Management of de novo metastatic hormone-sensitive prostate cancer: A comprehensive report of a single-center experience.

BACKGROUND: Upfront docetaxel or novel hormonal agents (NHA) such as abiraterone and enzalutamide have become the standard of care for metastatic hormone sensitive prostate cancer (mHSPC). We evaluated real-world management of patients treated with these agents at a single center. PATIENTS AND METHODS: Patients with de novo mHSPC treated with upfront docetaxel or an NHA between January 2014 and April 2019 at Mount Sinai Health System were included. We evaluated time to next treatment (TTNT), PSA progression free survival (PFS) and overall survival (OS) after initial treatment with these drugs. Kaplan Meier method and multivariable Cox proportional hazards models were used for analysis. We additionally assessed the prognostic value of post-treatment PSA. RESULTS: We identified 94 de novo mHSPC patients; 52 and 42 treated with upfront docetaxel and NHAs, respectively. NHAs were associated with a median TTNT of 20.7 months compared to 10.1 months with docetaxel (log-rank p = 0.023). We also observed median PSA PFS of 19 months for NHAs and 13.2 months for docetaxel (p = 0.069). However, OS between the two treatment groups was unchanged. Among docetaxel treated patients, TTNT was shorter among those with high metastasis burden (9.63 vs 25.5 months, p = 0.026) which was not observed among NHA treated patients (25.1 vs 20.7 months, p = 0.79). Regardless of treatment, lower post-treatment PSA levels were associated with improved TTNT (58.95 vs. 11.57 vs. 9.4 months for PSA ≤0.2, 0.2-0.4, >0.4ng/ml, respectively; p<0.001). CONCLUSION: Real world data demonstrated a shorter duration of treatment with docetaxel than NHAs, reflecting the time-limited nature of docetaxel regimens compared to the treat-till-progression approach of NHAs. While TTNT was generally longer for NHAs than docetaxel, some docetaxel-treated patients achieved significant periods of time off treatment. In addition, the depth of PSA response following combination treatment may hold prognostic value for mHSPC outcomes.

Extraction of Treatment Information From Electronic Health Records and Evaluation of Testosterone Recovery in Patients With Prostate Cancer.

PURPOSE: Data quality and standardization remain a challenge when analyzing real-world clinical data. We built a clinical research database, using machine learning and natural learning processing, and investigated factors influencing testosterone recovery (T-recovery) in patients with localized prostate cancer (LPC) after initial androgen deprivation therapy (ADT). METHODS: Medication and treatment-associated dates missing in structured tables were extracted from patient notes using ConceptMapper, an automated data extraction tool, standardized and curated in Sema4 clinical research database. ADT usage duration was evaluated, and T-recovery in patients with LPC was analyzed by the Kaplan-Meier method and multivariable Cox proportional hazards models. We assessed the prognostic value of post-ADT T-recovery with prostate-specific antigen progression-free survival and failure-free survival. RESULTS: In total, 4,125 of 30,832 (13.4%) patients with prostate cancer had medication exclusively from notes with high precision and recall, F1 score ≥ 0.95. Association of dates with medication usage had a F1 score of 0.76. ADT duration estimation had higher accuracy combining information from notes to tables from electronic medical record (70% v 45%). Baseline testosterone was the strongest predictor of T-recovery in these patients. Patients with a baseline testosterone ≥ 300 ng/dL recovered in 9.79 versus 38 months for patients with baseline testosterone < 300 ng/dL (P < .0001). Shorter prostate-specific antigen progression-free interval was observed for patients with T-recovery (≥ 300 ng/dL) at 6 months after ADT cessation compared with patients without T-recovery (< 300 ng/dL; 13.7 v 25.1 months; P = .055). CONCLUSION: We augmented structured electronic medical record data with data extracted from notes and improved the accuracy of medication information for patients. ADT exposure and T-recovery in patients with LPC produced results consistent with the literature and clinical experience and illustrates the power of applying machine learning methods to enhance the quality of real-world evidence in answering clinically relevant questions.

Targeted Next-Generation Sequencing Reveals Exceptionally High Rates of Molecular Driver Mutations in Never-Smokers With Lung Adenocarcinoma.

INTRODUCTION: Historically, high rates of actionable driver mutations have been reported in never-smokers with lung adenocarcinoma (ADC). In the era of modern, comprehensive cancer mutation sequencing, this relationship necessitates a more detailed analysis. METHODS: All Mount Sinai patients between January 1, 2015, and June 1, 2020, with a diagnosis of ADC of any stage with known smoking status who received genomic testing were included. Most patients were analyzed using the Sema4 hotspot panel or the Oncomine Comprehensive Assay version 3 next-generation sequencing (NGS) panel conducted at Sema4. Patients were considered fully genotyped if they were comprehensively analyzed for alterations in EGFR, KRAS, MET, ALK, RET, ROS1, BRAF, NTRK1-3, and ERBB2, otherwise they were considered partially genotyped. RESULTS: Two hundred and thirty-six never-smokers and 671 smokers met the above criteria. Of the never-smokers, 201 (85%) had a driver mutation with 167 (71%) considered actionable (ie, those with US Food and Drug Administration-approved agents). Among smokers, 439 (65%) had an identified driver mutation with 258 (38%) actionable (P < .0001). When comprehensively sequenced, 95% (70/74) of never-smokers had a driver mutation with 78% (58/74) actionable; whereas, for smokers, 75% (135/180) had a driver with only 47% (74/180) actionable (P < .0001). Within mutations groups, EGFR G719X and KRAS G12Cs were more common to smokers. For stage IV patients harboring EGFR-mutant tumors treated with EGFR-directed therapies, never-smokers had significantly improved OS compared to smokers (hazard ratio = 2.71; P = .025). In multivariable analysis, Asian ancestry and female sex remained significant predictors of (1) OS in stage IV patients and (2) likelihood of harboring a receptor of fusion-based driver. CONCLUSION: Comprehensive NGS revealed driver alterations in 95% of never-smokers, with the majority having an associated therapy available. All efforts should be exhausted to identify or rule out the presence of an actionable driver mutation in all metastatic lung ADC.

Impact of body mass index on the efficacy of aromatase inhibitors in patients with metastatic breast cancer.

PURPOSE: Higher levels of estrogen in obese patients may lead to incomplete inhibition by aromatase inhibitors (AIs). The aim of this study was to determine the impact of body mass index (BMI) on efficacy of AIs in patients with metastatic hormone receptor (HR)-positive breast cancer (BC). METHODS: We performed a retrospective chart review of all female patients with metastatic HR-positive BC on an AI in first- or second-line settings and seen at our academic institution between 2001 and 2020. The primary endpoint was progression-free survival (PFS), defined as the time from start of AI to disease progression or death from any cause. RESULTS: We identified 219 patients who had received an AI in the first- or second-line settings for metastatic HR-positive BC and with documented information on BMI. Of the 219 patients, 56% (123) had a low BMI (defined as < 27 kg/m2) and 44% (96) had a high BMI (≥ 27 kg/m2). The median PFS was 21.9 months (95% CI 14.5 to 28.4) in the low BMI group versus 20.2 months (95% CI 14.3 to 27.5) in the high BMI group (p = 0.73). CONCLUSION: While BMI influences efficacy of AIs in the adjuvant setting, our results suggest that in the metastatic setting, BMI may not impact the efficacy of AIs. This discrepancy could be due to other differences in disease characteristics that make complete aromatase inhibition more important in the adjuvant setting when disease burden is the lowest.

Human GPR17 missense variants identified in metabolic disease patients have distinct downstream signaling profiles.

GPR17 is a G-protein-coupled receptor (GPCR) implicated in the regulation of glucose metabolism and energy homeostasis. Such evidence is primarily drawn from mouse knockout studies and suggests GPR17 as a potential novel therapeutic target for the treatment of metabolic diseases. However, links between human GPR17 genetic variants, downstream cellular signaling, and metabolic diseases have yet to be reported. Here, we analyzed GPR17 coding sequences from control and disease cohorts consisting of individuals with adverse clinical metabolic deficits including severe insulin resistance, hypercholesterolemia, and obesity. We identified 18 nonsynonymous GPR17 variants, including eight variants that were exclusive to the disease cohort. We characterized the protein expression levels, membrane localization, and downstream signaling profiles of nine GPR17 variants (F43L, V96M, V103M, D105N, A131T, G136S, R248Q, R301H, and G354V). These nine GPR17 variants had similar protein expression and subcellular localization as wild-type GPR17; however, they showed diverse downstream signaling profiles. GPR17-G136S lost the capacity for agonist-mediated cAMP, Ca2+, and ß-arrestin signaling. GPR17-V96M retained cAMP inhibition similar to GPR17-WT, but showed impaired Ca2+ and ß-arrestin signaling. GPR17-D105N displayed impaired cAMP and Ca2+ signaling, but unaffected agonist-stimulated ß-arrestin recruitment. The identification and functional profiling of naturally occurring human GPR17 variants from individuals with metabolic diseases revealed receptor variants with diverse signaling profiles, including differential signaling perturbations that resulted in GPCR signaling bias. Our findings provide a framework for structure-function relationship studies of GPR17 signaling and metabolic disease.

Analysis of Real-World Data to Investigate the Impact of Race and Ethnicity on Response to Programmed Cell Death-1 and Programmed Cell Death-Ligand 1 Inhibitors in Advanced Non-Small Cell Lung Cancers.

BACKGROUND: Racial disparities among clinical trial participants present a challenge to assess whether trial results can be generalized into patients representing diverse races and ethnicities. The objective of this study was to evaluate the impact of race and ethnicity on treatment response in patients with advanced non-small cell lung cancer (aNSCLC) treated with programmed cell death-1 (PD-1) or programmed cell death-ligand 1 (PD-L1) inhibitors through analysis of real-world data (RWD). MATERIALS AND METHODS: A retrospective cohort study of 11,138 patients with lung cancer treated at hospitals within the Mount Sinai Health System was performed. Patients with confirmed aNSCLC who received anti-PD-1/PD-L1 treatment were analyzed for clinical outcomes. Our cohort included 249 patients with aNSCLC who began nivolumab, pembrolizumab, or atezolizumab treatment between November 2014 and December 2018. Time-to-treatment discontinuation (TTD) and overall survival (OS) were the analyzed clinical endpoints. RESULTS: After a median follow-up of 14.8 months, median TTD was 7.8 months (95% confidence interval, 5.4-not estimable [NE]) in 75 African American patients versus 4.6 (2.4-7.2) in 110 White patients (hazard ratio [HR], 0.63). Median OS was not reached (18.4-NE) in African American patients versus 11.6 months (9.7-NE) in White patients (HR, 0.58). Multivariable Cox regression conducted with potential confounders confirmed longer TTD (adjusted HR, 0.65) and OS (adjusted HR, 0.60) in African American versus White patients. Similar real-world response rate (42.6% vs. 43.5%) and disease control rate (59.6% vs. 56.5%) were observed in the African American and White patient populations. Further investigation revealed the African American patient group had lower incidence (14.7%) of putative hyperprogressive diseases (HPD) upon anti-PD-1/PD-L1 treatment than the White patient group (24.5%). CONCLUSION: Analysis of RWD showed longer TTD and OS in African American patients with aNSCLC treated with anti-PD-1/PD-L1 inhibitors. Lower incidence of putative HPD is a possible reason for the favorable outcomes in this patient population. IMPLICATIONS FOR PRACTICE: There is a significant underrepresentation of minority patients in randomized clinical trials, and this study demonstrates that real-world data can be used to investigate the impact of race and ethnicity on treatment response. In retrospective analysis of patients with advanced non-small cell lung cancer treated with programmed cell death-1 or programmed cell death-ligand 1 inhibitors, African American patients had significantly longer time-to-treatment discontinuation and longer overall survival. Analysis of real-world data can yield clinical insights and establish a more complete picture of medical interventions in routine clinical practice.

A composite biomarker of neutrophil-lymphocyte ratio and hemoglobin level correlates with clinical response to PD-1 and PD-L1 inhibitors in advanced non-small cell lung cancers.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been incorporated into various clinical oncology guidelines for systemic treatment of advanced non-small cell lung cancers (aNSCLC). However, less than 50% (and 20%) of the patients responded to the therapy as a first (or second) line of therapy. PD-L1 immunohistochemistry (IHC) is an extensively studied biomarker of response to ICI, but results from this test have equivocal predictive power. In order to identify other biomarkers that support clinical decision-making around whether to treat with ICIs or not, we performed a retrospective study of patients with aNSCLC who underwent ICI-based therapy in the Mount Sinai Health System between 2014 and 2019. METHODS: We analyzed data from standard laboratory tests performed in patients as a part of the routine clinical workup during treatment, including complete blood counts (CBC) and a comprehensive metabolic panel (CMP), to correlate test results with clinical response and survival. RESULTS: Of 11,138 NSCLC patients identified, 249 had been treated with ICIs. We found associations between high neutrophil-to-lymphocyte ratio (NLR ≥ 5) and poor survival in ICI-treated NSCLC. We further observed that sustained high NLR after initiation of treatment had a more profound impact on survival than baseline NLR, regardless of PD-L1 status. Hazard ratios when comparing patients with NLR ≥ 5 vs. NLR < 5 are 1.7 (p = 0.02), 3.4 (p = 4.2 × 10- 8), and 3.9 (p = 1.4 × 10- 6) at baseline, 2-8 weeks, and 8-14 weeks after treatment start, respectively. Mild anemia, defined as hemoglobin (HGB) less than 12 g/dL was correlated with survival independently of NLR. Finally, we developed a composite NLR and HGB biomarker. Patients with pretreatment NLR ≥ 5 and HGB < 12 g/dL had a median overall survival (OS) of 8.0 months (95% CI 4.5-11.5) compared to the rest of the cohort with a median OS not reached (95% CI 15.9-NE, p = 1.8 × 10- 5), and a hazard ratio of 2.6 (95% CI 1.7-4.1, p = 3.5 × 10- 5). CONCLUSIONS: We developed a novel composite biomarker for ICI-based therapy in NSCLC based on routine CBC tests, which may provide meaningful clinical utility to guide treatment decision. The results suggest that treatment of anemia to elevate HGB before initiation of ICI therapy may improve patient outcomes or the use of alternative non-chemotherapy containing regimens.

Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records.

OBJECTIVE: To assess association of clinical features on COVID-19 patient outcomes. DESIGN: Retrospective observational study using electronic medical record data. SETTING: Five member hospitals from the Mount Sinai Health System in New York City (NYC). PARTICIPANTS: 28 336 patients tested for SARS-CoV-2 from 24 February 2020 to 15 April 2020, including 6158 laboratory-confirmed COVID-19 cases. MAIN OUTCOMES AND MEASURES: Positive test rates and in-hospital mortality were assessed for different racial groups. Among positive cases admitted to the hospital (N=3273), we estimated HR for both discharge and death across various explanatory variables, including patient demographics, hospital site and unit, smoking status, vital signs, lab results and comorbidities. RESULTS: Hispanics (29%) and African Americans (25%) had disproportionately high positive case rates relative to their representation in the overall NYC population (p<0.05); however, no differences in mortality rates were observed in hospitalised patients based on race. Outcomes differed significantly between hospitals (Gray's T=248.9; p<0.05), reflecting differences in average baseline age and underlying comorbidities. Significant risk factors for mortality included age (HR 1.05, 95% CI 1.04 to 1.06; p=1.15e-32), oxygen saturation (HR 0.985, 95% CI 0.982 to 0.988; p=1.57e-17), care in intensive care unit areas (HR 1.58, 95% CI 1.29 to 1.92; p=7.81e-6) and elevated creatinine (HR 1.75, 95% CI 1.47 to 2.10; p=7.48e-10), white cell count (HR 1.02, 95% CI 1.01 to 1.04; p=8.4e-3) and body mass index (BMI) (HR 1.02, 95% CI 1.00 to 1.03; p=1.09e-2). Deceased patients were more likely to have elevated markers of inflammation. CONCLUSIONS: While race was associated with higher risk of infection, we did not find racial disparities in inpatient mortality suggesting that outcomes in a single tertiary care health system are comparable across races. In addition, we identified key clinical features associated with reduced mortality and discharge. These findings could help to identify which COVID-19 patients are at greatest risk of a severe infection response and predict survival.

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

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A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

BACKGROUND: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. RESULTS: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. CONCLUSION: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

Amino acid residues in five separate HLA genes can explain most of the known associations between the MHC and primary biliary cholangitis.

Primary Biliary Cholangitis (PBC) is a chronic autoimmune liver disease characterised by progressive destruction of intrahepatic bile ducts. The strongest genetic association is with HLA-DQA1*04:01, but at least three additional independent HLA haplotypes contribute to susceptibility. We used dense single nucleotide polymorphism (SNP) data in 2861 PBC cases and 8514 controls to impute classical HLA alleles and amino acid polymorphisms using state-of-the-art methodologies. We then demonstrated through stepwise regression that association in the HLA region can be largely explained by variation at five separate amino acid positions. Three-dimensional modelling of protein structures and calculation of electrostatic potentials for the implicated HLA alleles/amino acid substitutions demonstrated a correlation between the electrostatic potential of pocket P6 in HLA-DP molecules and the HLA-DPB1 alleles/amino acid substitutions conferring PBC susceptibility/protection, highlighting potential new avenues for future functional investigation.

Melanocortin 4 Receptor Pathway Dysfunction in Obesity: Patient Stratification Aimed at MC4R Agonist Treatment.

Context: The hypothalamic melanocortin 4 receptor (MC4R) pathway serves a critical role in regulating body weight. Loss of function (LoF) mutations in the MC4R pathway, including mutations in the pro-opiomelanocortin (POMC), prohormone convertase 1 (PCSK1), leptin receptor (LEPR), or MC4R genes, have been shown to cause early-onset severe obesity. Methods: Through a comprehensive epidemiological analysis of known and predicted LoF variants in the POMC, PCSK1, and LEPR genes, we sought to estimate the number of US individuals with biallelic MC4R pathway LoF variants. Results: We predict ~650 α-melanocyte-stimulating hormone (MSH)/POMC, 8500 PCSK1, and 3600 LEPR homozygous and compound heterozygous individuals in the United States, cumulatively enumerating >12,800 MC4R pathway-deficient obese patients. Few of these variants have been genetically diagnosed to date. These estimates increase when we include a small subset of less rare variants: ß-MSH/POMC,PCSK1 N221D, and a PCSK1 LoF variant (T640A). To further define the MC4R pathway and its potential impact on obesity, we tested associations between body mass index (BMI) and LoF mutation burden in the POMC, PCSK1, and LEPR genes in various populations. We show that the cumulative allele burden in individuals with two or more LoF alleles in one or more genes in the MC4R pathway are predisposed to a higher BMI than noncarriers or heterozygous LoF carriers with a defect in only one gene. Conclusions: Our analysis represents a genetically rationalized study of the hypothalamic MC4R pathway aimed at genetic patient stratification to determine which obese subpopulations should be studied to elucidate MC4R agonist (e.g., setmelanotide) treatment responsiveness.

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA. Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

A loss of function variant in CASP7 protects against Alzheimer's disease in homozygous APOE ε4 allele carriers.

BACKGROUND: Alzheimer's disease (AD) represents the most common form of dementia in elder populations with approximately 30 million cases worldwide. Genome wide genotyping and sequencing studies have identified many genetic variants associated with late-onset Alzheimer's disease (LOAD). While most of these variants are associated with increased risk of developing LOAD, only limited number of reports focused on variants that are protective against the disease. METHODS: Here we applied a novel approach to uncover protective alleles against AD by analyzing genetic and phenotypic data in Mount Sinai Biobank and Electronic Medical Record (EMR) databases. RESULTS: We discovered a likely loss-of-function small deletion variant in the caspase 7 (CASP7) gene associated with significantly reduced incidence of LOAD in carriers of the high-risk APOE ε4 allele. Further investigation of four independent cohorts of European ancestry revealed the protective effect of the CASP7 variant against AD is most significant in homozygous APOE ε4 allele carriers. Meta analysis of multiple datasets shows overall odds ratio = 0.45 (p = 0.004). Analysis of RNA sequencing derived gene expression data indicated the variant correlates with reduced caspase 7 expression in multiple brain tissues we examined. CONCLUSIONS: Taken together, these results are consistent with the notion that caspase 7 plays a key role in microglial activation driving neuro-degeneration during AD pathogenesis, and may explain the underlying genetic mechanisms that anti-inflammatory interventions in AD show greater benefit in APOE ε4 carriers than non-carriers. Our findings inform potential novel therapeutic opportunities for AD and warrant further investigations.

Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks.

MOTIVATION: Underrepresentation of racial groups represents an important challenge and major gap in phenomics research. Most of the current human phenomics research is based primarily on European populations; hence it is an important challenge to expand it to consider other population groups. One approach is to utilize data from EMR databases that contain patient data from diverse demographics and ancestries. The implications of this racial underrepresentation of data can be profound regarding effects on the healthcare delivery and actionability. To the best of our knowledge, our work is the first attempt to perform comparative, population-scale analyses of disease networks across three different populations, namely Caucasian (EA), African American (AA) and Hispanic/Latino (HL). RESULTS: We compared susceptibility profiles and temporal connectivity patterns for 1988 diseases and 37 282 disease pairs represented in a clinical population of 1 025 573 patients. Accordingly, we revealed appreciable differences in disease susceptibility, temporal patterns, network structure and underlying disease connections between EA, AA and HL populations. We found 2158 significantly comorbid diseases for the EA cohort, 3265 for AA and 672 for HL. We further outlined key disease pair associations unique to each population as well as categorical enrichments of these pairs. Finally, we identified 51 key 'hub' diseases that are the focal points in the race-centric networks and of particular clinical importance. Incorporating race-specific disease comorbidity patterns will produce a more accurate and complete picture of the disease landscape overall and could support more precise understanding of disease relationships and patient management towards improved clinical outcomes. CONTACTS: rong.chen@mssm.edu or joel.dudley@mssm.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of Genetic Analysis Workshop 18 data with gene-based penalized regression.

Under the premise that multiple causal variants exist within a disease gene and that we are underpowered to detect these variants individually, a variety of methods have been developed that attempt to cluster rare variants within a gene so that the variants may gather strength from one another. These methods group variants by gene or proximity, and test one gene or marker window at a time. We propose analyzing all genes simultaneously with a penalized regression method that enables grouping of all (rare and common) variants within a gene while subgrouping rare variants, thus borrowing strength from both rare and common variants within the same gene. We apply this approach using a burden based weighting of the rare variants to the Genetic Analysis Workshop 18 data.

Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age.

The genetic contribution to the variation in human lifespan is ∼ 25%. Despite the large number of identified disease-susceptibility loci, it is not known which loci influence population mortality. We performed a genome-wide association meta-analysis of 7729 long-lived individuals of European descent (≥ 85 years) and 16 121 younger controls (<65 years) followed by replication in an additional set of 13 060 long-lived individuals and 61 156 controls. In addition, we performed a subset analysis in cases aged ≥ 90 years. We observed genome-wide significant association with longevity, as reflected by survival to ages beyond 90 years, at a novel locus, rs2149954, on chromosome 5q33.3 (OR = 1.10, P = 1.74 × 10(-8)). We also confirmed association of rs4420638 on chromosome 19q13.32 (OR = 0.72, P = 3.40 × 10(-36)), representing the TOMM40/APOE/APOC1 locus. In a prospective meta-analysis (n = 34 103), the minor allele of rs2149954 (T) on chromosome 5q33.3 associates with increased survival (HR = 0.95, P = 0.003). This allele has previously been reported to associate with low blood pressure in middle age. Interestingly, the minor allele (T) associates with decreased cardiovascular mortality risk, independent of blood pressure. We report on the first GWAS-identified longevity locus on chromosome 5q33.3 influencing survival in the general European population. The minor allele of this locus associates with low blood pressure in middle age, although the contribution of this allele to survival may be less dependent on blood pressure. Hence, the pleiotropic mechanisms by which this intragenic variation contributes to lifespan regulation have to be elucidated.