Genetic mapping across autoimmune diseases reveals shared associations and mechanisms.

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Epilepsy in childhood and school performance: a nation-wide cohort study.

Childhood epilepsy has been linked to poor academic performance, but large-scale studies are lacking. In this nation-wide study of school-aged children, we examined the association between childhood epilepsy and school performance in standardized tests according to phenotypic and treatment-related characteristics. We performed a matched register-based cohort study of children born in Denmark (1997-2009) who participated in the Danish National School Test Programme between 2010 and 2019. We used population and health registers to identify children with epilepsy and a randomly sampled sex- and age-matched reference cohort without epilepsy (ratio 1:10). Norm-based test scores from language and mathematics reflecting performance as a percentile of the nation-wide distribution of scores (scale 1-100) were used to assess academic performance. Adjusted differences in mean standardized scores between children with and without epilepsy were estimated using linear regression models. Among 582 840 children participating in the School Test Programme, we identified 4659 (0.8%) children with epilepsy (52.8% males) and 46 590 matched reference children. Median age at epilepsy onset was 7.5 years (interquartile range: 4.0-10.6). Childhood epilepsy was associated with poorer school performance overall (mean score = 48.2 versus references = 56.7; adjusted difference = -6.7, 95% CI: -7.4 to -6.0), and worse performance was found in all epilepsy subgroups, including in 3534 children with uncomplicated epilepsy (i.e. no other pre-existing neurologic or intellectual disabilities and no identified possible cause for epilepsy; adjusted difference = -6.0, 95% CI: -6.8 to -5.2). No major variation by sex, age or subject was observed, but larger score differences were seen in children using antiseizure medication at time of testing (e.g. valproate monotherapy, adjusted difference = -9.3, 95% CI: -11.5 to -7.0 and lamotrigine monotherapy, adjusted difference = -13.1, 95% CI: -15.0 to -11.3) and in children with psychiatric comorbidity, especially epilepsy with comorbid intellectual disability (adjusted difference = -27.0, 95% CI: -30.0 to -23.9) and epilepsy with comorbid attention deficit/hyperactivity disorder (adjusted difference = -15.7, 95% CI: -19.0 to -12.4). Children with epilepsy scored significantly lower than their unaffected siblings (adjusted difference = -6.2, 95% CI: -7.1 to -5.4). In conclusion, childhood epilepsy was associated with impaired academic performance throughout schooling, which suggest that there is a widespread need for educational support of children with epilepsy, even when the child has no other comorbidities and when the epilepsy appears well-managed.

Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients.

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

Developing OCHROdb, a comprehensive quality checked database of open chromatin regions from sequencing data.

International consortia, including ENCODE, Roadmap Epigenomics, Genomics of Gene Regulation and Blueprint Epigenome have made large-scale datasets of open chromatin regions publicly available. While these datasets are extremely useful for studying mechanisms of gene regulation in disease and cell development, they only identify open chromatin regions in individual samples. A uniform comparison of accessibility of the same regulatory sites across multiple samples is necessary to correlate open chromatin accessibility and expression of target genes across matched cell types. Additionally, although replicate samples are available for majority of cell types, a comprehensive replication-based quality checking of individual regulatory sites is still lacking. We have integrated 828 DNase-I hypersensitive sequencing samples, which we have uniformly processed and then clustered their regulatory regions across all samples. We checked the quality of open-chromatin regions using our replication test. This has resulted in a comprehensive, quality-checked database of Open CHROmatin (OCHROdb) regions for 194 unique human cell types and cell lines which can serve as a reference for gene regulatory studies involving open chromatin. We have made this resource publicly available: users can download the whole database, or query it for their genomic regions of interest and visualize the results in an interactive genome browser.

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits.

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

The missing link between genetic association and regulatory function.

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.'

Genetics of multiple sclerosis: lessons from polygenicity.

Large-scale mapping studies have identified 236 independent genetic variants associated with an increased risk of multiple sclerosis. However, none of these variants are found exclusively in patients with multiple sclerosis. They are located throughout the genome, including 32 independent variants in the MHC and one on the X chromosome. Most variants are non-coding and seem to act through cell-specific effects on gene expression and splicing. The likely functions of these variants implicate both adaptive and innate immune cells in the pathogenesis of multiple sclerosis, provide pivotal biological insight into the causes and mechanisms of multiple sclerosis, and some of the variants implicated in multiple sclerosis also mediate risk of other autoimmune and inflammatory diseases. Genetics offers an approach to showing causality for environmental factors, through Mendelian randomisation. No single variant is necessary or sufficient to cause multiple sclerosis; instead, each increases total risk in an additive manner. This combined contribution from many genetic factors to disease risk, or polygenicity, has important consequences for how we interpret the epidemiology of multiple sclerosis and how we counsel patients on risk and prognosis. Ongoing efforts are focused on increasing cohort sizes, increasing diversity and detailed characterisation of study populations, and translating these associations into an understanding of the biology of multiple sclerosis.

Seasonal Variation and Risk of Febrile Seizures: A Danish Nationwide Cohort Study.

INTRODUCTION: Onset of febrile seizures varies with calendar season. However, it has not previously been assessed, how season of birth interacts with age and peak risk of febrile seizures, and whether season of birth correlates with the cumulative risk of febrile seizures at 5 years of age (i.e., when children are no longer of risk of febrile seizures). METHODS: We identified all singleton children born in Denmark between 1977 and 2011 who were alive at 3 months of age (N = 2,103,232). We used the Danish Civil Registration System to identify age and sex of the children and the Danish National Patient Register to identify children hospitalized with febrile seizures from 3 months to 5 years of age. Follow-up ended on December 31, 2016, when all children had reached 5 years of age. RESULTS: The relative risk of admission with a first febrile seizure varied with calendar month; in February (a winter month in Denmark), the risk was more than doubled (hazard ratio: 2.10 [95% confidence interval [CI]: 2.03-2.18]) compared with August (a summer month in Denmark). The age-specific incidence of a first febrile seizure by birth month identified the highest peak incidence of a first febrile seizure among children born in November (reaching a peak incidence of 350 first admissions with a febrile seizure per 100,000 person months at age 16 months) as compared to children born in July (reaching a peak incidence of 200 first admissions with a febrile seizure per 100,000 person months at age 16 months). However, the cumulative incidence of any admission with febrile seizures before 5 years was not correlated with season of birth (3.69% [95% CI: 3.64-3.74%] for winter births, 3.57% [95% CI: 3.52-3.62%] for spring births, 3.55% [95% CI: 3.50-3.59%] for summer births, and 3.64% [95% CI: 3.59-3.69%] for fall births). DISCUSSION/CONCLUSION: The study found a significant seasonal variation in onset of the first febrile seizure and in the age-specific peak incidence of febrile seizures. However, there was no correlation between season of birth and cumulative incidence of febrile seizures at 5 years of age suggesting that children who are predisposed to febrile seizures will eventually go on to experience a febrile seizure regardless of season of birth.

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Do monogenic inborn errors of immunity cause susceptibility to severe COVID-19?

The SARS-CoV-2 virus, which causes COVID-19, has been associated globally with substantial morbidity and mortality. Numerous reports over the past year have described the clinical and immunological profiles of COVID-19 patients, and while some trends have emerged for risk stratification, they do not provide a complete picture. Therefore, efforts are ongoing to identify genetic susceptibility factors of severe disease. In this issue of the JCI, Povysil et al. performed a large, multiple-country study, sequencing genomes from patients with mild and severe COVID-19, along with population controls. Contrary to previous reports, the authors observed no enrichment of predicted loss-of-function variants in genes in the type I interferon pathway, which might predispose to severe disease. These studies suggest that more evidence is needed to substantiate the hypothesis for a genetic immune predisposition to severe COVID-19, and highlights the importance of considering experimental design when implicating a monogenic basis for severe disease.

Birth characteristics and risk of febrile seizures.

OBJECTIVE: Febrile seizure is a common childhood disorder that affects 2-5% of all children, and is associated with later development of epilepsy and psychiatric disorders. This study determines how the incidence of febrile seizures correlates with birth characteristics, age, sex and brain development. METHODS: This is a cohort study of all children born Denmark between 1977 and 2011 who were alive at 3 months of age (N = 2,103,232). The Danish National Patient Register was used to identify children with febrile seizures up to 5 years of age. Follow-up ended on 31 December 2016 when all cohort members had potentially reached 5 years of age. RESULTS: In total, 75,593 (3.59%, 95% CI: 3.57-3.62%) were diagnosed with febrile seizures. Incidence peaked at 16.7 months of age (median: 16.7 months, interquartile range: 12.5-24.0). The 5-year cumulative incidence of febrile seizures increased with decreasing birth weight (<1500 g; 5.42% (95% CI: 4.98-5.88% vs. 3,000-4,000 g; 3.53% (95% CI: 3.50-3.56%)) and with decreasing gestational age at birth (31-32 weeks; 5.90% (95% CI: 5.40-6.44%) vs. 39-40 weeks; 3.56% (95% CI: 3.53-3.60)). Lower gestational age at birth was associated with higher age at onset of a first febrile seizure; an association that essentially disappeared when correcting for age from conception. CONCLUSIONS: The risk of febrile seizures increased with decreasing birth weight and gestational age at birth. The association between low gestational age at birth and age at first febrile seizure suggests that onset of febrile seizures is associated with the stage of brain development.

Shared associations identify causal relationships between gene expression and immune cell phenotypes.

Genetic mapping studies have identified thousands of associations between common variants and hundreds of human traits. Translating these associations into mechanisms is complicated by two factors: they fall into gene regulatory regions; and they are rarely mapped to one causal variant. One way around these limitations is to find groups of traits that share associations, using this genetic link to infer a biological connection. Here, we assess how many trait associations in the same locus are due to the same genetic variant, and thus shared; and if these shared associations are due to causal relationships between traits. We find that only a subset of traits share associations, with many due to causal relationships rather than pleiotropy. We therefore suggest that simply observing overlapping associations at a genetic locus is insufficient to infer causality; direct evidence of shared associations is required to support mechanistic hypotheses in genetic studies of complex traits.

Epilepsy risk in offspring of affected parents; a cohort study of the "maternal effect" in epilepsy.

OBJECTIVE: To assess whether the risk of epilepsy is higher in offspring of mothers with epilepsy than in offspring of fathers with epilepsy. METHODS: In a prospective population-based register study, we considered all singletons born in Denmark between 1981 and 2016 (N = 1,754,742). From the Danish National Patient Register since 1977, we identified epilepsy diagnoses in all study participants and their family members. Cox regression models were used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CI), adjusted for relevant confounders. RESULTS: We included 1,754,742 individuals contributing > 30 million person-years of follow-up. The incidence rate of epilepsy in offspring of unaffected parents was 78.8 (95% CI: 77.8-79.8) per 100,000 person-years, while the corresponding rate in offspring with an affected father was 172 per 100,000 person-years (95% CI: 156-187) and in offspring with an affected mother was 260 per 100,000 person-years (95% CI: 243-277). Having an affected mother was associated with a 1.45-fold (95% CI: 1.30-1.63) higher risk of epilepsy in the offspring, compared to having an affected father. This maternal effect was found both in male (HR = 1.39, 95% CI: 1.19-1.62) and female offspring (HR = 1.53, 95% CI: 1.30-1.80), and across various ages at onset in the offspring. The maternal effect was also found in familial epilepsies (i.e. where the affected parent had an affected sibling; HR = 1.50, 95% CI: 1.04-2.16). INTERPRETATION: We found a clear maternal effect on offspring risk of epilepsy in this nationwide cohort study.

ImmuneRegulation: a web-based tool for identifying human immune regulatory elements.

Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at https://immuneregulation.mssm.edu.

Childhood seizures and risk of psychiatric disorders in adolescence and early adulthood: a Danish nationwide cohort study.

BACKGROUND: Paediatric seizures have been linked to psychiatric disorders in childhood, but there is a paucity of large-scale population-based studies of psychiatric comorbidity in later life. We aimed to examine the relation between childhood seizures and the risk of psychiatric disorders in adolescence and early adulthood. METHODS: We did a register-based cohort study of all individuals born in Denmark in 1978-2002. Using diagnostic information from the Danish National Patient Register, all cohort members were categorised according to occurrence of febrile seizures and epilepsy, before entering the follow-up period on their 10th birthday. Individuals were followed up until onset of mental illness, death, emigration, or the end of the study period on Dec 31, 2012. Cox regression analyses were used to estimate the risk of five predefined groups of psychiatric disorders (substance abuse disorders, schizophrenia, mood disorder, anxiety, and personality disorder), separately and combined. Models were adjusted for relevant confounders. FINDINGS: Between Jan 1, 1978, and Dec 31, 2002, 1 291 679 individuals were born in Denmark and followed up in our population cohort (approximately 15 million person-years). 43 148 individuals had a history of febrile seizures, 10 355 had epilepsy, and 1696 had both these disorders. 83 735 (6%) cohort members were identified with at least one of the psychiatric disorders of interest. The risk of any psychiatric disorder was raised in individuals with a history of febrile seizures (hazard ratio [HR] 1·12, 95% CI 1·08-1·17), epilepsy (1·34, 1·25-1·44), or both disorders (1·50, 1·28-1·75). Excess risk of psychiatric illness associated with childhood seizures was present across a range of different disorders, most notably schizophrenia but also anxiety and mood disorders. Associations did not differ between males and females (p=0·30) but increased with a growing number of admissions for febrile seizures (p<0·0001) and with later onset of childhood epilepsy (p<0·0001). INTERPRETATION: Children with epilepsy and febrile seizures-with and without concomitant epilepsy-are at increased risk of developing a broad range of psychiatric disorders in later life. Clarification of the underlying mechanisms attributable to these associations is needed to identify potential options for prevention. FUNDING: Novo Nordisk Foundation, Danish Epilepsy Association, Central Denmark Region, Lundbeck Foundation, and Stanley Medical Research Institute.

Erratum: Genome-wide association studies of multiple sclerosis.

[This corrects the article DOI: 10.1002/cti2.1018.].

Genome-wide association studies of multiple sclerosis.

Large-scale genetic studies of multiple sclerosis have identified over 230 risk effects across the human genome, making it a prototypical common disease with complex genetic architecture. Here, after a brief historical background on the discovery and definition of the disease, we summarise the last fifteen years of genetic discoveries and map out the challenges that remain to translate these findings into an aetiological framework and actionable clinical understanding.

Multiple sclerosis.

Multiple sclerosis is a potentially progressive, autoimmune neurologic disorder of the central nervous system, resulting from an autoimmune attack on central nervous system white matter. It is a leading cause of neurologic symptoms in young adults, with no known cure. Emerging disease-modifying therapies aim to control symptoms, with increasingly sophisticated immune function modulation. Though several environmental exposures increase the risk of developing the disease, a large fraction of overall risk is heritable and can be attributed to hundreds of common genetic variants influencing gene regulation in specific immune subsets. Here, we review the history of the disease, the realization that risk is heritable, and the recent revelation of hundreds of genetic variants driving this risk by international consortia studying tens of thousands of patients. Finally, we discuss how these results are revealing the specific pathobiology of multiple sclerosis and how this knowledge is transforming drug discovery.

Microbiota control immune regulation in humanized mice.

The microbiome affects development and activity of the immune system, and may modulate immune therapies, but there is little direct information about this control in vivo. We studied how the microbiome affects regulation of human immune cells in humanized mice. When humanized mice were treated with a cocktail of 4 antibiotics, there was an increase in the frequency of effector T cells in the gut wall, circulating levels of IFN-γ, and appearance of anti-nuclear antibodies. Teplizumab, a non-FcR-binding anti-CD3ε antibody, no longer delayed xenograft rejection. An increase in CD8+ central memory cells and IL-10, markers of efficacy of teplizumab, were not induced. IL-10 levels were only decreased when the mice were treated with all 4 but not individual antibiotics. Antibiotic treatment affected CD11b+CD11c+ cells, which produced less IL-10 and IL-27, and showed increased expression of CD86 and activation of T cells when cocultured with T cells and teplizumab. Soluble products in the pellets appeared to be responsible for the reduced IL-27 expression in DCs. Similar changes in IL-10 induction were seen when human peripheral blood mononuclear cells were cultured with human stool samples. We conclude that changes in the microbiome may impact the efficacy of immunosuppressive medications by altering immune regulatory pathways.

Integrative Genetic and Epigenetic Analysis Uncovers Regulatory Mechanisms of Autoimmune Disease.

Genome-wide association studies in autoimmune and inflammatory diseases (AID) have uncovered hundreds of loci mediating risk. These associations are preferentially located in non-coding DNA regions and in particular in tissue-specific DNase I hypersensitivity sites (DHSs). While these analyses clearly demonstrate the overall enrichment of disease risk alleles on gene regulatory regions, they are not designed to identify individual regulatory regions mediating risk or the genes under their control, and thus uncover the specific molecular events driving disease risk. To do so we have departed from standard practice by identifying regulatory regions which replicate across samples and connect them to the genes they control through robust re-analysis of public data. We find significant evidence of regulatory potential in 78/301 (26%) risk loci across nine autoimmune and inflammatory diseases, and we find that individual genes are targeted by these effects in 53/78 (68%) of these. Thus, we are able to generate testable mechanistic hypotheses of the molecular changes that drive disease risk.