Personalized medicine in a community health system: the NorthShore experience.

Genomic and personalized medicine implementation efforts have largely centered on specialty care in tertiary health systems. There are few examples of fully integrated care systems that span the healthcare continuum. In 2014, NorthShore University HealthSystem launched the Center for Personalized Medicine to catalyze the delivery of personalized medicine. Successful implementation required the development of a scalable family history collection tool, the Genetic and Wellness Assessment (GWA) and Breast Health Assessment (BHA) tools; integrated pharmacogenomics programming; educational programming; electronic medical record integration; and robust clinical decision support tools. To date, more than 225,000 patients have been screened for increased hereditary conditions, such as cancer risk, through these tools in primary care. More than 35,000 patients completed clinical genetic testing following GWA or BHA completion. An innovative program trained more than 100 primary care providers in genomic medicine, activated with clinical decision support and access to patient genetic counseling services and digital healthcare tools. The development of a novel bioinformatics platform (FLYPE) enabled the incorporation of genomics data into electronic medical records. To date, over 4,000 patients have been identified to have a pathogenic or likely pathogenic variant in a gene with medical management implications. Over 33,000 patients have clinical pharmacogenomics data incorporated into the electronic health record supported by clinical decision support tools. This manuscript describes the evolution, strategy, and successful multispecialty partnerships aligned with health system leadership that enabled the implementation of a comprehensive personalized medicine program with measurable patient outcomes through a genomics-enabled learning health system model that utilizes implementation science frameworks.

An Overview of Cancer in the First 315,000 All of Us Participants.

INTRODUCTION: The NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered. MATERIALS AND METHODS: This work was performed on data collected from the All of Us Research Program's 315,297 enrolled participants to date using the Researcher Workbench, where approved researchers can access and analyze All of Us data on cancer and other diseases. Cancer case ascertainment was performed using data from EHR and self-reported surveys across key factors. Distribution of cancer types and concordance of data sources by cancer site and demographics is analyzed. RESULTS AND DISCUSSION: Data collected from 315,297 participants resulted in 13,298 cancer cases detected in the survey (in 89,261 participants), 23,520 cancer cases detected in the EHR (in 203,813 participants), and 7,123 cancer cases detected across both sources (in 62,497 participants). Key differences in survey completion by race/ethnicity impacted the makeup of cohorts when compared to cancer in the EHR and national NCI SEER data. CONCLUSIONS: This study provides key insight into cancer detection in the All of Us Research Program and points to the existing strengths and limitations of All of Us as a platform for cancer research now and in the future.

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.

Sex-specific nicotine sensitization and imprinting of self-administration in rats inform GWAS findings on human addiction phenotypes.

Repeated nicotine exposure leads to sensitization (SST) and enhances self-administration (SA) in rodents. However, the molecular basis of nicotine SST and SA and their biological relevance to the mounting genome-wide association study (GWAS) loci of human addictive behaviors are poorly understood. Considering a gateway drug role of nicotine, we modeled nicotine SST and SA in F1 progeny of inbred rats (F344/BN) and conducted integrative genomics analyses. We unexpectedly observed male-specific nicotine SST and a parental effect of SA only present in paternal F344 crosses. Transcriptional profiling in the ventral tegmental area (VTA) and nucleus accumbens (NAc) core and shell further revealed sex- and brain region-specific transcriptomic signatures of SST and SA. We found that genes associated with SST and SA were enriched for those related to synaptic processes, myelin sheath, and tobacco use disorder or chemdependency. Interestingly, SST-associated genes were often downregulated in male VTA but upregulated in female VTA, and strongly enriched for smoking GWAS risk variants, possibly explaining the male-specific SST. For SA, we found widespread region-specific allelic imbalance of expression (AIE), of which genes showing AIE bias toward paternal F344 alleles in NAc core were strongly enriched for SA-associated genes and for GWAS risk variants of smoking initiation, likely contributing to the parental effect of SA. Our study suggests a mechanistic link between transcriptional changes underlying the NIC SST and SA and human nicotine addiction, providing a resource for understanding the neurobiology basis of the GWAS findings on human smoking and other addictive phenotypes.

A rare functional noncoding variant at the GWAS-implicated MIR137/MIR2682 locus might confer risk to schizophrenia and bipolar disorder.

Schizophrenia (SZ) genome-wide association studies (GWASs) have identified common risk variants in >100 susceptibility loci; however, the contribution of rare variants at these loci remains largely unexplored. One of the strongly associated loci spans MIR137 (miR137) and MIR2682 (miR2682), two microRNA genes important for neuronal function. We sequenced ∼6.9 kb MIR137/MIR2682 and upstream regulatory sequences in 2,610 SZ cases and 2,611 controls of European ancestry. We identified 133 rare variants with minor allele frequency (MAF) <0.5%. The rare variant burden in promoters and enhancers, but not insulators, was associated with SZ (p = 0.021 for MAF < 0.5%, p = 0.003 for MAF < 0.1%). A rare enhancer SNP, 1:g.98515539A>T, presented exclusively in 11 SZ cases (nominal p = 4.8 × 10(-4)). We further identified its risk allele T in 2 of 2,434 additional SZ cases, 11 of 4,339 bipolar (BP) cases, and 3 of 3,572 SZ/BP study controls and 1,688 population controls; yielding combined p values of 0.0007, 0.0013, and 0.0001 for SZ, BP, and SZ/BP, respectively. The risk allele T of 1:g.98515539A>T reduced enhancer activity of its flanking sequence by >50% in human neuroblastoma cells, predicting lower expression of MIR137/MIR2682. Both empirical and computational analyses showed weaker transcription factor (YY1) binding by the risk allele. Chromatin conformation capture (3C) assay further indicated that 1:g.98515539A>T influenced MIR137/MIR2682, but not the nearby DPYD or LOC729987. Our results suggest that rare noncoding risk variants are associated with SZ and BP at MIR137/MIR2682 locus, with risk alleles decreasing MIR137/MIR2682 expression.

La etiología de la esquizofrenia / The etiology of schizophrenia

Las investigaciones realizadas en los últimos años iniciaron una nueva era de conocimiento de los factores de riesgo de la esquizofrenia. Por otra parte, los métodos de estudio del genoma completo han revolucionado el campo del mapeado genético de la esquizofrenia. Estudios genéticos recientes sugieren que la variación genética rara y la variación genética común tienen una función importante en la arquitectura genética de la esquizofrenia, que el modelo poligénico es correcto, e indican una superposición de los factores genéticos que confieren susceptibilidad a la esquizofrenia y otros trastornos psiquiátricos, como el trastorno bipolar y el autismo (pleotropía). Los programas de resecuenciación del genoma completo permitirán una disección más profunda de la genética molecular de la enfermedad. Uno de los desafíos importantes de la psiquiatría genética es la traducción de las asociaciones estadísticas detectadas en estudios de genoma completo en una mejor comprensión fisiopatológica de la esquizofrenia.

Research conducted in recent years represents a new dawn of knowledge for the risk factors of schizophrenia, and genome-wide approaches have revolutionized the field of genetic mapping of schizophrenia. The aggregate genetic data increasingly support a combination of rare and common genetic variation in schizophrenia, a major role for polygenic inheritance, and a genetic overlap (pleiotropy) of schizophrenia and other psychiatric disorders, such as bipolar disorder and autism. A main challenge for the field is the translation of established genetic associations into a better pathophysiological understanding of schizophrenia. The current and upcoming resequencing programs - both exomes (all exons) and full genomes - and genome-wide transcriptional analyses will allow a more thorough dissection of the molecular genetics of the disorder.

Smoking and genetic risk variation across populations of European, Asian, and African American ancestry--a meta-analysis of chromosome 15q25.

Recent meta-analyses of European ancestry subjects show strong evidence for association between smoking quantity and multiple genetic variants on chromosome 15q25. This meta-analysis extends the examination of association between distinct genes in the CHRNA5-CHRNA3-CHRNB4 region and smoking quantity to Asian and African American populations to confirm and refine specific reported associations. Association results for a dichotomized cigarettes smoked per day phenotype in 27 datasets (European ancestry (N = 14,786), Asian (N = 6,889), and African American (N = 10,912) for a total of 32,587 smokers) were meta-analyzed by population and results were compared across all three populations. We demonstrate association between smoking quantity and markers in the chromosome 15q25 region across all three populations, and narrow the region of association. Of the variants tested, only rs16969968 is associated with smoking (P < 0.01) in each of these three populations (odds ratio [OR] = 1.33, 95% CI = 1.25-1.42, P = 1.1 × 10(-17) in meta-analysis across all population samples). Additional variants displayed a consistent signal in both European ancestry and Asian datasets, but not in African Americans. The observed consistent association of rs16969968 with heavy smoking across multiple populations, combined with its known biological significance, suggests rs16969968 is most likely a functional variant that alters risk for heavy smoking. We interpret additional association results that differ across populations as providing evidence for additional functional variants, but we are unable to further localize the source of this association. Using the cross-population study paradigm provides valuable insights to narrow regions of interest and inform future biological experiments.

Genomewide association analysis of symptoms of alcohol dependence in the molecular genetics of schizophrenia (MGS2) control sample.

BACKGROUND: While genetic influences on alcohol dependence (AD) are substantial, progress in the identification of individual genetic variants that impact on risk has been difficult. METHODS: We performed a genome-wide association study on 3,169 alcohol consuming subjects from the population-based Molecular Genetics of Schizophrenia (MGS2) control sample. Subjects were asked 7 questions about symptoms of AD which were analyzed by confirmatory factor analysis. Genotyping was performed using the Affymetrix 6.0 array. Three sets of analyses were conducted separately for European American (EA, n = 2,357) and African-American (AA, n = 812) subjects: individual single nucleotide polymorphisms (SNPs), candidate genes and enriched pathways using gene ontology (GO) categories. RESULTS: The symptoms of AD formed a highly coherent single factor. No SNP approached genome-wide significance. In the EA sample, the most significant intragenic SNP was in KCNMA1, the human homolog of the slo-1 gene in C. Elegans. Genes with clusters of significant SNPs included AKAP9, phosphatidylinositol glycan anchor biosynthesis, class G (PIGG), and KCNMA1. In the AA sample, the most significant intragenic SNP was CEACAM6 and genes showing empirically significant SNPs included KCNQ5, SLC35B4, and MGLL. In the candidate gene based analyses, the most significant findings were with ADH1C, nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1) and ankyrin repeat and kinase domain containing 1 (ANKK1) in the EA sample, and ADH5, POMC, and CHRM2 in the AA sample. The ALIGATOR program identified a significant excess of associated SNPs within and near genes in a substantial number of GO categories over a range of statistical stringencies in both the EA and AA sample. CONCLUSIONS: While we cannot be highly confident about any single result from these analyses, a number of findings were suggestive and worthy of follow-up. Although quite large samples will be needed to obtain requisite power, the study of AD symptoms in general population samples is a viable complement to case-control studies in identifying genetic risk variants for AD.