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BACKGROUND: In the randomized, controlled, phase III KEYNOTE-061 trial, second-line pembrolizumab did not significantly prolong overall survival (OS) versus paclitaxel in patients with PD-L1-positive (combined positive score ≥1) advanced gastric/gastroesophageal junction (G/GEJ) cancer but did elicit a longer duration of response and offered a favorable safety profile. This prespecified exploratory analysis was conducted to evaluate associations between tumor gene expression signatures and clinical outcomes in the phase III KEYNOTE-061 trial. METHODS: Using RNA sequencing data obtained from formalin-fixed, paraffin-embedded baseline tumor tissue samples, we evaluated the 18-gene T-cell-inflamed gene expression profile (TcellinfGEP) and 10 non-TcellinfGEP signatures (angiogenesis, glycolysis, granulocytic myeloid-derived suppressor cell (gMDSC), hypoxia, monocytic MDSC (mMDSC), MYC, proliferation, RAS, stroma/epithelial-to-mesenchymal transition/transforming growth factor-β, WNT). The association between each signature on a continuous scale and outcomes was analyzed using logistic (objective response rate (ORR)) and Cox proportional hazards regression (progression-free survival (PFS) and OS). One-sided (pembrolizumab) and two-sided (paclitaxel) p values were calculated for TcellinfGEP (prespecified α=0.05) and the 10 non-TcellinfGEP signatures (multiplicity-adjusted; prespecified α=0.10). RESULTS: RNA sequencing data were available for 137 patients in each treatment group. TcellinfGEP was positively associated with ORR (p=0.041) and PFS (p=0.026) for pembrolizumab but not paclitaxel (p>0.05). The TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR (p=0.077), PFS (p=0.057), and OS (p=0.033) for pembrolizumab, while the TcellinfGEP-adjusted glycolysis (p=0.018), MYC (p=0.057), and proliferation (p=0.002) signatures were negatively associated with OS for paclitaxel. CONCLUSIONS: This exploratory analysis of tumor TcellinfGEP showed associations with ORR and PFS for pembrolizumab but not for paclitaxel. TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR, PFS, and OS for pembrolizumab but not paclitaxel. These data suggest myeloid-driven suppression may play a role in resistance to PD-1 inhibition in G/GEJ cancer and support a strategy of considering immunotherapy combinations which target this myeloid axis. TRIAL REGISTRATION NUMBER: NCT02370498.

BackgroundIn the Children's Oncology Group ANBL1221 phase 2 trial for patients with first relapse/first declaration of refractory high-risk neuroblastoma, irinotecan and temozolomide (I/T) combined with either temsirolimus (TEMS) or immunotherapy (the anti-GD2 antibody dinutuximab (DIN) and granulocyte macrophage colony stimulating factory (GM-CSF)) was administered. The response rate among patients treated with I/T/DIN/GM-CSF in the initial cohort (n=17) was 53%; additional patients were enrolled to permit further evaluation of this chemoimmunotherapy regimen. Potential associations between immune-related biomarkers and clinical outcomes including response and survival were evaluated.MethodsPatients were evaluated for specific immunogenotypes that influence natural killer (NK) cell activity, including killer immunoglobulin-like receptors (KIRs) and their ligands, Fc gamma receptors, and NCR3. Total white cells and leucocyte subsets were assessed via complete blood counts, and flow cytometry of peripheral blood mononuclear cells was performed to assess the potential association between immune cell subpopulations and surface marker expression and clinical outcomes. Appropriate statistical tests of association were performed. The Bonferroni correction for multiple comparisons was performed where indicated.ResultsOf the immunogenotypes assessed, the presence or absence of certain KIR and their ligands was associated with clinical outcomes in patients treated with chemoimmunotherapy rather than I/T/TEMS. While median values of CD161, CD56, and KIR differed in responders and non-responders, statistical significance was not maintained in logistic regression models. White cell and neutrophil counts were associated with differences in survival outcomes, however, increases in risk of event in patients assigned to chemoimmunotherapy were not clinically significant.ConclusionsThese findings are consistent with those of prior studies showing that KIR/KIR-ligand genotypes are associated with clinical outcomes following anti-GD2 immunotherapy in children with neuroblastoma. The current study confirms the importance of KIR/KIR-ligand genotype in the context of I/T/DIN/GM-CSF chemoimmunotherapy administered to patients with relapsed or refractory disease in a clinical trial. These results are important because this regimen is now widely used for treatment of patients at time of first relapse/first declaration of refractory disease. Efforts to assess the role of NK cells and genes that influence their function in response to immunotherapy are ongoing.Trial registration numberNCT01767194.

BackgroundInsulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.MethodsWe conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P

BackgroundIdentifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450).ResultsThe NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays.ConclusionsWe developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.

AimsThe DNA marker HF183 is a partial 16S rRNA gene sequence highly specific to human-associated Bacteroides including Bacteroides dorei. While HF183 is used to assess human faecal contamination in aquatic environments worldwide, little is known about the existence of HF183 and B. dorei in human microbiomes outside of the human gastrointestinal tract and faeces.Methods and resultsPreviously published human skin and urine microbiome data sets from five independent human body skin studies, the Human Microbiome Project (HMP) and three independent human urine studies were analysed. The HF183 gene sequence was detected in all skin data sets, with the ratios of positive samples ranging from 0.5% to 36.3%. Popliteal fossa (knee), volar forearm and inguinal (groin) creases were identified as hot spots. HF183 was detected in two of three urine data sets, with ratios of positive samples ranging from 0% to 37.5%. All HF183-containing sequences from these data sets were classified as associated with B. dorei.ConclusionsHF183 is widespread on human skin and present in urine.Significance and impact of studySkin and urine microbiomes could be sources of HF183 to environmental waters. Such non-faecal sources of HF183 might explain low concentrations of HF183 in recreational waters when swimmers are present.

Antimicrobial resistance in N. gonorrhoeae is increasing globally, and ceftriaxone is the recommended treatment for empirical therapy in most settings. Developing molecular assays to detect decreased ceftriaxone susceptibility is critical. Using PathogenWatch, a public database of N. gonorrhoeae genomes, antibiotic susceptibility data and DNA sequences of different genes associated with ceftriaxone resistance were extracted. That information was used to determine the sensitivity and specificity of different molecular markers and algorithms to predict decreased susceptibility to ceftriaxone. A total of 12,943 N. gonorrhoeae genomes were extracted from the PathogenWatch database, of which 9,540 genomes were used in the analysis. The sensitivity and specificity of specific molecular markers and algorithms were largely consistent with prior reports. Small variation (

Rationale: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. Objectives: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. Methods: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. Measurements and Main Results: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV1% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV1 was 3.9% lower (95% confidence interval [CI], -6.55% to -1.26%) and emphysema (the percentage of lung attenuation areas

BackgroundThere is great interest in finding ways to identify patients who will develop toxicity to cancer therapies. This has become especially pressing in the era of immune therapy, where toxicity can be long-lasting and life-altering, and primarily comes in the form of immune-related adverse effects (irAEs). Treatment with the first drugs in this class, anti-programmed death 1 (anti-PD1)/programmed death-ligand 1 (PDL1) checkpoint therapies, results in grade 2 or higher irAEs in up to 25%-30% of patients, which occur most commonly within the first 6 months of treatment and can include arthralgias, rash, pruritus, pneumonitis, diarrhea and/or colitis, hepatitis, and endocrinopathies. We tested the hypothesis that germline microRNA pathway functional variants, known to predict altered systemic stress responses to cancer therapies, would predict irAEs in patients across cancer types.MethodsMicroRNA pathway variants were evaluated for an association with grade 2 or higher toxicity using four classifiers on 62 patients with melanoma, and then the panel's performance was validated on 99 patients with other cancer types. Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. The predicted probability of toxicity was evaluated for its association, if any, with response categories to anti-PD1/PDL1 therapy in the melanoma cohort.ResultsA biomarker panel was identified that predicts toxicity with 80% accuracy (F1=0.76, area under the curve (AUC)=0.82) in the melanoma training cohort and 77.6% accuracy (F1=0.621, AUC=0.778) in the pan-cancer validation cohort. In the melanoma cohort, the predictive probability of toxicity was not associated with response categories to anti-PD1/PDL1 therapy (p=0.70). In the same cohort, the most significant biomarker of toxicity in RAC1, predicting a greater than ninefold increased risk of toxicity (p

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

The development of genome-informed methods for identifying quantitative trait loci (QTL) and studying the genetic basis of quantitative variation in natural and experimental populations has been driven by advances in high-throughput genotyping. For many complex traits, the underlying genetic variation is caused by the segregation of one or more 'large-effect' loci, in addition to an unknown number of loci with effects below the threshold of statistical detection. The large-effect loci segregating in populations are often necessary but not sufficient for predicting quantitative phenotypes. They are, nevertheless, important enough to warrant deeper study and direct modelling in genomic prediction problems. We explored the accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability ([Formula: see text]) for large-effect loci underlying complex phenotypes. We found that commonly used statistical methods overestimate p and [Formula: see text]. The source of the upward bias was traced to inequalities between the expected values of variance components in the numerators and denominators of these parameters. Algebraic solutions for bias-correcting estimates of p and [Formula: see text] were found that only depend on the degrees of freedom and are constant for a given study design. We discovered that average semivariance methods, which have heretofore not been used in complex trait analyses, yielded unbiased estimates of p and [Formula: see text], in addition to best linear unbiased predictors of the additive and dominance effects of the underlying loci. The cryptic bias problem described here is unrelated to selection bias, although both cause the overestimation of p and [Formula: see text]. The solutions we described are predicted to more accurately describe the contributions of large-effect loci to the genetic variation underlying complex traits of medical, biological, and agricultural importance.

BackgroundPhase IIb clinical trial with isatuximab (Isa)-lenalidomide (Len)-dexamethasone (Dex) showed an improved progression-free survival (PFS) in patients with relapsed or refractory multiple myeloma (RRMM), but the efficacy varied by patient. Antibody-dependent cell-mediated cytotoxicity (ADCC) by natural killer (NK) cells plays a crucial role in arbitrating antitumor activities of therapeutic-antibodies. We tested if patient-specific genetic makeup known to set NK cell functional threshold influence response to Isa-Len-Dex therapy.MethodsWe characterized 57 patients with RRMM receiving Isa-Len-Dex for polymorphisms of killer-cell immunoglobulin-like receptors (KIR), human leukocyte antigen (HLA) class I, and FCGR3A loci. In vitro ADCC assay, coincubating primary NK cells expressing specific KIR repertoire with multiple myeloma cell lines (MM cells) expressing selected HLA class I ligands, was used to confirm the identified genetic correlatives of clinical response.ResultsPatients with KIR3DL2+ and its cognate-ligand HLA-A3/11+ had superior PFS than patients missing this combination (HR=0.43; p=0.02), while patients carrying KIR2DL1+ and HLA-C2C2+ compared with to patients missing this pair showed short PFS (HR=3.54; p=0.05). Patients with KIR3DL2+ and HLA-A3/11+ plus high-affinity FCGR3A-158V allele showed the most prolonged PFS (HR=0.35; p=0.007). Consistent with these clinical data, mechanistic experiments demonstrated that NK cells expressing KIR3DL2 trigger greater ADCC when MM cells express HLA-A3/11. Inversely, NK cells expressing KIR2DL1 do not kill if MM cells express the HLA-C2C2 ligand. NK cells expressing high-affinity FCGR3A-158VV-induced greater ADCC compared with those with low-affinity FCGR3A-158FF.ConclusionsOur results suggest that KIR3DL2+ and HLA-A3/11+ with FCGR3A-158V markers lead to enhanced Isa-dependent NK-mediated cytolysis against MM cells and results in improved PFS in patients with RRMM treated by Isa-Len-Dex. Moreover, the presence of KIR2DL1+ and HLA-C2C2+ identifies patients who may have a lower response to Isa-Len-Dex therapy linked to a reduced NK-mediated ADCC. These biomarkers could potentially identify, via precision medicine, patients more likely to respond to Isa-Len-Dex immunotherapy.Trial registration numberNCT01749969.

BackgroundCoronavirus Disease 2019 (Covid-19) continues to challenge the limits of our knowledge and our healthcare system. Here we sought to define the host immune response, a.k.a, the "cytokine storm" that has been implicated in fatal COVID-19 using an AI-based approach.MethodOver 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a 'seed' gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. An AI-based approach was used to explore the utility of the signature in navigating the uncharted territory of Covid-19, setting therapeutic goals, and finding therapeutic solutions.FindingsThe 166-gene signature was surprisingly conserved across all viral pandemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViP and severe-ViP signatures, respectively. The ViP signatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determine severity/fatality. Precise therapeutic goals could be formulated; these goals were met in high-dose SARS-CoV-2-challenged hamsters using either neutralizing antibodies that abrogate SARS-CoV-2•ACE2 engagement or a directly acting antiviral agent, EIDD-2801. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine prognosticated disease severity.InterpretationThe ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs.FundingThis work was supported by the National Institutes for Health (NIH) [grants CA151673 and GM138385 (to DS) and AI141630 (to P.G), DK107585-05S1 (SD) and AI155696 (to P.G, D.S and S.D), U19-AI142742 (to S.C, cchiCooperative Centers for Human Immunology)]; Research Grants Program Office (RGPO) from the University of California Office of the President (UCOP) (R00RG2628 & R00RG2642 to P.G, D.S and S.D); the UC San Diego Sanford Stem Cell Clinical Center (to P.G, D.S and S.D); LJI Institutional Funds (to S.C); the VA San Diego Healthcare System Institutional funds (to L.C.A). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists.One sentence summaryThe host immune response in COVID-19.

OBJECTIVE: Accumulating evidence from recent molecular diagnostic studies has indicated the prognostic significance of various genetic markers for patients with glioblastoma (GBM). To evaluate the impact of such genetic markers on prognosis, we retrospectively analyzed the outcomes of patients with IDH-wildtype GBM in our institution. In addition, to assess the impact of bevacizumab (BEV) treatment, we compared overall survival (OS) between the pre- and post-BEV eras. METHODS: We analyzed the data of 100 adult patients (over 18 years old) with IDH-wildtype GBM from our database between February 2006 and October 2018. Genetic markers, such as MGMT methylation status, EGFR amplification, CDKN2A homozygous deletion, and clinical factors were analyzed by evaluating the patients OS. RESULTS: CDKN2A homozygous deletion showed no significant impact on OS in patients with methylated MGMT status (p = 0.5268), whereas among patients with unmethylated MGMT status, there was a significant difference in OS between patients with and without CDKN2A homozygous deletion (median OS: 14.7 and 16.9 months, respectively, p = 0.0129). This difference was more evident in the pre-BEV era (median OS: 10.1 and 15.6 months, respectively, p = 0.0351) but has become nonsignificant in the post-BEV era (median OS: 16.0 and 16.9 months, respectively, p = 0.1010) due to OS improvement in patients with CDKN2A homozygous deletion. However, these findings could not be validated in The Cancer Genome Atlas cohort. CONCLUSIONS: MGMT and CDKN2A status subdivided our cohort into three race-specific groups with different prognoses. Our findings indicate that BEV approval in Japan led to OS improvement exclusively for patients with concurrent unmethylated MGMT status and CDKN2A homozygous deletion.

Although statins (3-hydroxy-3-methylglutaryl-CoA reductase inhibitors) have proven effective in reducing plasma low-density lipoprotein levels and risk of cardiovascular disease, their lipid lowering efficacy is highly variable among individuals. Furthermore, statin treatment carries a small but significant risk of adverse effects, most notably myopathy and new onset diabetes. Hence, identification of biomarkers for predicting patients who would most likely benefit from statin treatment without incurring increased risk of adverse effects can have a significant public health impact. In this review, we discuss the rationale for the use of subject-derived lymphoblastoid cell lines in studies of statin pharmacogenomics and describe a variety of approaches we have employed to identify novel genetic markers associated with interindividual variation in statin response.

Immune checkpoint inhibitors (ICI) can achieve durable responses in a subset of patients with locally advanced or metastatic urothelial carcinoma (aUC). The use of tumor genomic profiling in clinical practice may help suggest biomarkers to identify patients most likely to benefit from ICI. We undertook a retrospective analysis of patients treated with an ICI for aUC at a large academic medical center. Patient clinical and histopathological variables were collected. Responses to treatment were assessed for all patients with at least one post-baseline scan or clear evidence of clinical progression following treatment start. Genomic profiling information was also collected for patients when available. Associations between patient clinical/genomic characteristics and objective response were assessed by logistic regression; associations between the characteristics and progression-free survival (PFS) and overall survival (OS) were examined by Cox regression. Multivariable analyses were performed to identify independent prognostic factors. We identified 119 aUC patients treated with an ICI from December 2014 to January 2020. Genomic profiling was available for 78 patients. Overall response rate to ICI was 29%, and median OS (mOS) was 13.4 months. Favorable performance status at the start of therapy was associated with improved OS (HR 0.46, p=0.025) after accounting for other covariates. Similarly, the presence of a TERT promoter mutation was an independent predictor of improved PFS (HR 0.38, p=0.012) and OS (HR 0.32, p=0.037) among patients who had genomic profiling available. Patients with both a favorable performance status and a TERT promoter mutation had a particularly good prognosis with mOS of 21.1 months as compared with 7.5 months in all other patients (p=0.03). The presence of a TERT promoter mutation was an independent predictor of improved OS in a cohort of aUC patients treated with an ICI who had genomic data available. Most of the clinical and laboratory variables previously shown to be prognostic in aUC patients treated with chemotherapy did not have prognostic value among patients treated with an ICI. Genomic profiling may provide important prognostic information and affect clinical decision making in this patient population. Validation of these findings in prospective patient cohorts is needed.

Nicotine is inactivated by the polymorphic CYP2A6 enzyme to cotinine and then to 3'hydroxycotinine. The Nicotine Metabolite Ratio (NMR; 3'hydroxycotinine/cotinine) is a heritable nicotine metabolism biomarker, varies with sex and ancestry, and influences smoking cessation and disease risk. We conducted sex-stratified genome-wide association studies of the NMR in European American (EA) and African American (AA) smokers (NCT01314001, NCT00666978). In EA females (n = 389) and males (n = 541), one significant (P

BackgroundThe causes for thousands of individually rare recessive diseases have been discovered since the adoption of next generation sequencing (NGS). Following the molecular diagnosis in older children in a family, parents could use this information to opt for fetal genotyping in subsequent pregnancies, which could inform decisions about elective termination of pregnancy. The use of NGS diagnostic sequencing in families has not been demonstrated to yield benefit in subsequent pregnancies to reduce recurrence. Here we evaluated whether genetic diagnosis in older children in families supports reduction in recurrence of recessive neurogenetic disease.MethodsRetrospective study involving families with a child with a recessive pediatric brain disease (rPBD) that underwent NGS-based molecular diagnosis. Prenatal molecular testing was offered to couples in which a molecular diagnosis was made, to help couples seeking to prevent recurrence. With this information, families made decisions about elective termination. Pregnancies that were carried to term were assessed for the health of child and mother, and compared with historic recurrence risk of recessive disease.ResultsBetween 2010 and 2016, 1172 families presented with a child a likely rPBD, 526 families received a molecular diagnosis, 91 families returned to the clinic with 101 subsequent pregnancies, and 84 opted for fetal genotyping. Sixty tested negative for recurrence for the biallelic mutation in the fetus, and all, except for one spontaneous abortion, carried to term, and were unaffected at follow-up. Of 24 that genotyped positive for the biallelic mutation, 16 were electively terminated, and 8 were carried to term and showed features of disease similar to that of the older affected sibling(s). Among the 101 pregnancies, disease recurrence in living offspring deviated from the expected 25% to the observed 12% ([95% CI 0·04 to 0·20], p = 0·011).ConclusionsMolecular diagnosis in an older child, coupled with prenatal fetal genotyping in subsequent pregnancies and genetic counselling, allows families to make informed decisions to reduce recessive neurogenetic disease recurrence.

BackgroundWhether high blood pressure has a causal effect on cognitive function as early as middle age is unclear. We investigated whether high blood pressure (BP) causally impairs cognitive function at midlife using Mendelian Randomization (MR).MethodsWe applied a two-sample MR approach to investigate the causal relationship between BP and midlife cognitive performance measured by the Digit Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT), and Stroop Interference test. We used a total of 109 genetic polymorphisms with established associations with BP as instrumental variables and estimated gene-cognitive function association in 1369 middle-aged adults (Mean age (SD): 50.8 (3.3), 54.0% women) from the CARDIA study.ResultsA 10 mmHg increment in genetically-predicted systolic, diastolic, or pulse pressure was associated with a 4.9 to 7.7-point lower DSST score (P = 0.002, SBP; P = 0.005, DBP and P = 0.008, PP), while a 10 mmHg increment in genetically-predicted SBP was associated with a 0.7 point lower RAVLT and a 2.3 point higher Stroop (P = 0.046 and 0.011, respectively).ConclusionsThis MR analysis shows that high BP, especially SBP, is causally associated with poorer processing speed, verbal memory, and executive function during midlife. These findings emphasize the need for further investigation of the role and mechanisms of BP dysregulation on cognitive health in middle age and perhaps, more broadly, across the lifespan.

IntroductionMicrobial residents of the human oral cavity have long been a major focus of microbiology due to their influence on host health and intriguing patterns of site specificity amidst the lack of dispersal limitation. However, the determinants of niche partitioning in this habitat are yet to be fully understood, especially among taxa that belong to recently discovered branches of microbial life.ResultsHere, we assemble metagenomes from tongue and dental plaque samples from multiple individuals and reconstruct 790 non-redundant genomes, 43 of which resolve to TM7, a member of the Candidate Phyla Radiation, forming six monophyletic clades that distinctly associate with either plaque or tongue. Both pangenomic and phylogenomic analyses group tongue-specific clades with other host-associated TM7 genomes. In contrast, plaque-specific TM7 group with environmental TM7 genomes. Besides offering deeper insights into the ecology, evolution, and mobilome of cryptic members of the oral microbiome, our study reveals an intriguing resemblance between dental plaque and non-host environments indicated by the TM7 evolution, suggesting that plaque may have served as a stepping stone for environmental microbes to adapt to host environments for some clades of microbes. Additionally, we report that prophages are widespread among oral-associated TM7, while absent from environmental TM7, suggesting that prophages may have played a role in adaptation of TM7 to the host environment.ConclusionsOur data illuminate niche partitioning of enigmatic members of the oral cavity, including TM7, SR1, and GN02, and provide genomes for poorly characterized yet prevalent members of this biome, such as uncultivated Flavobacteriaceae.

BackgroundCurrent South American populations trace their origins mainly to three continental ancestries, i.e. European, Amerindian and African. Individual variation in relative proportions of each of these ancestries may be confounded with socio-economic factors due to population stratification. Therefore, ancestry is a potential confounder variable that should be considered in epidemiologic studies and in public health plans. However, there are few studies that have assessed the ancestry of the current admixed Chilean population. This is partly due to the high cost of genome-scale technologies commonly used to estimate ancestry. In this study we have designed a small panel of SNPs to accurately assess ancestry in the largest sampling to date of the Chilean mestizo population (n = 3349) from eight cities. Our panel is also able to distinguish between the two main Amerindian components of Chileans: Aymara from the north and Mapuche from the south.ResultsA panel of 150 ancestry-informative markers (AIMs) of SNP type was selected to maximize ancestry informativeness and genome coverage. Of these, 147 were successfully genotyped by KASPar assays in 2843 samples, with an average missing rate of 0.012, and a 0.95 concordance with microarray data. The ancestries estimated with the panel of AIMs had relative high correlations (0.88 for European, 0.91 for Amerindian, 0.70 for Aymara, and 0.68 for Mapuche components) with those obtained with AXIOM LAT1 array. The country's average ancestry was 0.53 ± 0.14 European, 0.04 ± 0.04 African, and 0.42 ± 0.14 Amerindian, disaggregated into 0.18 ± 0.15 Aymara and 0.25 ± 0.13 Mapuche. However, Mapuche ancestry was highest in the south (40.03%) and Aymara in the north (35.61%) as expected from the historical location of these ethnic groups. We make our results available through an online app and demonstrate how it can be used to adjust for ancestry when testing association between incidence of a disease and nongenetic risk factors.ConclusionsWe have conducted the most extensive sampling, across many different cities, of current Chilean population. Ancestry varied significantly by latitude and human development. The panel of AIMs is available to the community for estimating ancestry at low cost in Chileans and other populations with similar ancestry.

Meningiomas are the most common primary intracranial tumors, but the molecular drivers of meningioma tumorigenesis are poorly understood. We hypothesized that investigating intratumor heterogeneity in meningiomas would elucidate biologic drivers and reveal new targets for molecular therapy. To test this hypothesis, here we perform multiplatform molecular profiling of 86 spatially-distinct samples from 13 human meningiomas. Our data reveal that regional alterations in chromosome structure underlie clonal transcriptomic, epigenomic, and histopathologic signatures in meningioma. Stereotactic co-registration of sample coordinates to preoperative magnetic resonance images further suggest that high apparent diffusion coefficient (ADC) distinguishes meningioma regions with proliferating cells enriched for developmental gene expression programs. To understand the function of these genes in meningioma, we develop a human cerebral organoid model of meningioma and validate the high ADC marker genes CDH2 and PTPRZ1 as potential targets for meningioma therapy using live imaging, single cell RNA sequencing, CRISPR interference, and pharmacology.

Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80-93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93-98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89-98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care.

Gastrointestinal infections can be life threatening, but not much is known about the host's genetic contribution to susceptibility to gastrointestinal infections or the latter's association with psychiatric disorders. We utilized iPSYCH, a genotyped population-based sample of individuals born between 1981 and 2005 comprising 65,534 unrelated Danish individuals (45,889 diagnosed with mental disorders and 19,645 controls from a random population sample) in which all individuals were linked utilizing nationwide population-based registers to estimate the genetic contribution to susceptibility to gastrointestinal infections, identify genetic variants associated with gastrointestinal infections, and examine the link between gastrointestinal infections and psychiatric and neurodevelopmental disorders. The SNP heritability of susceptibility to gastrointestinal infections ranged from 3.7% to 6.4% on the liability scale. Significant correlations were found between gastrointestinal infections and the combined group of mental disorders (OR = 2.09; 95% CI: 1.82-2.4, P = 1.87 × 10-25). Correlations with autism spectrum disorder, attention deficit hyperactivity disorder, and depression were also significant. We identified a genome-wide significant locus associated with susceptibility to gastrointestinal infections (OR = 1.13; 95% CI: 1.08-1.18, P = 2.9 × 10-8), where the top SNP was an eQTL for the ABO gene. The risk allele was associated with reduced ABO expression, providing, for the first time, genetic evidence to support previous studies linking the O blood group to gastrointestinal infections. This study also highlights the importance of integrative work in genetics, psychiatry, infection, and epidemiology on the road to translational medicine.

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., triglycerides) is high or low relative to its distribution in the population. Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for 6227 offspring-parent pairs. Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), decreased 0.0047 ± 0.0007 (P = 2.9 × 10-14) for each one-percent decrement in fasting triglyceride concentrations, i.e., h2 ± SE were: 0.428 ± 0.059, 0.230 ± 0.030, 0.111 ± 0.015, 0.050 ± 0.016, and 0.033 ± 0.010 at the 90th, 75th, 50th, 25th, and 10th percentiles of the triglyceride distribution, respectively. Consistent with quantile-dependent expressivity, 11 drug studies report smaller genotype differences at lower (post-treatment) than higher (pre-treatment) triglyceride concentrations. This meant genotype-specific triglyceride changes could not move in parallel when triglycerides were decreased pharmacologically, so that subtracting pre-treatment from post-treatment triglyceride levels necessarily created a greater triglyceride decrease for the genotype with a higher pre-treatment value (purported precision-medicine genetic markers). In addition, sixty-five purported gene-environment interactions were found to be potentially attributable to triglyceride's quantile-dependent expressivity, including gene-adiposity (APOA5, APOB, APOE, GCKR, IRS-1, LPL, MTHFR, PCSK9, PNPLA3, PPARγ2), gene-exercise (APOA1, APOA2, LPL), gene-diet (APOA5, APOE, INSIG2, LPL, MYB, NXPH1, PER2, TNFA), gene-alcohol (ALDH2, APOA5, APOC3, CETP, LPL), gene-smoking (APOC3, CYBA, LPL, USF1), gene-pregnancy (LPL), and gene-insulin resistance interactions (APOE, LPL).

BACKGROUND: Tumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patients tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown. METHODS: Sequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient. RESULTS: Regression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data. CONCLUSIONS: TMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.

We sought to replicate and expand upon previous work demonstrating antenatal TTC9B and HP1BP3 gene DNA methylation is prospectively predictive of postpartum depression (PPD) with ~80% accuracy. In a preterm birth study from Emory, Illumina MethylEPIC microarray derived 1st but not 3rd trimester biomarker models predicted 3rd trimester Edinburgh Postnatal Depression Scale (EPDS) scores ≥ 13 with an AUC=0.8 (95% CI: 0.63-0.8). Bisulfite pyrosequencing derived biomarker methylation was generated using bisulfite pyrosequencing across all trimesters in a pregnancy cohort at UC Irvine and in 3rd trimester from an independent Johns Hopkins pregnancy cohort. A support vector machine model incorporating 3rd trimester EPDS scores, TTC9B, and HP1BP3 methylation status predicted 4 week to 6 week postpartum EPDS ≥ 13 from 3rd trimester blood in the UC Irvine cohort (AUC=0.78, 95% CI: 0.64-0.78) and from the Johns Hopkins cohort (AUC=0.84, 95% CI: 0.72-0.97), both independent of previous psychiatric diagnosis. Technical replicate predictions in a subset of the Johns Hopkins cohort exhibited strong cross experiment correlation. This study confirms the PPD prediction model has the potential to be developed into a clinical tool enabling the identification of pregnant women at future risk of PPD who may benefit from clinical intervention.

BackgroundArthralgia is a common and debilitating toxicity of aromatase inhibitors (AI) that leads to premature drug discontinuation. We sought to evaluate the clinical and genetic risk factors associated with AI-associated arthralgia (AIAA).MethodsWe performed a cross-sectional study among postmenopausal women with stage 0-III breast cancer who were prescribed a third-generation AI for adjuvant therapy. The primary outcome was patient-reported AIAA occurrence. We extracted and assayed germline DNA for single nucleotide polymorphisms (SNPs) of genes implicated in estrogen and inflammation pathways. Multivariable logistic regression models examined the association between demographic, clinical, and genetic factors and AIAA. Analyses were restricted to White participants.ResultsAmong 1049 White participants, 543 (52%) reported AIAA. In multivariable analyses, women who had a college education [Adjusted Odds Ratio (AOR) 1.49, 95% Confidence Interval (CI) 1.00-2.20], had a more recent transition into menopause (

BACKGROUND/AIM:This study aimed to measure the DNA methylation state of thousands of CpG islands in the blood of two monozygotic twins that were discordant for cardiovascular disease (CVD). Twin 1 had suffered myocardial infarction, while the other was healthy. PATIENTS AND METHODS:Since the aim of this study was to identify differentially methylated regions which might act as potential markers, reduced-representation bisulfite libraries were used for whole-genome methylation analysis. RESULTS:According to the analysis, 11 genes lipid droplet associated hydrolase (LDAH), apolipoprotein B (APOB), acyl-CoA synthetase medium chain family member 2A (ACSM2A), acyl-CoA synthetase medium chain family member 5(ACSM5), acyl-CoA synthetase family member 3 (ACSF3), carboxylesterase 1 (CES1), carboxylesterase 1 pseudogene 1 (CES1P1), AFG3 like matrix AAA peptidase subunit 2 (AFG3L2), iron-sulfur cluster assembly enzyme (ISCU), SEC14 like lipid binding 2 (SEC14L2) and microsomal triglyceride transfer protein (MTTP) were all hypomethylated in DNA from twin 2, the unaffected twin. Methylation changes were observed at different multiple loci between the twins, suggesting loci that are affected by disease status in identical genetic backgrounds. CONCLUSION:This twin study may contribute significantly to the understanding of the genetic basis of CVD and resulting myocardial infarction. This approach may allow identification of possible target loci associated with aberrant epigenetic regulation in CVD.

Gene-environment interactions (GxE) can be fundamental in applications ranging from functional genomics to precision medicine and is a conjectured source of substantial heritability. However, unbiased methods to profile GxE genome-wide are nascent and, as we show, cannot accommodate general environment variables, modest sample sizes, heterogeneous noise, and binary traits. To address this gap, we propose a simple, unifying mixed model for gene-environment interaction (GxEMM). In simulations and theory, we show that GxEMM can dramatically improve estimates and eliminate false positives when the assumptions of existing methods fail. We apply GxEMM to a range of human and model organism datasets and find broad evidence of context-specific genetic effects, including GxSex, GxAdversity, and GxDisease interactions across thousands of clinical and molecular phenotypes. Overall, GxEMM is broadly applicable for testing and quantifying polygenic interactions, which can be useful for explaining heritability and invaluable for determining biologically relevant environments.

Anorexia nervosa is a complex eating disorder with genetic, metabolic, and psychosocial underpinnings. Using genome-wide methods, recent studies have associated many genes with the disorder. We characterized these genes by projecting them into reference transcriptomic atlases of the prenatal and adult human brain to determine where these genes are expressed in fine detail. We found that genes from an induced stem cell study of anorexia nervosa cases are expressed at higher levels in the lateral parabrachial nucleus. Although weaker, expression enrichment of the adult lateral parabrachial is also found with genes from independent genetic studies. Candidate causal genes from the largest genetic study of anorexia nervosa to date were enriched for expression in the arcuate nucleus of the hypothalamus. We also found an enrichment of anorexia nervosa associated genes in the adult and fetal raphe and ventral tegmental areas. Motivated by enrichment of these feeding circuits, we tested if these genes respond to fasting in mice hypothalami, which highlighted the differential expression of Rps26 and Dalrd3. This work improves our understanding of the neurobiology of anorexia nervosa by suggesting disturbances in subcortical appetitive circuits.

Infections and mental disorders are two of the major global disease burdens. While correlations between mental disorders and infections have been reported, the possible genetic links between them have not been assessed in large-scale studies. Moreover, the genetic basis of susceptibility to infection is largely unknown, as large-scale genome-wide association studies of susceptibility to infection have been lacking. We utilized a large Danish population-based sample (N = 65,534) linked to nationwide population-based registers to investigate the genetic architecture of susceptibility to infection (heritability estimation, polygenic risk analysis, and a genome-wide association study (GWAS)) and examined its association with mental disorders (comorbidity analysis and genetic correlation). We found strong links between having at least one psychiatric diagnosis and the occurrence of infection (P = 2.16 × 10-208, OR = 1.72). The SNP heritability of susceptibility to infection ranged from ~2 to ~7% in samples of differing psychiatric diagnosis statuses (suggesting the environment as a major contributor to susceptibility), and polygenic risk scores moderately but significantly explained infection status in an independent sample. We observed a genetic correlation of 0.496 (P = 2.17 × 10-17) between a diagnosis of infection and a psychiatric diagnosis. While our GWAS did not identify genome-wide significant associations, we found 90 suggestive (P ≤ 10-5) associations for susceptibility to infection. Our findings suggest a genetic component in susceptibility to infection and indicate that the occurrence of infections in individuals with mental illness may be in part genetically driven.

Compelling preclinical studies indicate that low-dose carbon monoxide (CO) abrogates experimental lung fibrosis. We recently reported the results of a multicenter, double-blinded, clinical trial of inhaled CO in patients with idiopathic pulmonary fibrosis (IPF). Identifying no significantly changes in metalloproteinase-7 (MMP7) serum concentration, or secondary endpoints of physiologic measurements, hospitalization, death, or patient-reported outcomes. In the present study, we evaluated the effect of low dose CO exposure (100-200 ppm) for 12 weeks on genome-wide gene expression in peripheral blood mononuclear cells (PBMC) derived from these IPF study subjects. We conducted transcriptome profiling on 38 IPF subjects with time points available at 0, 12, and 24 weeks. Total RNA isolated from PBMCs was hybridized onto the Affymetrix Human Gene 2.0 ST Array. We identified 621 genes significantly upregulated in the 24-week CO exposed group compared with the 12-week. Pathway analysis demonstrated association with Oxidative Phosphorylation (adjusted P

Clinical trial designs targeting patient subgroups with certain genetic characteristics may enhance the efficiency of developing drugs for cardiovascular disease (CVD). To evaluate the extent to which genetic knowledge translates to the CVD pipeline, we analyzed how genomic biomarkers are utilized in trials. Phase II and III trial protocols for investigational new drugs for CVD and risk factors were evaluated for prospective and exploratory genomic biomarker use; drug targets were evaluated for the presence of evidence that genetic variations can impact CVD risk or drug response. We identified 134 programs (73 unique drug targets) and 147 clinical trials. Less than 1% (n = 1/147) trials used a genomic biomarker prospectively for in-trial enrichment despite 32% (n = 23/73) of the drug targets having evidence of genetic variations. Additionally, 46% (n = 68/147) of the trials specified exploratory biomarker use. The results highlight an opportunity for more targeted CVD drug development by leveraging genomic biomarker knowledge.

Between October 2021 and September 2022 Europe has suffered the most devastating highly pathogenic avian influenza (HPAI) epidemic with a total of 2,520 outbreaks in poultry, 227 outbreaks in captive birds, and 3,867 HPAI virus detections in wild birds. The unprecedent geographical extent (37 European countries affected) resulted in 50 million birds culled in affected establishments. In the current reporting period, between 10 September and 2 December 2022, 1,163 HPAI virus detections were reported in 27 European countries in poultry (398), captive (151) and wild birds (613). A decrease in HPAI virus detections in colony‐breeding seabirds species and an increase in the number of detections in waterfowl has been observed. The continuous circulation of the virus in the wild reservoir has led to the frequent introduction of the virus into poultry populations. It is suspected that waterfowl might be more involved than seabirds in the incursion of HPAI virus into poultry establishments. In the coming months, the increasing infection pressure on poultry establishments might increase the risk of incursions in poultry, with potential further spread, primarily in areas with high poultry densities. The viruses detected since September 2022 (clade 2.3.4.4b) belong to eleven genotypes, three of which have circulated in Europe during the summer months, while eight represent new genotypes. HPAI viruses were also detected in wild and farmed mammal species in Europe and North America, showing genetic markers of adaptation to replication in mammals. Since the last report, two A(H5N1) detections in humans in Spain, one A(H5N1), one A(H5N6) and one A(H9N2) human infection in China as well as one A(H5) infection without NA‐type result in Vietnam were reported, respectively. The risk of infection is assessed as low for the general population in the EU/EEA, and low to medium for occupationally exposed people. [ABSTRACT FROM AUTHOR]

Dupuytren's disease is a common inherited tissue-specific fibrotic disorder, characterized by progressive and irreversible fibroblastic proliferation affecting the palmar fascia of the hand. Although genome-wide association study (GWAS) have identified 24 genomic regions associated with Dupuytrens risk, the biological mechanisms driving signal at these regions remain elusive. We identify potential biological mechanisms for Dupuytren's disease by integrating the most recent, largest GWAS (3,871 cases and 4,686 controls) with eQTLs (47 tissue panels from five consortia, total n = 3,975) to perform a transcriptome-wide association study. We identify 43 tissue-specific gene associations with Dupuytren's risk, including one in a novel risk region. We also estimate the genome-wide genetic correlation between Dupuytren's disease and 45 complex traits and find significant genetic correlations between Dupuytren's disease and body mass index (BMI), type II diabetes, triglycerides, and high-density lipoprotein (HDL), suggesting a shared genetic etiology between these traits. We further examine local genetic correlation to identify 8 and 3 novel regions significantly correlated with BMI and HDL respectively. Our results are consistent with previous epidemiological findings showing that lower BMI increases risk for Dupuytren's disease. These 12 novel risk regions provide new insight into the biological mechanisms of Dupuytren's disease and serve as a starting point for functional validation.

Power calculation prior to a genetic experiment can help investigators choose the optimal sample size to detect a quantitative trait locus (QTL). Without the guidance of power analysis, an experiment may be underpowered or overpowered. Either way will result in wasted resource. QTL mapping and genome-wide association studies (GWAS) are often conducted using a linear mixed model (LMM) with controls of population structure and polygenic background using markers of the whole genome. Power analysis for such a mixed model is often conducted via Monte Carlo simulations. In this study, we derived a non-centrality parameter for the Wald test statistic for association, which allows analytical power analysis. We show that large samples are not necessary to detect a biologically meaningful QTL, say explaining 5% of the phenotypic variance. Several R functions are provided so that users can perform power analysis to determine the minimum sample size required to detect a given QTL with a certain statistical power or calculate the statistical power with given sample size and known values of other population parameters.

The microbiota of the built environment is an amalgamation of both human and environmental sources. While human sources have been examined within single-family households or in public environments, it is unclear what effect a large number of cohabitating people have on the microbial communities of their shared environment. We sampled the public and private spaces of a college dormitory, disentangling individual microbial signatures and their impact on the microbiota of common spaces. We compared multiple methods for marker gene sequence clustering and found that minimum entropy decomposition (MED) was best able to distinguish between the microbial signatures of different individuals and was able to uncover more discriminative taxa across all taxonomic groups. Further, weighted UniFrac- and random forest-based graph analyses uncovered two distinct spheres of hand- or shoe-associated samples. Using graph-based clustering, we identified spheres of interaction and found that connection between these clusters was enriched for hands, implicating them as a primary means of transmission. In contrast, shoe-associated samples were found to be freely interacting, with individual shoes more connected to each other than to the floors they interact with. Individual interactions were highly dynamic, with groups of samples originating from individuals clustering freely with samples from other individuals, while all floor and shoe samples consistently clustered together.IMPORTANCE Humans leave behind a microbial trail, regardless of intention. This may allow for the identification of individuals based on the "microbial signatures" they shed in built environments. In a shared living environment, these trails intersect, and through interaction with common surfaces may become homogenized, potentially confounding our ability to link individuals to their associated microbiota. We sought to understand the factors that influence the mixing of individual signatures and how best to process sequencing data to best tease apart these signatures.

A higher incidence of diabetes was observed among family members of individuals affected by Huntington's Disease with no follow-up studies investigating the genetic nature of the observation. Using a genome-wide association study (GWAS), RNA sequencing (RNA-Seq) analysis and western blotting of Rattus norvegicus and human, we were able to identify that the gene family of sortilin receptors was affected in Huntington's Disease patients. We observed that less than 5% of SNPs were of statistical significance and that sortilins and HLA/MHC gene expression or SNPs were associated with mutant huntingtin (mHTT). These results suggest that ST14A cells derived from R. norvegicus are a reliable model of HD, since sortilins were identified through analysis of the transcriptome in these cells. These findings help highlight the genes involved in mechanisms targeted by diabetes drugs, such as glucose transporters as well as proteins controlling insulin release related to mHTT. To the best of our knowledge, this is the first GWAS using RNA-Seq data from both ST14A rat HD cell model and human Huntington's Disease.

Sequencing-based studies have identified novel risk genes associated with severe epilepsies and revealed an excess of rare deleterious variation in less-severe forms of epilepsy. To identify the shared and distinct ultra-rare genetic risk factors for different types of epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,436 controls of European ancestry. We focused on three phenotypic groups: severe developmental and epileptic encephalopathies (DEEs), genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy; we saw the strongest enrichment in individuals with DEEs and the least strong in individuals with NAFE. Moreover, we found that inhibitory GABAA receptor genes were enriched for missense variants across all three classes of epilepsy, whereas no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEEs and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the lead associations; such genes included CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study, the largest epilepsy WES study to date, confirms a convergence in the genetics of severe and less-severe epilepsies associated with ultra-rare coding variation, and it highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology.

Mutations in gene regulatory elements have been associated with a wide range of complex neuropsychiatric disorders. However, due to their cell-type specificity and difficulties in characterizing their regulatory targets, the ability to identify causal genetic variants has remained limited. To address these constraints, we perform an integrative analysis of chromatin interactions, open chromatin regions and transcriptomes using promoter capture Hi-C, assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and RNA sequencing, respectively, in four functionally distinct neural cell types: induced pluripotent stem cell (iPSC)-induced excitatory neurons and lower motor neurons, iPSC-derived hippocampal dentate gyrus-like neurons and primary astrocytes. We identify hundreds of thousands of long-range cis-interactions between promoters and distal promoter-interacting regions, enabling us to link regulatory elements to their target genes and reveal putative processes that are dysregulated in disease. Finally, we validate several promoter-interacting regions by using clustered regularly interspaced short palindromic repeats (CRISPR) techniques in human excitatory neurons, demonstrating that CDK5RAP3, STRAP and DRD2 are transcriptionally regulated by physically linked enhancers.

Using high-resolution resting state functional magnetic resonance imaging (fMRI), the present study tested the hypothesis that ABCA7 genetic risk differentially affects intra-medial temporal lobe (MTL) functional connectivity between MTL subfields, versus internetwork connectivity of the MTL with the medial prefrontal cortex (mPFC), in nondemented older African Americans. Although the association of ABCA7 risk variants with Alzheimer's disease (AD) has been confirmed worldwide, its effect size on the relative odds of being diagnosed with AD is significantly higher in African Americans. However, little is known about the neural correlates of cognitive function in older African Americans and how they relate to AD risk conferred by ABCA7. In a case-control fMRI study of 36 healthy African Americans, we observed ABCA7 related impairments in behavioral generalization that was mediated by dissociation in entorhinal cortex (EC) resting state functional connectivity. Specifically, ABCA7 risk variant was associated with EC-hippocampus hyper-synchronization and EC-mPFC hypo-synchronization. Carriers of the risk genotype also had a significantly smaller anterolateral EC, despite our finding no group differences on standardized neuropsychological tests. Our findings suggest a model where impaired cortical connectivity leads to a more functionally isolated EC at rest, which translates into aberrant EC-hippocampus hyper-synchronization resulting in generalization deficits. While we cannot identify the exact mechanism underlying the observed alterations in EC structure and network function, considering the relevance of Aβ in ABCA7 related AD pathogenesis, the results of our study may reflect the synergistic reinforcement between amyloid and tau pathology in the EC, which significantly increases tau-induced neuronal loss and accelerates synaptic alterations. Finally, our results add to a growing literature suggesting that generalization of learning may be a useful tool for assessing the mild cognitive deficits seen in the earliest phases of prodromal AD, even before the more commonly reported deficits in episodic memory arise.

BackgroundBronchopulmonary dysplasia (BPD) is an orphan disease and advances in prevention and treatment are lacking. The clinical efficacy of systemic corticosteroid therapy to reduce the severity of lung disease and BPD is highly variable. Our objective was to assess whether candidate SNPs in corticosteroid metabolism and response genes are associated with short-term phenotypic response to systemic corticosteroids in infants at high risk for BPD.MethodsPharmacogenetic analysis of data from a large randomized controlled trial (TOLSURF) in infants treated with dexamethasone or hydrocortisone using multivariate linear regression. The primary outcome was a change in respiratory severity score (RSS, mean airway pressure x FiO2) at day 7 of corticosteroid treatment.Resultsrs7225082 in the intron of CRHR1 is significantly associated with the magnitude of decrease in RSS 7 days after starting treatment with systemic corticosteroid (meta-analysis P = 2.8 × 10-4). Each T allele at rs7225082 is associated with a smaller absolute change in RSS at day 7, i.e., less response to systemic corticosteroids.ConclusionsGenetic variability is associated with corticosteroid responsiveness with regard to respiratory status in preterm infants. Identification of genetic markers of corticosteroid responsiveness may allow for therapeutic individualization, with the goal of optimizing the risk-to-benefit ratio for an individual child.

Current cancer detection systems lack the required sensitivity to reliably detect minimal residual disease (MRD) and recurrence at the earliest stages when treatment would be most effective. To address this issue, we present a novel liquid biopsy approach that utilizes an integrated comprehensive droplet digital detection (IC3D) digital PCR system which combines microfluidic droplet partitioning, fluorescent multiplex PCR chemistry, and our rapid 3D, large-volume droplet counting technology. The IC3D ddPCR assay can detect cancer-specific, ultra-rare genomic targets due to large sample input and high degree of partitioning. We first demonstrate our droplet digital PCR assay can robustly detect common cancer mutants including KRAS G12D spiked in wild-type genomic background or isolated from patient samples with 100% specificity. We then demonstrate that the IC3D ddPCR system can detect oncogenic KRAS G12D mutant alleles against a background of wild-type genomes at a sensitivity of 0.00125-0.005% with a false positive rate of 0% which is 50 to 1000× more sensitive than existing commercial liquid biopsy ddPCR and qPCR platforms, respectively. In addition, our technology can uniquely enable detection of circulating tumor cells using their genetic markers without a pre-enrichment step, and analysis of total tumor DNA isolated from blood samples, which will increase clinical sensitivity and specificity, and minimize inter-assay variability. Therefore, our technology holds the potential to provide clinicians with a powerful decision-making tool to monitor and treat MRD with unprecedented sensitivity for earlier stage intervention.

BackgroundPrader-Willi syndrome (PWS) is due to errors in genomic imprinting. PWS is recognised as the most common known genetic cause of life-threatening obesity. This report summarises the frequency and further characterises the PWS molecular classes and maternal age effects.MethodsHigh-resolution microarrays, comprehensive chromosome 15 genotyping and methylation-specific multiplex ligation probe amplification were used to describe and further characterise molecular classes of maternal disomy 15 (UPD15) considering maternal age.ResultsWe summarised genetic data from 510 individuals with PWS and 303 (60%) had the 15q11-q13 deletion; 185 (36%) with UPD15 and 22 (4%) with imprinting defects. We further characterised UPD15 findings into subclasses based on the presence (size, location) or absence of loss of heterozygosity (LOH). Additionally, significantly older mothers (mean age=32.5 years vs 27.7 years) were found in the UPD15 group (n=145) compared with the deletion subtype (n=200).ConclusionsWe report on molecular classes in PWS using advanced genomic technology in the largest cohort to date. LOH patterns in UPD15 may impact the risk of having a second genetic condition if the mother carries a recessive mutant allele in the isodisomic region on chromosome 15. The risk of UPD15 may also increase with maternal age.

Linear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits. However, fully-specified models are computationally demanding and common simplifications often lead to reduced power or biased inference. We describe Grid-LMM (https://github.com/deruncie/GridLMM), an extendable algorithm for repeatedly fitting complex linear models that account for multiple sources of heterogeneity, such as additive and non-additive genetic variance, spatial heterogeneity, and genotype-environment interactions. Grid-LMM can compute approximate (yet highly accurate) frequentist test statistics or Bayesian posterior summaries at a genome-wide scale in a fraction of the time compared to existing general-purpose methods. We apply Grid-LMM to two types of quantitative genetic analyses. The first is focused on accounting for spatial variability and non-additive genetic variance while scanning for QTL; and the second aims to identify gene expression traits affected by non-additive genetic variation. In both cases, modeling multiple sources of heterogeneity leads to new discoveries.

BackgroundFactor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are associated with risk of arterial and venous thrombosis and with hemorrhagic disorders. We aimed to identify and functionally test novel genetic associations regulating plasma FVIII and VWF.MethodsWe meta-analyzed genome-wide association results from 46 354 individuals of European, African, East Asian, and Hispanic ancestry. All studies performed linear regression analysis using an additive genetic model and associated ≈35 million imputed variants with natural log-transformed phenotype levels. In vitro gene silencing in cultured endothelial cells was performed for candidate genes to provide additional evidence on association and function. Two-sample Mendelian randomization analyses were applied to test the causal role of FVIII and VWF plasma levels on the risk of arterial and venous thrombotic events.ResultsWe identified 13 novel genome-wide significant ( P≤2.5×10-8) associations, 7 with FVIII levels ( FCHO2/TMEM171/TNPO1, HLA, SOX17/RP1, LINC00583/NFIB, RAB5C-KAT2A, RPL3/TAB1/SYNGR1, and ARSA) and 11 with VWF levels ( PDHB/PXK/KCTD6, SLC39A8, FCHO2/TMEM171/TNPO1, HLA, GIMAP7/GIMAP4, OR13C5/NIPSNAP, DAB2IP, C2CD4B, RAB5C-KAT2A, TAB1/SYNGR1, and ARSA), beyond 10 previously reported associations with these phenotypes. Functional validation provided further evidence of association for all loci on VWF except ARSA and DAB2IP. Mendelian randomization suggested causal effects of plasma FVIII activity levels on venous thrombosis and coronary artery disease risk and plasma VWF levels on ischemic stroke risk.ConclusionsThe meta-analysis identified 13 novel genetic loci regulating FVIII and VWF plasma levels, 10 of which we validated functionally. We provide some evidence for a causal role of these proteins in thrombotic events.

Surfactant protein B (SFTPB) deficiency is a fatal disease affecting newborn infants. Surfactant is produced by alveolar type II cells which can be differentiated in vitro from patient specific induced pluripotent stem cell (iPSC)-derived lung organoids. Here we show the differentiation of patient specific iPSCs derived from a patient with SFTPB deficiency into lung organoids with mesenchymal and epithelial cell populations from both the proximal and distal portions of the human lung. We alter the deficiency by infecting the SFTPB deficient iPSCs with a lentivirus carrying the wild type SFTPB gene. After differentiating the mutant and corrected cells into lung organoids, we show expression of SFTPB mRNA during endodermal and organoid differentiation but the protein product only after organoid differentiation. We also show the presence of normal lamellar bodies and the secretion of surfactant into the cell culture medium in the organoids of lentiviral infected cells. These findings suggest that a lethal lung disease can be targeted and corrected in a human lung organoid model in vitro.

The inconsistency of open pharmacogenomics datasets produced by different studies limits the usage of such datasets in many tasks, such as biomarker discovery. Investigation of multiple pharmacogenomics datasets confirmed that the pairwise sensitivity data correlation between drugs, or rows, across different studies (drug-wise) is relatively low, while the pairwise sensitivity data correlation between cell-lines, or columns, across different studies (cell-wise) is considerably strong. This common interesting observation across multiple pharmacogenomics datasets suggests the existence of subtle consistency among the different studies (i.e., strong cell-wise correlation). However, significant noises are also shown (i.e., weak drug-wise correlation) and have prevented researchers from comfortably using the data directly. Motivated by this observation, we propose a novel framework for addressing the inconsistency between large-scale pharmacogenomics data sets. Our method can significantly boost the drug-wise correlation and can be easily applied to re-summarized and normalized datasets proposed by others. We also investigate our algorithm based on many different criteria to demonstrate that the corrected datasets are not only consistent, but also biologically meaningful. Eventually, we propose to extend our main algorithm into a framework, so that in the future when more datasets become publicly available, our framework can hopefully offer a "ground-truth" guidance for references.

Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.

ImportanceTo date, there is no diagnostic test for Kawasaki disease (KD). Diagnosis is based on clinical features shared with other febrile conditions, frequently resulting in delayed or missed treatment and an increased risk of coronary artery aneurysms.ObjectiveTo identify a whole-blood gene expression signature that distinguishes children with KD in the first week of illness from other febrile conditions.Design, setting, and participantsThe case-control study comprised a discovery group that included a training and test set and a validation group of children with KD or comparator febrile illness. The setting was pediatric centers in the United Kingdom, Spain, the Netherlands, and the United States. The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, and 242 bacterial or viral infections) and 55 healthy controls. The independent validation group comprised 102 patients with KD, including 72 in the first 7 days of illness, and 130 febrile controls. The study dates were March 1, 2009, to November 14, 2013, and data analysis took place from January 1, 2015, to December 31, 2017.Main outcomes and measuresWhole-blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (parallel regularized regression model search). The ability of transcript signatures (implemented as disease risk scores) to discriminate KD cases from controls was assessed by area under the curve (AUC), sensitivity, and specificity at the optimal cut point according to the Youden index.ResultsAmong 404 patients in the discovery set, there were 78 with KD (median age, 27 months; 55.1% male) and 326 febrile controls (median age, 37 months; 56.4% male). Among 202 patients in the validation set, there were 72 with KD (median age, 34 months; 62.5% male) and 130 febrile controls (median age, 17 months; 56.9% male). A 13-transcript signature identified in the discovery training set distinguished KD from other infectious and inflammatory conditions in the discovery test set, with AUC of 96.2% (95% CI, 92.5%-99.9%), sensitivity of 81.7% (95% CI, 60.0%-94.8%), and specificity of 92.1% (95% CI, 84.0%-97.0%). In the validation set, the signature distinguished KD from febrile controls, with AUC of 94.6% (95% CI, 91.3%-98.0%), sensitivity of 85.9% (95% CI, 76.8%-92.6%), and specificity of 89.1% (95% CI, 83.0%-93.7%). The signature was applied to clinically defined categories of definite, highly probable, and possible KD, resulting in AUCs of 98.1% (95% CI, 94.5%-100%), 96.3% (95% CI, 93.3%-99.4%), and 70.0% (95% CI, 53.4%-86.6%), respectively, mirroring certainty of clinical diagnosis.Conclusions and relevanceIn this study, a 13-transcript blood gene expression signature distinguished KD from other febrile conditions. Diagnostic accuracy increased with certainty of clinical diagnosis. A test incorporating the 13-transcript disease risk score may enable earlier diagnosis and treatment of KD and reduce inappropriate treatment in those with other diagnoses.