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Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGSWBC [95%CI, 0.30−0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69−0.88], p = 4.0 × 10−5) or immunosuppressant (n = 354, HR = 0.61 [0.38–0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44−0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit. Here, the authors find that a benign polygenic predisposition to lower white blood cell counts is associated with multiple clinical endpoints, suggesting that predisposed individuals are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals. Most polygenic risk score (PRS) methods focus only on individuals with distinct primary continental ancestry, without accommodating recently-admixed individuals. Here, the authors develop a novel penalized regression-based PRS method specifically designed for admixed individuals. [ABSTRACT FROM AUTHOR]

Asthma is a heterogeneous, complex syndrome, and identifying asthma endotypes has been challenging. We hypothesize that distinct endotypes of asthma arise in disparate genetic variation and life-time environmental exposure backgrounds, and that disease comorbidity patterns serve as a surrogate for such genetic and exposure variations. Here, we computationally discover 22 distinct comorbid disease patterns among individuals with asthma (asthma comorbidity subgroups) using diagnosis records for >151 M US residents, and re-identify 11 of the 22 subgroups in the much smaller UK Biobank. GWASs to discern asthma risk loci for individuals within each subgroup and in all subgroups combined reveal 109 independent risk loci, of which 52 are replicated in multi-ancestry meta-analysis across different ethnicity subsamples in UK Biobank, US BioVU, and BioBank Japan. Fourteen loci confer asthma risk in multiple subgroups and in all subgroups combined. Importantly, another six loci confer asthma risk in only one subgroup. The strength of association between asthma and each of 44 health-related phenotypes also varies dramatically across subgroups. This work reveals subpopulations of asthma patients distinguished by comorbidity patterns, asthma risk loci, gene expression, and health-related phenotypes, and so reveals different asthma endotypes. Asthma is a heterogeneous, complex syndrome that arises in individuals with various genetic and exposure variations. Here, the authors show that disease comorbidity patterns can serve as a surrogate for these variations, and identify asthma endotypes distinguished by comorbidity patterns, asthma risk loci, gene expression, and health-related phenotypes. [ABSTRACT FROM AUTHOR]

Discovering novel uses for existing drugs, through drug repurposing, can reduce the time, costs, and risk of failure associated with new drug development. However, prioritizing drug repurposing candidates for downstream studies remains challenging. Here, we present a high-throughput approach to identify and validate drug repurposing candidates. This approach integrates human gene expression, drug perturbation, and clinical data from publicly available resources. We apply this approach to find drug repurposing candidates for two diseases, hyperlipidemia and hypertension. We screen >21,000 compounds and replicate ten approved drugs. We also identify 25 (seven for hyperlipidemia, eighteen for hypertension) drugs approved for other indications with therapeutic effects on clinically relevant biomarkers. For five of these drugs, the therapeutic effects are replicated in the All of Us Research Program database. We anticipate our approach will enable researchers to integrate multiple publicly available datasets to identify high priority drug repurposing opportunities for human diseases. Prioritizing drug repurposing candidates for downstream studies remains challenging. Here, the authors present a high-throughput approach to identify and validate drug repurposing candidates, integrating human gene expression, drug perturbation, and clinical data from publicly available resources. [ABSTRACT FROM AUTHOR]

Background: Irinotecan (CPT-11) is an anticancer agent widely used to treat adult solid tumours. Large interindividual variability in the clearance of irinotecan and SN-38, its active and toxic metabolite, results in highly unpredictable toxicity.Methods: In 217 cancer patients treated with intravenous irinotecan single agent or in combination, germline DNA was used to interrogate the variation in 84 genes by next-generation sequencing. A stepwise analytical framework including a population pharmacokinetic model with SNP- and gene-based testing was used to identify demographic/clinical/genetic factors that influence the clearance of irinotecan and SN-38.Results: Irinotecan clearance was influenced by rs4149057 in SLCO1B1, body surface area, and co-administration of 5-fluorouracil/leucovorin/bevacizumab. SN-38 clearance was influenced by rs887829 in UGT1A1, pre-treatment total bilirubin, and EGFR rare variant burden. Within each UGT1A1 genotype group, elevated pre-treatment total bilirubin and/or presence of at least one rare variant in EGFR resulted in significantly lower SN-38 clearance. The model reduced the interindividual variability in irinotecan clearance from 38 to 34% and SN-38 clearance from 49 to 32%.Conclusions: This new model significantly reduced the interindividual variability in the clearance of irinotecan and SN-38. New genetic factors of variability in clearance have been identified. [ABSTRACT FROM AUTHOR]

The kidney proximal tubule is the primary site for solute reabsorption, secretion and where kidney diseases can originate, including drug-induced toxicity. Two-dimensional cell culture systems of the human proximal tubule cells (hPTCs) are often used to study these processes. However, these systems fail to model the interplay between filtrate flow, fluid shear stress (FSS), and functionality essential for understanding renal diseases and drug toxicity. The impact of FSS exposure on gene expression and effects of FSS at differing rates on gene expression in hPTCs has not been thoroughly investigated. Here, we performed RNA-sequencing of human RPTEC/TERT1 cells in a microfluidic chip-based 3D model to determine transcriptomic changes. We measured transcriptional changes following treatment of cells in this device at three different fluidic shear stress. We observed that FSS changes the expression of PTC-specific genes and impacted genes previously associated with renal diseases in genome-wide association studies (GWAS). At a physiological FSS level, we observed cell morphology, enhanced polarization, presence of cilia, and transport functions using albumin reabsorption via endocytosis and efflux transport. Here, we present a dynamic view of hPTCs response to FSS with increasing fluidic shear stress conditions and provide insight into hPTCs cellular function under biologically relevant conditions. [ABSTRACT FROM AUTHOR]

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition. This Review describes progress in the study of human genetics, in which rapid advances in technology, foundational genomic resources and analytical tools have contributed to the understanding of the mechanisms responsible for many rare and common diseases and to preventative and therapeutic strategies for many of these conditions. [ABSTRACT FROM AUTHOR]

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes. [ABSTRACT FROM AUTHOR]

Preclinical Alzheimer's disease (AD) is characterized by amyloid deposition in the absence of overt clinical impairment. There is substantial heterogeneity in the long-term clinical outcomes among amyloid positive individuals, yet limited work has focused on identifying molecular factors driving resilience from amyloid-related cognitive impairment. We apply a recently developed predicted gene expression analysis (PrediXcan) to identify genes that modify the association between baseline amyloid deposition and longitudinal cognitive changes. Participants free of clinical AD (n = 631) were selected from the AD Neuroimaging Initiative (ADNI) who had a baseline positron emission tomography measure of amyloid deposition (quantified as a standard uptake value ratio), longitudinal neuropsychological data, and genetic data. PrediXcan was used to impute gene expression levels across 15 heart and brain tissues. Mixed effect regression models assessed the interaction between predicted gene expression levels and amyloid deposition on longitudinal cognitive outcomes. The predicted gene expression levels for two genes in the coronary artery (CNTLN, PROK1) and two genes in the atrial appendage (PRSS50, PROK1) interacted with amyloid deposition on episodic memory performance. The predicted gene expression levels for two additional genes (TMC4 in the basal ganglia and HMBS in the aorta) interacted with amyloid deposition on executive function performance. Post-hoc analyses provide additional validation of the HMBS and PROK1 effects across two independent subsets of ADNI using two additional metrics of amyloid deposition. These results highlight a subset of unique candidate genes of resilience and provide evidence that cell-cycle regulation, angiogenesis, and heme biosynthesis likely play a role in AD progression. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual's genetic profile and correlates 'imputed' gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys the benefits of gene-based approaches such as reduced multiple-testing burden and a principled approach to the design of follow-up experiments. Our results demonstrate that PrediXcan can detect known and new genes associated with disease traits and provide insights into the mechanism of these associations. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well characterized, but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses, on the basis of analyses of 9,604 haemagglutinin sequences of human seasonal influenza viruses from 2000 to 2012. Whereas genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast Asia, genetic variants of A/H1N1 and B viruses persisted across several seasons and exhibited complex global dynamics with East and Southeast Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller, less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as probable drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology, and human behaviour. [ABSTRACT FROM AUTHOR]

Genetic variation influences the response of an individual to drug treatments. Understanding this variation has the potential to make therapy safer and more effective by determining selection and dosing of drugs for an individual patient. In the context of cancer, tumours may have specific disease-defining mutations, but a patient's germline genetic variation will also affect drug response (both efficacy and toxicity), and here we focus on how to study this variation. Advances in sequencing technologies, statistical genetics analysis methods and clinical trial designs have shown promise for the discovery of variants associated with drug response. We discuss the application of germline genetics analysis methods to cancer pharmacogenomics with a focus on the special considerations for study design. [ABSTRACT FROM AUTHOR]

Because only a small fraction of asbestos-exposed individuals develop malignant mesothelioma, and because mesothelioma clustering is observed in some families, we searched for genetic predisposing factors. We discovered germline mutations in the gene encoding BRCA1 associated protein-1 (BAP1) in two families with a high incidence of mesothelioma, and we observed somatic alterations affecting BAP1 in familial mesotheliomas, indicating biallelic inactivation. In addition to mesothelioma, some BAP1 mutation carriers developed uveal melanoma. We also found germline BAP1 mutations in 2 of 26 sporadic mesotheliomas; both individuals with mutant BAP1 were previously diagnosed with uveal melanoma. We also observed somatic truncating BAP1 mutations and aberrant BAP1 expression in sporadic mesotheliomas without germline mutations. These results identify a BAP1-related cancer syndrome that is characterized by mesothelioma and uveal melanoma. We hypothesize that other cancers may also be involved and that mesothelioma predominates upon asbestos exposure. These findings will help to identify individuals at high risk of mesothelioma who could be targeted for early intervention. [ABSTRACT FROM AUTHOR]

Although five-year survival rates for childhood acute lymphoblastic leukemia (ALL) are now over 80% in most industrialized countries, not all children have benefited equally from this progress. Ethnic differences in survival after childhood ALL have been reported in many clinical studies, with poorer survival observed among African Americans or those with Hispanic ethnicity when compared with European Americans or Asians. The causes of ethnic differences remain uncertain, although both genetic and non-genetic factors are likely important. Interrogating genome-wide germline SNP genotypes in an unselected large cohort of children with ALL, we observed that the component of genomic variation that co-segregated with Native American ancestry was associated with risk of relapse (P = 0.0029) even after adjusting for known prognostic factors (P = 0.017). Ancestry-related differences in relapse risk were abrogated by the addition of a single extra phase of chemotherapy, indicating that modifications to therapy can mitigate the ancestry-related risk of relapse. [ABSTRACT FROM AUTHOR]

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment. [ABSTRACT FROM AUTHOR]

Influenza virus remains a serious health threat, owing to its ability to evade immune surveillance through rapid genetic drift and reassortment. Here we used a human non-immune antibody phage-display library and the H5 hemagglutinin ectodomain to select ten neutralizing antibodies (nAbs) that were effective against all group 1 influenza viruses tested, including H5N1 'bird flu' and the H1N1 'Spanish flu'. The crystal structure of one such nAb bound to H5 shows that it blocks infection by inserting its heavy chain into a conserved pocket in the stem region, thus preventing membrane fusion. Nine of the nAbs employ the germline gene VH1-69, and all seem to use the same neutralizing mechanism. Our data further suggest that this region is recalcitrant to neutralization escape and that nAb-based immunotherapy is a promising strategy for broad-spectrum protection against seasonal and pandemic influenza viruses. [ABSTRACT FROM AUTHOR]

In addition to the differences between populations in transcriptional and translational regulation of genes, alternative pre-mRNA splicing (AS) is also likely to play an important role in regulating gene expression and generating variation in mRNA and protein isoforms. Recently, the genetic contribution to transcript isoform variation has been reported in individuals of recent European descent. We report here results of an investigation of the differences in AS patterns between human populations. AS patterns in 176 HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry were evaluated using the Affymetrix GeneChip® Human Exon 1.0 ST Array. A variety of biological processes such as response to stimulus and transcription were found to be enriched among the differentially spliced genes. The differentially spliced genes also include some involved in human diseases that have different prevalence or susceptibility between populations. The genetic contribution to the population differences in transcript isoform variation was then evaluated by a genome-wide association using the HapMap genotypic data on single nucleotide polymorphisms (SNPs). The results suggest that local and distant genetic variants account for a substantial fraction of the observed transcript isoform variation between human populations. Our findings provide new insights into the complexity of the human genome as well as the health disparities between the two populations. [ABSTRACT FROM AUTHOR]

It has been proposed that variation in calpain 10 ( CAPN10) contributes to the risk of type 2 diabetes (T2D). A previous survey of CAPN10 in ethnically diverse populations revealed an intronic region with a significant excess of polymorphism levels relative to inter-species sequence divergence, suggesting that this region was the target of long-standing balancing selection. Based on the thrifty genotype hypothesis, variation that increases risk to T2D in contemporary humans at one time conferred a survival advantage in ancestral populations. Thus, the signature of positive natural selection in a T2D candidate gene could identify a genomic region containing variation that influences disease susceptibility. Here, we investigate this hypothesis by re-sequencing the CAPN10 region with unusual polymorphism levels in T2D cases and controls ( n=91) from a Mexican American (MA) population, and by using networks to infer the evolutionary relationships between the major haplotypes. Haplotype tag SNPs (htSNPs) were then selected in each population sample and in MA cases and controls. By placing the htSNPs on the haplotype network, we investigate how cross-population differences in CAPN10 genetic architecture may affect the detection of the disease association. Interestingly, despite the small scale of our case-control study, we observe a nearly significant signal of association between T2D and variation in the putative target of balancing selection. Finally, we use phylogenetic shadowing across 10 primate species to search for conserved non-coding elements that may affect the expression and function of CAPN10. These elements are postulated to be the targets of long-standing balancing selection. [ABSTRACT FROM AUTHOR]

Type 2 or non-insulin-dependent diabetes mellitus (NIDDM) is the most common form of diabetes worldwide, affecting approximately 4% of the world's adult population. It is multifactorial in origin with both genetic and environmental factors contributing to its development. A genome-wide screen for type 2 diabetes genes carried out in Mexican Americans localized a susceptibility gene, designated NIDDM1, to chromosome 2. Here we describe the positional cloning of a gene located in the NIDDM1 region that shows association with type 2 diabetes in Mexican Americans and a Northern European population from the Botnia region of Finland. This putative diabetes-susceptibility gene encodes a ubiquitously expressed member of the calpain-like cysteine protease family, calpain-10 (CAPN10). This finding suggests a novel pathway that may contribute to the development of type 2 diabetes. [ABSTRACT FROM AUTHOR]

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

During the past decade, the genetics of type 1 (insulin-dependent) diabetes mellitus (IDDM) has been studied extensively and the disorder has become a paradigm for genetically complex diseases. Previous genome screens and studies focused on candidate genes have provided evidence for genetic linkage between polymorphic DNA markers and 15 putative IDDM susceptibility loci, designated IDDM1-IDDM15. We have carried out a second-generation screen of the genome for linkage and analysed the data by multipoint linkage methods. An initial panel of 212 affected sibpairs (ASPs) was genotyped for 438 markers spanning all autosomes, and an additional 467 ASPs were used for follow-up genotyping. Other than the well-established linkage with the HLA region at chromosome 6p21.3, there was only one region, located on chromosome 1q and not previously reported, where the log likelihood ratio (lod) was greater than 3. Lods between 1.0 and 1.8 were found in six other regions, three of which have been reported in other studies. Another reported region, on chromosome 6q and loosely linked to HLA, also had an elevated lod. Little or no support was found for most reported IDDM loci (lods were less than 1), despite larger sample sizes in the present study. [ABSTRACT FROM AUTHOR]

Hypertriglyceridemia is a common metabolic disorder with a major inherited component. In some individuals the condition is suspected to occur as a result of overproduction of apolipoprotein (apo)CIII, a major constituent of triglyceride-rich lipoproteins. Population studies have established an association with the apoCIII gene but the identity of the causal mutation remains unknown. In the present study we have examined a series of six 5′ polymorphic nucleotides (G to A, C to A, G to A, deletion of T, C to T, and T to C) that lie within the promoter region of the apoCIII gene for evidence of possible involvement in disease susceptibility. The polymorphic nucleotides at positions -455 and -482 reside within a negative insulin-response element. We show, in a community-based sample of 503 school children, that a DNA polymorphism (S2 allele) within the 3′-noncoding region of the apoCIII gene was associated with elevated apoCIII and triglyceride levels, but that the polymorphic nucleotides of the promoter were not. In addition, no obvious effect of any extended apoCIII promoter haplotype on plasma apoCIII or triglyceride levels, over and above that conferred by the presence of the S2 polymorphic nucleotide, was detected. These results demonstrate that none of the 5′ apoCIII polymorphisms can account for the association of the apoCIII gene locus with hypertriglyceridemia and, moreover, owing to linkage disequilibrium, raise the possibility that the region conferring susceptibility maps downstream, rather than upstream, of the apoCIII gene promoter sequences. [ABSTRACT FROM AUTHOR]

Complex disorders such as diabetes, cardiovascular disease, asthma, hypertension and psychiatric illnesses account for a large and disproportionate share of health care costs, but remain poorly characterized with respect to aetiology. The transmission of such disorders is complex, reflecting the actions and interactions of multiple genetic and environmental factors. Genetic analyses that allow for the simultaneous consideration of susceptibility from multiple regions may improve the ability to map genes for complex disorders, but such analyses are currently computationally intensive and narrowly focused. We describe here an approach to assessing the evidence for statistical interactions between unlinked regions that allows multipoint allele-sharing analysis to take the evidence for linkage at one region into account in assessing the evidence for linkage over the rest of the genome. Using this method, we show that the interaction of genes on chromosomes 2 (NIDDM1) and 15 (near CYP19) makes a contribution to susceptibility to type 2 diabetes in Mexican Americans from Starr County, Texas. [ABSTRACT FROM AUTHOR]

Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearman's ρ = 0.32, p < 10–16); and (3) the disease onset age and heritability are negatively correlated (ρ = −0.46, p < 10–16). Disease heritability and genetic correlations between traits depend on genetics, the environment and their interaction. Here, Jia et al. compute disease prevalence curves and disease embeddings from electronic health records and impute heritability for hundreds of diseases and genetic correlations for thousands of disease pairs. [ABSTRACT FROM AUTHOR]

Comments on anstudy by Morley and colleagues published in the same issue of "Nature" about the determination of genomic locations of genetic determinants that influence the variation in levels of gene expression between people. Determination of the baseline expression level of genes that are active in immortalized human B cells from 14 families; Limitations to the studies; Significance of researchers' identification of possible master regulators of baseline levels of gene expression.

This MERLIN is not a wizard, but a new software package offering more rapid calculation of multipoint linkage likelihoods in larger pedigrees than has been possible. The practical advances provided by MERLIN are certainly welcome, but perhaps we need a little magic as well. [ABSTRACT FROM AUTHOR]

A letter to the editor is presnted on the neccessity for a global initiative to share avian flu data.

Human diseases are traditionally studied as singular, independent entities, limiting researchers' capacity to view human illnesses as dependent states in a complex, homeostatic system. Here, using time-stamped clinical records of over 151 million unique Americans, we construct a disease representation as points in a continuous, high-dimensional space, where diseases with similar etiology and manifestations lie near one another. We use the UK Biobank cohort, with half a million participants, to perform a genome-wide association study of newly defined human quantitative traits reflecting individuals' health states, corresponding to patient positions in our disease space. We discover 116 genetic associations involving 108 genetic loci and then use ten disease constellations resulting from clustering analysis of diseases in the embedding space, as well as 30 common diseases, to demonstrate that these genetic associations can be used to robustly predict various morbidities., (© 2023. The Author(s).)

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches., (© 2023. The Author(s).)