40 into three wild genetic backgrounds uncovered wide variation in onset of aggregation and corresponding toxicity, as well as alteration in the cell-specific susceptibility to aggregation. To further dissect these relationships, we established a panel of 21 recombinant inbred lines that showed a broad range of aggregation phenotypes, independent of differences in expression levels. We found that aggregation is a transgressive trait, and does not always correlate with measures of toxicity, such as early onset of muscle dysfunction, egg-laying deficits, or reduced lifespan. Moreover, distinct measures of proteotoxicity were independently modified by the genetic background.

Conclusions

Resistance to protein aggregation and the ability to restrict its associated cellular dysfunction are independently controlled by the natural variation in genetic background, revealing important new considerations in the search for targets for therapeutic intervention in conformational diseases. Thus, our C. elegans model can serve as a powerful tool to dissect the contribution of natural variation to individual susceptibility to proteotoxicity.

Please see related commentary by Kaeberlein, http://www.biomedcentral.com/1741-7007/11/102.

What causes alopecia areata?

The pathobiology of alopecia areata (AA), one of the most frequent autoimmune diseases and a major unsolved clinical problem, has intrigued dermatologists, hair biologists and immunologists for decades. Simultaneously, both affected patients and the physicians who take care of them are increasingly frustrated that there is still no fully satisfactory treatment. Much of this frustration results from the fact that the pathobiology of AA remains unclear, and no single AA pathogenesis concept can claim to be universally accepted. In fact, some investigators still harbour doubts whether this even is an autoimmune disease, and the relative importance of CD8(+) T cells, CD4(+) T cells and NKGD2(+) NK or NKT cells and the exact role of genetic factors in AA pathogenesis remain bones of contention. Also, is AA one disease, a spectrum of distinct disease entities or only a response pattern of normal hair follicles to immunologically mediated damage? During the past decade, substantial progress has been made in basic AA-related research, in the development of new models for translationally relevant AA research and in the identification of new therapeutic agents and targets for future AA management. This calls for a re-evaluation and public debate of currently prevalent AA pathobiology concepts. The present Controversies feature takes on this challenge, hoping to attract more skin biologists, immunologists and professional autoimmunity experts to this biologically fascinating and clinically important model disease.

Histone variant HTZ1 shows extensive epistasis with, but does not increase robustness to, new mutations

Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact) to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA) lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1) to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be caused by loss of robustness, and therefore force reevaluation of prior claims based on that assumption.

The details in the distributions: why and how to study phenotypic variability

Phenotypic variability is present even when genetic and environmental differences between cells are reduced to the greatest possible extent. For example, genetically identical bacteria display differing levels of resistance to antibiotics, clonal yeast populations demonstrate morphological and growth-rate heterogeneity, and mouse blastomeres from the same embryo have stochastic differences in gene expression. However, the distributions of phenotypes present among isogenic organisms are often overlooked; instead, many studies focus on population aggregates such as the mean. The details of these distributions are relevant to major questions in diverse fields, including the evolution of antimicrobial-drug and chemotherapy resistance. We review emerging experimental and statistical techniques that allow rigorous analysis of phenotypic variability and thereby may lead to advances across the biological sciences.

Trade-off in the effect of the APOE gene on the ages at onset of cardiocascular disease and cancer across ages, gender, and human generations

Decades of studies of candidate genes show their complex role in aging-related traits. We focus on apolipoprotein E e2/3/4 polymorphism and ages at onset of cardiovascular diseases (CVD) and cancer in the parental and offspring generations of the Framingham Heart Study participants to gain insights on the role of age and gender across generations in genetic trade-offs. The analyses show that the apolipoprotein E e4 allele carriers live longer lives without cancer than the non-e4 allele carriers in each generation. The role of the e4 allele in onset of CVD is age- and generation-specific, constituting two modes of sexually dimorphic genetic trade-offs. In offspring, the e4 allele confers risk of CVD primarily in women and can protect against cancer primarily in men of the same age. In the parental generation, genetic trade-off is seen in different age groups, with a protective role of the e4 allele against cancer in older men and its detrimental role in CVD in younger women. The puzzling complexity of genetic mechanisms working in different genders, ages, and environments calls for more detail and systemic analyses beyond those adapted in current large-scale genetic association studies.

Genetic risk prediction: individualized variability in susceptibility to toxicants

Genetic risk prediction uses genetic data to individualize prediction of outcome or effect from a known harmful toxicant. Several examples of toxicogenetics (usually binary traits) are discussed, reflecting largely Mendelian traits before the Human Genome Project began in 1990. Numerous complexities of the genome and what constitutes "a gene" have emerged during these past two decades. Examples of toxicogenomics (continuous outcomes, gradients) are examined. Most xenobiotic-induced environmental diseases resemble human complex diseases or other multifactorial traits such as height; these traits result from hundreds of low-effect genes. Consequently, uncovering an association between a trait and a genetic variant in a large cohort can provide important information about underlying biology; however, screening for a specific variant in an individual worker or patient has poor predictive value and little clinical utility. Individualized risk assessment for toxicants that cause environmental diseases, although a lofty goal, remains to be achieved.

Plastic, fantastic! Phenotypic variance in the transcriptional landscape of the grape berry

Evaluation of the common grapevine Vitis vinifera across multiple harvests and field locations provides important insights into crop transcriptional plasticity under diverse agricultural regimes.

Ethnic differences in the relationship between insulin sensitivity and insulin response: a systematic review and meta-analysis

OBJECTIVE

Human blood glucose levels have likely evolved toward their current point of stability over hundreds of thousands of years. The robust population stability of this trait is called canalization. It has been represented by a hyperbolic function of two variables: insulin sensitivity and insulin response. Environmental changes due to global migration may have pushed some human subpopulations to different points of stability. We hypothesized that there may be ethnic differences in the optimal states in the relationship between insulin sensitivity and insulin response.

RESEARCH DESIGN AND METHODS

We identified studies that measured the insulin sensitivity index (SI) and acute insulin response to glucose (AIRg) in three major ethnic groups: Africans, Caucasians, and East Asians. We identified 74 study cohorts comprising 3,813 individuals (19 African cohorts, 31 Caucasian, and 24 East Asian). We calculated the hyperbolic relationship using the mean values of SI and AIRg in the healthy cohorts with normal glucose tolerance.

RESULTS

We found that Caucasian subpopulations were located around the middle point of the hyperbola, while African and East Asian subpopulations are located around unstable extreme points, where a small change in one variable is associated with a large nonlinear change in the other variable.

CONCLUSIONS

Our findings suggest that the genetic background of Africans and East Asians makes them more and differentially susceptible to diabetes than Caucasians. This ethnic stratification could be implicated in the different natural courses of diabetes onset.

Genome-wide association study of sleep in Drosophila melanogaster

BACKGROUND

Sleep is a highly conserved behavior, yet its duration and pattern vary extensively among species and between individuals within species. The genetic basis of natural variation in sleep remains unknown.

RESULTS

We used the Drosophila Genetic Reference Panel (DGRP) to perform a genome-wide association (GWA) study of sleep in D. melanogaster. We identified candidate single nucleotide polymorphisms (SNPs) associated with differences in the mean as well as the environmental sensitivity of sleep traits; these SNPs typically had sex-specific or sex-biased effects, and were generally located in non-coding regions. The majority of SNPs (80.3%) affecting sleep were at low frequency and had moderately large effects. Additive models incorporating multiple SNPs explained as much as 55% of the genetic variance for sleep in males and females. Many of these loci are known to interact physically and/or genetically, enabling us to place them in candidate genetic networks. We confirmed the role of seven novel loci on sleep using insertional mutagenesis and RNA interference.

CONCLUSIONS

We identified many SNPs in novel loci that are potentially associated with natural variation in sleep, as well as SNPs within genes previously known to affect Drosophila sleep. Several of the candidate genes have human homologues that were identified in studies of human sleep, suggesting that genes affecting variation in sleep are conserved across species. Our discovery of genetic variants that influence environmental sensitivity to sleep may have a wider application to all GWA studies, because individuals with highly plastic genotypes will not have consistent phenotypes.

Inter-chromosomal level of genome organization and longevity-related phenotypes in humans

Studies focusing on unraveling the genetic origin of health span in humans assume that polygenic, aging-related phenotypes are inherited through Mendelian mechanisms of inheritance of individual genes. We use the Framingham Heart Study (FHS) data to examine whether non-Mendelian mechanisms of inheritance can drive linkage of loci on non-homologous chromosomes and whether such mechanisms can be relevant to longevity-related phenotypes. We report on genome-wide inter-chromosomal linkage disequilibrium (LD) and on chromosome-wide intra-chromosomal LD and show that these are real phenomena in the FHS data. Genetic analysis of inheritance in families based on Mendelian segregation reveals that the alleles of single nucleotide polymorphisms (SNPs) in LD at loci on non-homologous chromosomes are inherited as a complex resembling haplotypes of a genetic unit. This result implies that the inter-chromosomal LD is likely caused by non-random assortment of non-homologous chromosomes during meiosis. The risk allele haplotypes can be subject to dominant-negative selection primary through the mechanisms of non-Mendelian inheritance. They can go to extinction within two human generations. The set of SNPs in inter-chromosomal LD (N=68) is nearly threefold enriched, with high significance (p=1.6 × 10(-9)), on non-synonymous coding variants (N=28) compared to the entire qualified set of the studied SNPs. Genes for the tightly linked SNPs are involved in fundamental biological processes in an organism. Survival analyses show that the revealed non-genetic linkage is associated with heritable complex phenotype of premature death. Our results suggest the presence of inter-chromosomal level of functional organization in the human genome and highlight a challenging problem of genomics of human health and aging.

Genomics of human health and aging

Despite notable progress of the candidate-gene and genome-wide association studies (GWAS), understanding the role of genes contributing to human health and lifespan is still very limited. We use the Framingham Heart Study to elucidate if recognizing the role of evolution and systemic processes in an aging organism could advance such studies. We combine throughput methods of GWAS with more detail methods typical for candidate-gene analyses and show that both lifespan and ages at onset of CVD and cancer can be controlled by the same allelic variants. The risk allele carriers are at highly significant risk of premature death (e.g., RR=2.9, p=5.0 × 10(-66)), onset of CVD (e.g., RR=1.6, p=4.6 × 10(-17)), and onset of cancer (e.g., RR=1.6, p=1.5 × 10(-6)). The mechanism mediating the revealed genetic associations is likely associated with biological aging. These aging-related phenotypes are associated with a complex network which includes, in this study, 62 correlated SNPs even so these SNPs can be on non-homologous chromosomes. A striking result is three-fold, highly significant (p=3.6 × 10(-10)) enrichment of non-synonymous SNPs (N=27) in this network compared to the entire qualified set of the studied SNPs. Functional significance of this network is strengthened by involvement of genes for these SNPs in fundamental biological processes related to aging (e.g., response to stimuli, protein degradation, apoptosis) and by connections of these genes with neurological (20 genes) and cardio-vascular (nine genes) processes and tumorigenesis (10 genes). These results document challenging role of gene networks in regulating human health and aging and call for broadening focus on genomics of such phenotypes.

The role of lipid-related genes, aging-related processes, and environment in healthspan

The inherent complexity of aging-related traits can temper progress in unraveling the genetic origins of healthspan. We focus on two generations in the Framingham Heart Study, the original (FHS) and offspring (FHSO) cohorts, to determine whether aging-related processes in changing environments can substantially impact the role of lipid-related genes discovered in candidate gene (the apolipoprotein E (APOE) e2/3/4 polymorphism) and genome-wide (the APOB rs1042034 (C/T)) studies, in regulation of total cholesterol (TC) and onset of cardiovascular disease (CVD). We demonstrate that the APOE e4 allele and APOB CC genotype can play detrimental, neutral, and protective sex-specific roles in the etiology of CVD at different ages and in different environments. We document antagonistic roles for the e4 allele in the onset of CVD characterized by detrimental effects at younger ages (RR≤ 75 years = 1.49, P = 7.5 × 10(-4) ) and protective effects at older ages (RR76+years = 0.77, P = 0.044) for FHS participants. We found that disregarding the role of aging erroneously nullifies the significant effects of the e4 allele in this sample (RR = 0.92, P = 0.387). The leading biogenetic pathways mediating genetic effects on CVD may be more relevant to lipid metabolism for APOB than APOE. Aging-related processes can modulate the strength of genetic associations with TC in the same individuals at different chronological ages. We found substantial differences in the effects of the same APOE and APOB alleles on CVD and TC across generations. The results suggest that aging-related processes in changing environments may play key roles in the genetics of healthspan. Detailed systemic integrative analyses may substantially advance the progress.

Canalization and control in automata networks: body segmentation in Drosophila melanogaster

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.

The Emerging Field of Human Social Genomics

Although we generally experience our bodies as being biologically stable across time and situations, an emerging field of research is demonstrating that external social conditions, especially our subjective perceptions of those conditions, can influence our most basic internal biological processes-namely, the expression of our genes. This research on human social genomics has begun to identify the types of genes that are subject to social-environmental regulation, the neural and molecular mechanisms that mediate the effects of social processes on gene expression, and the genetic polymorphisms that moderate individual differences in genomic sensitivity to social context. The molecular models resulting from this research provide new opportunities for understanding how social and genetic factors interact to shape complex behavioral phenotypes and susceptibility to disease. This research also sheds new light on the evolution of the human genome and challenges the fundamental belief that our molecular makeup is relatively stable and impermeable to social-environmental influence.

Molecular mechanisms of robustness in plants

Robustness, the ability of organisms to buffer phenotypes against perturbations, has drawn renewed interest among developmental biologists and geneticists. A growing body of research supports an important role of robustness in the genotype to phenotype translation, with far-reaching implications for evolutionary processes and disease susceptibility. Similar to animals and fungi, plant robustness is a function of genetic network architecture. Most perturbations are buffered; however, perturbation of network hubs destabilizes many traits. Here, we review recent advances in identifying molecular robustness mechanisms in plants that have been enabled by a combination of classical genetics and population genetics with genome-scale data.

Epistasis, complexity, and multifactor dimensionality reduction

Genome-wide association studies (GWASs) and other high-throughput initiatives have led to an information explosion in human genetics and genetic epidemiology. Conversion of this wealth of new information about genomic variation to knowledge about public health and human biology will depend critically on the complexity of the genotype to phenotype mapping relationship. We review here computational approaches to genetic analysis that embrace, rather than ignore, the complexity of human health. We focus on multifactor dimensionality reduction (MDR) as an approach for modeling one of these complexities: epistasis or gene-gene interaction.

Beyond orchids and dandelions: testing the 5-HTT "risky" allele for evidence of phenotypic capacitance and frequency-dependent selection

The persistence of behaviorally deleterious genes in the human population poses an interesting question for population genetics: If certain alleles at these loci are deleterious, why have they survived in the population? We consider evidence for phenotypic capacitance and/or frequency-dependent selection for an allele that has been putatively shown to have negative associations with human behaviors (the "short" 5-HTT promoter region allele) yet has persisted in human and nonhuman primate populations. Using data from the National Longitudinal Study of Adolescent Health, we compare sibling and twin variation in depression by 5-HTT genotype (specified in several ways) and investigate sibship-level cross-person gene-gene interactions. In support of the "orchid/dandelion" hypothesis, we find evidence that the short allele increases variation in phenotypes in response to environmental (or genetic) differences (i.e., acts as a perturbation of a phenotypic capacitor). Further, we also find some evidence that the effects of allelic variation at this locus are moderated by the genetic environment of the sibship unit (i.e., effects may be susceptible to frequency-dependent selection). We discuss implications of these findings for genetic models in general, specifically with respect to stable unit treatment value assumption violations (i.e., nonindependence of units of analysis).

Lessons from model organisms: phenotypic robustness and missing heritability in complex disease

Genetically tractable model organisms from phages to mice have taught us invaluable lessons about fundamental biological processes and disease-causing mutations. Owing to technological and computational advances, human biology and the causes of human diseases have become accessible as never before. Progress in identifying genetic determinants for human diseases has been most remarkable for Mendelian traits. In contrast, identifying genetic determinants for complex diseases such as diabetes, cancer, and cardiovascular and neurological diseases has remained challenging, despite the fact that these diseases cluster in families. Hundreds of variants associated with complex diseases have been found in genome-wide association studies (GWAS), yet most of these variants explain only a modest amount of the observed heritability, a phenomenon known as "missing heritability." The missing heritability has been attributed to many factors, mainly inadequacies in genotyping and phenotyping. We argue that lessons learned about complex traits in model organisms offer an alternative explanation for missing heritability in humans. In diverse model organisms, phenotypic robustness differs among individuals, and those with decreased robustness show increased penetrance of mutations and express previously cryptic genetic variation. We propose that phenotypic robustness also differs among humans and that individuals with lower robustness will be more responsive to genetic and environmental perturbations and hence susceptible to disease. Phenotypic robustness is a quantitative trait that can be accurately measured in model organisms, but not as yet in humans. We propose feasible approaches to measure robustness in large human populations, proof-of-principle experiments for robustness markers in model organisms, and a new GWAS design that takes differences in robustness into account.

More than the sum of its parts: a complex epistatic network underlies natural variation in thermal preference behavior in Caenorhabditis elegans

Behavior is a complex trait that results from interactions among multiple genes and the environment. Both additive and nonadditive effects are expected to contribute to broad-sense heritability of complex phenotypes, although the relative contribution of each of these mechanisms is unknown. Here, we mapped genetic variation in the correlated phenotypes of thermal preference and isothermal dispersion in the nematode Caenorhabditis elegans. Genetic variation underlying these traits is characterized by a set of linked quantitative trait loci (QTL) that interact in a complex epistatic network. In particular, two loci located on the X chromosome interact with one another to generate extreme thermophilic behavior and are responsible for ∼50% of the total variation observed in a cross between two parental lines, even though these loci individually explain very little of the among-line variation. Our results demonstrate that simultaneously considering the influence of a quantitative trait locus (QTL) on multiple scales of behavior can inform the physiological mechanism of the QTL and show that epistasis can explain significant proportions of otherwise unattributed variance within populations.

Directional selection causes decanalization in a group I ribozyme

A canalized genotype is robust to environmental or genetic perturbations. Canalization is expected to result from stabilizing selection on a well-adapted phenotype. Decanalization, the loss of robustness, might follow periods of directional selection toward a new optimum. The evolutionary forces causing decanalization are still unknown, in part because it is difficult to determine the fitness effects of mutations in populations of organisms with complex genotypes and phenotypes. Here, we report direct experimental measurements of robustness in a system with a simple genotype and phenotype, the catalytic activity of an RNA enzyme. We find that the robustness of a population of RNA enzymes decreases during a period of directional selection in the laboratory. The decrease in robustness is primarily caused by the selective sweep of a genotype that is decanalized relative to the wild-type, both in terms of mutational robustness and environmental robustness (thermodynamic stability). Our results experimentally demonstrate that directional selection can cause decanalization on short time scales, and demonstrate co-evolution of mutational and environmental robustness.

A knowledge-based method for association studies on complex diseases

Complex disorders are a class of diseases whose phenotypic variance is caused by the interplay of multiple genetic and environmental factors. Analyzing the complexity underlying the genetic architecture of such traits may help develop more efficient diagnostic tests and therapeutic protocols. Despite the continuous advances in revealing the genetic basis of many of complex diseases using genome-wide association studies (GWAS), a major proportion of their genetic variance has remained unexplained, in part because GWAS are unable to reliably detect small individual risk contributions and to capture the underlying genetic heterogeneity. In this paper we describe a hypothesis-based method to analyze the association between multiple genetic factors and a complex phenotype. Starting from sets of markers selected based on preexisting biomedical knowledge, our method generates multi-marker models relevant to the biological process underlying a complex trait for which genotype data is available. We tested the applicability of our method using the WTCCC case-control dataset. Analyzing a number of biological pathways, the method was able to identify several immune system related multi-SNP models significantly associated with Rheumatoid Arthritis (RA) and Crohn's disease (CD). RA-associated multi-SNP models were also replicated in an independent case-control dataset. The method we present provides a framework for capturing joint contributions of genetic factors to complex traits. In contrast to hypothesis-free approaches, its results can be given a direct biological interpretation. The replicated multi-SNP models generated by our analysis may serve as a predictor to estimate the risk of RA development in individuals of Caucasian ancestry.

Human genomic disease variants: a neutral evolutionary explanation

Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease.