A Phase 1, randomized, double-blind, placebo-controlled, single- and multiple-dose escalation study to evaluate the safety and pharmacokinetics/pharmacodynamics of PF-06835375, a C-X-C chemokine receptor type 5 directed antibody, in patients with systemic lupus erythematosus or rheumatoid arthritis.

BACKGROUND: The objective of this study was to evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of PF­06835375, a potent selective afucosyl immunoglobulin G1 antibody targeting C-X-C chemokine receptor type 5 (CXCR5) that potentially depletes B cells, follicular T helper (Tfh) cells, and circulating Tfh-like (cTfh) cells, in patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). METHODS: This first-in-human, multicenter, double-blind, sponsor-open, placebo-controlled Phase 1 study recruited patients aged 18-70 years with SLE or RA. In Part A, patients received single doses of intravenous PF-06835375 (dose range: 0.03-6 mg) or placebo in six sequential single ascending dose (SAD) cohorts. In Part B, patients received repeat doses of subcutaneous PF-06835375 (dose range: 0.3-10 mg) or placebo on Days 1 and 29 in five multiple ascending dose (MAD) cohorts. Tetanus/Diphtheria (Td) and Meningococcal B (MenB/Trumenba™) vaccines were administered at Day 4 (Td and MenB) and Week 8 (MenB only) to assess PF-06835375 functional effects. Endpoints included treatment-emergent adverse events (TEAEs), pharmacokinetic parameters, pharmacodynamic effects on B and cTfh cells, and biomarker counts, vaccine response, and exploratory differential gene expression analysis. Safety, pharmacokinetic, and pharmacodynamic endpoints are summarized descriptively. The change from baseline of B and Tfh cell-specific genes over time was calculated using a prespecified mixed-effects model, with a false discovery rate < 0.05 considered statistically significant. RESULTS: In total, 73 patients were treated (SAD cohorts: SLE, n = 17; RA, n = 14; MAD cohorts: SLE, n = 22; RA, n = 20). Mean age was 53.3 years. Sixty-two (84.9%) patients experienced TEAEs (placebo n = 17; PF-06835375 n = 45); most were mild or moderate. Three (9.7%) patients experienced serious adverse events. Mean t1/2 ranged from 3.4-121.4 h (SAD cohorts) and 162.0-234.0 h (MAD cohorts, Day 29). B and cTfh cell counts generally showed dose-dependent reductions across cohorts (range of mean maximum depletion: 67.3-99.3%/62.4-98.7% [SAD] and 91.1-99.6%/89.5-98.1% [MAD], respectively). B cell-related genes and pathways were significantly downregulated in patients treated with PF-06835375. CONCLUSIONS: These data support further development of PF-06835375 to assess the clinical potential for B and Tfh cell depletion as a treatment for autoimmune diseases. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03334851.

Improvements in immune/melanocyte biomarkers with JAK3/TEC family kinase inhibitor ritlecitinib in vitiligo.

BACKGROUND: Vitiligo is an autoimmune depigmenting disorder with no effective and safe treatments. Its pathogenesis is not fully elucidated. OBJECTIVE: This substudy of a randomized, double-blind, placebo-controlled phase 2b trial (NCT03715829) evaluated effects of ritlecitinib, an oral JAK3/TEC family kinase inhibitor, on skin and blood biomarkers in participants with nonsegmental vitiligo (NSV). METHODS: Sixty-five adults with NSV participated in the substudy and received daily treatment for 24 weeks with placebo (n = 14) or ritlecitinib with or without a 4-week loading dose: 200 (loading dose)/50 mg (n = 13), 100/50 mg (n = 12), 50 mg (n = 11), 30 mg (n = 8), or 10 mg (n = 6). Skin (lesional and nonlesional) biopsy samples were obtained at baseline and at 4 and 24 weeks. Changes from baseline to weeks 4 and 24 in skin and blood molecular and cellular biomarkers were evaluated by RNA sequencing, quantitative real-time PCR, proteomic analysis, and flow cytometry. RESULTS: Ritlecitinib-treated groups showed downregulation of immune biomarkers and upregulation of melanocyte-related markers at weeks 4 and 24 compared to baseline and/or placebo. Significant reductions were seen in CD3+/CD8+ T-cell infiltrates, with significant increases in melanocyte markers (tyrosinase; Melan-A) in NSV lesions in the 50 mg ritlecitinib groups (both P < .05). There was significant, dose-dependent downregulation in T-cell activation, NK, cytotoxic, and regulatory markers in lesional skin (IL-2, IL2-RA, IL-15, CCR7, CD5, CRTAM, NCR1, XCL1, KIR3DL1, FASLG, KLRD; P < .05). TH1 and TH2 markers were also downregulated in lesional skin and blood in a dose-dependent manner (P < .05). Changes in immune biomarkers correlated with clinical response. CONCLUSIONS: Ritlecitinib significantly downregulated proinflammatory biomarkers and increased melanocyte products in skin and blood of participants with NSV, suggesting its potential in treatment. Ritlecitinib-mediated changes positively correlated with clinical response.

Baseline serum and stool microbiome biomarkers predict clinical efficacy and tissue molecular response after ritlecitinib induction therapy in ulcerative colitis.

BACKGROUND AND AIMS: Ritlecitinib, an oral JAK3/TEC family kinase inhibitor, was well- tolerated and efficacious in the phase 2b VIBRATO study in participants with moderate-to-severe ulcerative colitis (UC). The aim of this study was to identify baseline serum and microbiome markers that predict subsequent clinical efficacy and to develop noninvasive serum signatures as potential real-time noninvasive surrogates of clinical efficacy after ritlecitinib. METHODS: Tissue and peripheral blood proteomics, transcriptomics, and fecal metagenomics were performed on samples before and after 8-week oral ritlecitinib induction therapy (20 mg, 70 mg, 200 mg, or placebo once daily, N=39, 41, 33, and 18, respectively). Linear mixed models were used to identify baseline and longitudinal protein markers associated with efficacy. The combined predictivity of these proteins was evaluated using a logistic model with permuted efficacy data. Differential expression of fecal metagenomic was used to differentiate responders and nonresponders. RESULTS: Peripheral blood serum proteomics identified 4 baseline serum markers (LTA, CCL21, HLA-E, MEGF10) predictive of modified clinical remission (MR), endoscopic improvement (EI), histologic remission (HR), and integrative score of tissue molecular improvement. In responders, 37 serum proteins significantly changed at Week 8 compared with baseline (FDR<0.05); of these, changes in 4 (IL4R, TNFRSF4, SPINK4, and LAIR-1) predicted concurrent EI and HR responses. Fecal metagenomics analysis revealed baseline and treatment response signatures that correlated with EI, MR, and tissue molecular improvement. CONCLUSIONS: Blood and microbiome biomarkers stratify endoscopic, histologic, and tissue molecular response to ritlecitinib, which may help guide future precision medicine approaches to UC treatment.

Relationship Between Paraoxonase-1 Genotype and Activity, and Major Adverse Cardiovascular Events and Malignancies in Patients With Rheumatoid Arthritis Receiving Tofacitinib.

OBJECTIVE: This posthoc analysis investigated the relationship between paraoxonase-1 (PON1) genotype and activity, and risk of major adverse cardiovascular events (MACE) and malignancies in clinical studies of tofacitinib in patients with rheumatoid arthritis (RA). METHODS: Data were pooled from 9 phase II/III studies and the associated long-term extension studies (all completed by October 2017). PON1 activities in plasma were measured using paraoxon (paraoxonase activity), dihydrocoumarin (lactonase activity), and phenylacetate (arylesterase activity) as substrates. PON1 Q192R genotype effect on baseline PON1 activity was assessed using linear regression for each study, with fixed-effects metaanalysis across studies. MACE and malignancy risk by time-varying enzyme activity was determined using Cox proportional hazards regression. RESULTS: The analysis included 1969 patients with RA. Compared with the QQ genotype, the RR genotype had a significant positive association with baseline paraoxonase activity and a significant negative association with baseline lactonase and arylesterase activity (all P < 0.001). Time-varying models demonstrated a significant association of increased paraoxonase activity over time with lower risk of MACE (P < 0.001) and malignancies (excluding nonmelanoma skin cancer [NMSC]; P ≤ 0.05), even after controlling for risk factors identified in univariate analysis and RA disease activity. A similar trend was observed for lactonase and arylesterase for MACE. CONCLUSION: Higher paraoxonase activity over time was associated with significantly reduced risk of future MACE and malignancies (excluding NMSC), but not NMSC, in patients with RA receiving tofacitinib. Further investigation of PON1 as a novel functional lipid biomarker of MACE/malignancy risk in patients with RA is warranted. (ClinicalTrials.gov: NCT01059864, NCT00550446, NCT00687193, NCT00960440, NCT00814307, NCT00856544, NCT00853385, NCT00847613, NCT01039688, NCT00413699, NCT00661661).

PfaSTer: a machine learning-powered serotype caller for Streptococcus pneumoniae genomes.

Streptococcus pneumoniae (pneumococcus) is a leading cause of morbidity and mortality worldwide. Although multi-valent pneumococcal vaccines have curbed the incidence of disease, their introduction has resulted in shifted serotype distributions that must be monitored. Whole genome sequence (WGS) data provide a powerful surveillance tool for tracking isolate serotypes, which can be determined from nucleotide sequence of the capsular polysaccharide biosynthetic operon (cps). Although software exists to predict serotypes from WGS data, most are constrained by requiring high-coverage next-generation sequencing reads. This can present a challenge in respect of accessibility and data sharing. Here we present PfaSTer, a machine learning-based method to identify 65 prevalent serotypes from assembled S. pneumoniae genome sequences. PfaSTer combines dimensionality reduction from k-mer analysis with a Random Forest classifier for rapid serotype prediction. By leveraging the model's built-in statistical framework, PfaSTer determines confidence in its predictions without the need for coverage-based assessments. We then demonstrate the robustness of this method, returning >97 % concordance when compared to biochemical results and other in silico serotyping tools. PfaSTer is open source and available at: https://github.com/pfizer-opensource/pfaster.

Tandem mass tag-based quantitative proteomic profiling identifies candidate serum biomarkers of drug-induced liver injury in humans.

Diagnosis of drug-induced liver injury (DILI) and its distinction from other liver diseases are significant challenges in drug development and clinical practice. Here, we identify, confirm, and replicate the biomarker performance characteristics of candidate proteins in patients with DILI at onset (DO; n = 133) and follow-up (n = 120), acute non-DILI at onset (NDO; n = 63) and follow-up (n = 42), and healthy volunteers (HV; n = 104). Area under the receiver operating characteristic curve (AUC) for cytoplasmic aconitate hydratase, argininosuccinate synthase, carbamoylphosphate synthase, fumarylacetoacetase, fructose-1,6-bisphosphatase 1 (FBP1) across cohorts achieved near complete separation (range: 0.94-0.99) of DO and HV. In addition, we show that FBP1, alone or in combination with glutathione S-transferase A1 and leukocyte cell-derived chemotaxin 2, could potentially assist in clinical diagnosis by distinguishing NDO from DO (AUC range: 0.65-0.78), but further technical and clinical validation of these candidate biomarkers is needed.

Biomarkers to predict risk of venous thromboembolism in patients with rheumatoid arthritis receiving tofacitinib or tumour necrosis factor inhibitors.

OBJECTIVE: In the ORAL (Oral Rheumatoid Arthritis triaL) Surveillance study of patients with rheumatoid arthritis aged ≥50 years with ≥1 additional cardiovascular risk factor, incidence of pulmonary embolism was higher with tofacitinib 10 mg two times per day than with tumour necrosis factor inhibitors (TNFi). This exploratory post hoc analysis examined whether biomarkers explained the associations of tofacitinib versus TNFi with venous thromboembolism (VTE). METHODS: ORAL Surveillance was a prospective, open-label, event-driven, non-inferiority, postauthorisation safety study. Patients were randomised 1:1:1 to receive tofacitinib 5 mg or 10 mg two times per day or a TNFi. For this analysis, 294 soluble, proteomic, genetic and antibody biomarkers (of which 79 had a known role in inflammation, coagulation, vascular biology or Janus kinase signalling) were quantified in serum collected at baseline, month 12 and study end. RESULTS: Overall, 4362 patients were randomised and treated. The exploratory biomarker data set included 285 patients (57 VTE cases; 228 matched controls). D-dimer was quantified in 3732 patients (54 VTE cases; 3678 controls). No biomarker demonstrated a clear mechanistic association with the increased risk of VTE for tofacitinib versus TNFi. Month 12 D-dimer levels were positively associated with risk of a subsequent VTE within the tofacitinib 5 mg and 10 mg two times per day arms. CONCLUSIONS: Overall, this post hoc analysis did not identify biomarkers that explained the increased VTE risk for tofacitinib versus TNFi. Individual VTE risk should be considered when making decisions about initiation or maintenance of tofacitinib treatment. TRIAL REGISTRATION NUMBER: NCT02092467; ClinicalTrials.gov.

A shared tissue transcriptome signature and pathways in psoriasis and ulcerative colitis.

Despite multiple efficacious therapies in common between psoriasis (PS) and Ulcerative Colitis (UC), mechanisms underlying their common pathophysiology remain largely unclear. Here we sought to establish a link by evaluating expression differences and pathway alterations in diseased tissues. We identified two sets of differentially expressed genes (DEGs) between lesional and nonlesional tissues in meta-analyses of data collected from baseline samples in 3 UC and then 3 PS available clinical studies from Pfizer. A shared gene signature was defined by 190 DEGs common to both diseases. Commonly dysregulated pathways identified via enrichment analysis include interferon signaling, partly driven by genes IFI6, CXCL9, CXCL10 and CXCL11, which may attract chemotaxis of Th1 cells to inflammatory sites; IL-23 pathway (IL-23A, CCL20, PI3, CXCL1, LCN2); and Th17 pathway except IL-17A. Elevated expression of costimulatory molecules ICOS and CTLA4 suggests ongoing T-cell activation in both diseases. The clinical value of the shared signature is demonstrated by a gene set improvement score reflecting post-treatment molecular improvement for each disease. This is the first study using transcriptomic meta-analysis to define a tissue gene signature and pathways dysregulated in both PS and UC. These findings suggest immune mechanisms may initiate and sustain inflammation similarly in the two diseases.

An optimal variant to gene distance window derived from an empirical definition of cis and trans protein QTLs.

BACKGROUND: A genome-wide association study (GWAS) correlates variation in the genotype with variation in the phenotype across a cohort, but the causal gene mediating that impact is often unclear. When the phenotype is protein abundance, a reasonable hypothesis is that the gene encoding that protein is the causal gene. However, as variants impacting protein levels can occur thousands or even millions of base pairs from the gene encoding the protein, it is unclear at what distance this simple hypothesis breaks down. RESULTS: By making the simple assumption that cis-pQTLs should be distance dependent while trans-pQTLs are distance independent, we arrive at a simple and empirical distance cutoff separating cis- and trans-pQTLs. Analyzing a recent large-scale pQTL study (Pietzner in Science 374:eabj1541, 2021) we arrive at an estimated distance cutoff of 944 kilobasepairs (95% confidence interval: 767-1,161) separating the cis and trans regimes. CONCLUSIONS: We demonstrate that this simple model can be applied to other molecular GWAS traits. Since much of biology is built on molecular traits like protein, transcript and metabolite abundance, we posit that the mathematical models for cis and trans distance distributions derived here will also apply to more complex phenotypes and traits.

Genome-wide pharmacogenetics of anti-drug antibody response to bococizumab highlights key residues in HLA DRB1 and DQB1.

In this largest to-date genetic analysis of anti-drug antibody (ADA) response to a therapeutic monoclonal antibody (MAb), genome-wide association was performed for five measures of ADA status among 8844 individuals randomized to bococizumab, which targets PCSK9 for LDL-C lowering and cardiovascular protection. Index associations prioritized specific amino acid substitutions at the DRB1 and DQB1 MHC class II genes rather than canonical haplotypes. Two clusters of missense variants at DRB1 were associated with general ADA measures (residues 9, 11, 13; and 96, 112, 120, 180) and a third cluster of missense variants in DQB1 was associated with ADA measures including neutralizing antibody (NAb) titers (residues 66, 67, 71, 74, 75). The structural disposition of the missense substitutions implicates peptide antigen binding and CD4 effector function, mechanisms that are potentially generalizable to other therapeutic mAbs.Clinicaltrials.gov: NCT01968954, NCT01968967, NCT01968980, NCT01975376, NCT01975389, NCT02100514.

Antitumor Necrosis Factor-like Ligand 1A Therapy Targets Tissue Inflammation and Fibrosis Pathways and Reduces Gut Pathobionts in Ulcerative Colitis.

BACKGROUND: The first-in-class treatment PF-06480605 targets the tumor necrosis factor-like ligand 1A (TL1A) molecule in humans. Results from the phase 2a TUSCANY trial highlighted the safety and efficacy of PF-06480605 in ulcerative colitis. Preclinical and in vitro models have identified a role for TL1A in both innate and adaptive immune responses, but the mechanisms underlying the efficacy of anti-TL1A treatment in inflammatory bowel disease (IBD) are not known. METHODS: Here, we provide analysis of tissue transcriptomic, peripheral blood proteomic, and fecal metagenomic data from the recently completed phase 2a TUSCANY trial and demonstrate endoscopic improvement post-treatment with PF-06480605 in participants with ulcerative colitis. RESULTS: Our results revealed robust TL1A target engagement in colonic tissue and a distinct colonic transcriptional response reflecting a reduction in inflammatory T helper 17 cell, macrophage, and fibrosis pathways in patients with endoscopic improvement. Proteomic analysis of peripheral blood revealed a corresponding decrease in inflammatory T-cell cytokines. Finally, microbiome analysis showed significant changes in IBD-associated pathobionts, Streptococcus salivarius, S. parasanguinis, and Haemophilus parainfluenzae post-therapy. CONCLUSIONS: The ability of PF-06480605 to engage and inhibit colonic TL1A, targeting inflammatory T cell and fibrosis pathways, provides the first-in-human mechanistic data to guide anti-TL1A therapy for the treatment of IBD.

Evaluating the Sensitivity and Specificity of Promising Circulating Biomarkers to Diagnose Liver Injury in Humans.

Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and postmarketing. The objective of this study was to evaluate the diagnostic performance of promising biomarkers of liver injury-glutamate dehydrogenase (GLDH), cytokeratin-18 (K18), caspase-cleaved K18 (ccK18), osteopontin (OPN), macrophage colony-stimulating factor (MCSF), MCSF receptor (MCSFR), and microRNA-122 (miR-122) in comparison to the traditional biomarker alanine aminotransferase (ALT). Biomarkers were evaluated individually and as a multivariate model in a cohort of acetaminophen overdose (n = 175) subjects and were further tested in cohorts of healthy adults (n = 135), patients with liver damage from various causes (n = 104), and patients with damage to the muscle (n = 74), kidney (n = 40), gastrointestinal tract (n = 37), and pancreas (n = 34). In the acetaminophen cohort, a multivariate model with GLDH, K18, and miR-122 was able to detect DILI more accurately than individual biomarkers alone. Furthermore, the three-biomarker model could accurately predict patients with liver injury compared with healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract, and kidney. Expression of K18, GLDH, and miR-122 was evaluated using a database of transcriptomic profiles across multiple tissues/organs in humans and rats. K18 mRNA (Krt18) and MiR-122 were highly expressed in liver whereas GLDH mRNA (Glud1) was widely expressed. We performed a comprehensive, comparative performance assessment of 7 promising biomarkers and demonstrated that a 3-biomarker multivariate model can accurately detect liver injury.

Multiplex proteomics identifies novel CSF and plasma biomarkers of early Alzheimer's disease.

To date, the development of disease-modifying therapies for Alzheimer's disease (AD) has largely focused on the removal of amyloid beta Aß fragments from the CNS. Proteomic profiling of patient fluids may help identify novel therapeutic targets and biomarkers associated with AD pathology. Here, we applied the Olink™ ProSeek immunoassay to measure 270 CSF and plasma proteins across 415 Aß- negative cognitively normal individuals (Aß- CN), 142 Aß-positive CN (Aß+ CN), 50 Aß- mild cognitive impairment (MCI) patients, 75 Aß+ MCI patients, and 161 Aß+ AD patients from the Swedish BioFINDER study. A validation cohort included 59 Aß- CN, 23 Aß- + CN, 44 Aß- MCI and 53 Aß+ MCI. To compare protein concentrations in patients versus controls, we applied multiple linear regressions adjusting for age, gender, medications, smoking and mean subject-level protein concentration, and corrected findings for false discovery rate (FDR, q < 0.05). We identified, and replicated, altered levels of ten CSF proteins in Aß+ individuals, including CHIT1, SMOC2, MMP-10, LDLR, CD200, EIF4EBP1, ALCAM, RGMB, tPA and STAMBP (- 0.14 < d < 1.16; q < 0.05). We also identified and replicated alterations of six plasma proteins in Aß+ individuals OSM, MMP-9, HAGH, CD200, AXIN1, and uPA (- 0.77 < d < 1.28; q < 0.05). Multiple analytes associated with cognitive performance and cortical thickness (q < 0.05). Plasma biomarkers could distinguish AD dementia (AUC = 0.94, 95% CI = 0.87-0.98) and prodromal AD (AUC = 0.78, 95% CI = 0.68-0.87) from CN. These findings reemphasize the contributions of immune markers, phospholipids, angiogenic proteins and other biomarkers downstream of, and potentially orthogonal to, Aß- and tau in AD, and identify candidate biomarkers for earlier detection of neurodegeneration.

Self-report data as a tool for subtype identification in genetically-defined Parkinson's Disease.

Through a targeted recruitment 23andMe has collected DNA and patient-reported symptoms from more than 10,000 subjects reporting a physician-verified diagnosis of PD. This study evaluated the potential of self-report, web-based questionnaires to rapidly assess disease natural history and symptomology in genetically-defined PD populations. While average age-at-diagnosis was significantly lower in GBA mutation carriers compared to idiopathic PD, or iPD (idiopathic PD, defined as no GBA mutations and no LRRK2 G2019S mutation), there were no significant differences in symptoms. Conversely, LRRK2 G2019S carrier status significantly associated with reporting of milder daily symptoms of lightheadedness and several differences were observed at a false discovery rate < 0.1, including increased reporting of changes in walking as an initial symptom of disease, decreased reporting of lightheadedness upon standing, and milder symptoms related to daily functioning. The subclinical differences in symptoms reported by LRRK2 G2019S carriers suggest differences in underlying pathophysiology and/or disease progression in LRRK2 carriers compared to iPD. Importantly, we confirm previous findings in PD genetic subsets where disease characteristics were ascertained through clinical exam. Overall, these data support the effective use of self-report and genetic data to rapidly analyze information from a large disease population or difficult to identify genetic subgroups.

Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib.

BACKGROUND: Early detection of adverse effects of novel therapies and understanding of their mechanisms could improve the safety and efficiency of drug development. We have retrospectively applied large-scale proteomics to blood samples from ILLUMINATE (Investigation of Lipid Level Management to Understand its Impact in Atherosclerotic Events), a trial of torcetrapib (a cholesterol ester transfer protein inhibitor), that involved 15 067 participants at high cardiovascular risk. ILLUMINATE was terminated at a median of 550 days because of significant absolute increases of 1.2% in cardiovascular events and 0.4% in mortality with torcetrapib. The aims of our analysis were to determine whether a proteomic analysis might reveal biological mechanisms responsible for these harmful effects and whether harmful effects of torcetrapib could have been detected early in the ILLUMINATE trial with proteomics. METHODS: A nested case-control analysis of paired plasma samples at baseline and at 3 months was performed in 249 participants assigned to torcetrapib plus atorvastatin and 223 participants assigned to atorvastatin only. Within each treatment arm, cases with events were matched to controls 1:1. Main outcomes were a survey of 1129 proteins for discovery of biological pathways altered by torcetrapib and a 9-protein risk score validated to predict myocardial infarction, stroke, heart failure, or death. RESULTS: Plasma concentrations of 200 proteins changed significantly with torcetrapib. Their pathway analysis revealed unexpected and widespread changes in immune and inflammatory functions, as well as changes in endocrine systems, including in aldosterone function and glycemic control. At baseline, 9-protein risk scores were similar in the 2 treatment arms and higher in participants with subsequent events. At 3 months, the absolute 9-protein derived risk increased in the torcetrapib plus atorvastatin arm compared with the atorvastatin-only arm by 1.08% (P=0.0004). Thirty-seven proteins changed in the direction of increased risk of 49 proteins previously associated with cardiovascular and mortality risk. CONCLUSIONS: Heretofore unknown effects of torcetrapib were revealed in immune and inflammatory functions. A protein-based risk score predicted harm from torcetrapib within just 3 months. A protein-based risk assessment embedded within a large proteomic survey may prove to be useful in the evaluation of therapies to prevent harm to patients. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00134264.

Association of White Matter With Core Cognitive Deficits in Patients With Schizophrenia.

Importance: Efforts to remediate the multiple cognitive function impairments in schizophrenia should consider white matter as one of the underlying neural mechanisms. Objective: To determine whether altered structural brain connectivity is responsible for 2 of the core cognitive deficits in schizophrenia- reduced information processing speed and impaired working memory. Design, Setting, and Participants: This cross-sectional study design took place in outpatient clinics from August 1, 2004, to August 31, 2015. Participants included 166 patients with schizophrenia and 213 healthy control individuals. These participants were from 3 independent cohorts, each of which had its own healthy control group. No participant had current or past neurological conditions or major medical conditions. Patients were diagnosed with either schizophrenia or schizoaffective disorder as defined by the DSM-IV. Controls had no Axis I psychiatric disorder. Main Outcomes and Measures: Mediation analyses and structural equation modeling were used to analyze the associations among processing speed, working memory, and white matter microstructures. Whole-brain and regional diffusion tensor imaging fractional anisotropy were used to measure white matter microstructures. Results: Of the study participants, the 166 patients with schizophrenia had a mean (SD) age of 38.2 (13.3) years and the 213 healthy controls had a mean (SD) age of 39.2 (14.0) years. There were significantly more male patients than controls in each of the 3 cohorts (117 [70%] vs 91 [43%]), but there were no significant differences in sex composition among the 3 cohorts. Patients had significantly reduced processing speed (Cohen d = 1.24; P = 6.91 × 10-30) and working memory deficits (Cohen d = 0.83; P = 1.10 × 10-14) as well as a significant whole-brain fractional anisotropy deficit (Cohen d = 0.63; P = 2.20 × 10-9). In schizophrenia, working memory deficit was mostly accounted for by processing speed deficit, but this deficit remained when accounting for working memory (Cohen d = 0.89; P = 2.21 × 10-17). Mediation analyses showed a significant association pathway from fractional anisotropy to processing speed to working memory (P = 5.01 × 10-7). The strength of this brain-to-cognition pathway in different white matter tracts was strongly associated with the severity of schizophrenia-associated fractional anisotropy deficits in the corresponding white matter tracts as determined by a meta-analysis (r = 0.85-0.94; all P < .001). The same pattern was observed in patients and controls either jointly or independently. Conclusions and Relevance: Study findings suggest that (1) processing speed contributes to the association between white matter microstructure and working memory in schizophrenia and (2) white matter impairment in schizophrenia is regional tract-specific, particularly in tracts normally supporting processing speed performance.

GWAS of self-reported mosquito bite size, itch intensity and attractiveness to mosquitoes implicates immune-related predisposition loci.

Understanding the interaction between humans and mosquitoes is a critical area of study due to the phenomenal burdens on public health from mosquito-transmitted diseases. In this study, we conducted the first genome-wide association studies (GWAS) of self-reported mosquito bite reaction size (n = 84,724), itchiness caused by bites (n = 69,057), and perceived attractiveness to mosquitoes (n = 16,576). In total, 15 independent significant (P < 5×10-8) associations were identified. These loci were enriched for immunity-related genes that are involved in multiple cytokine signalling pathways. We also detected suggestive enrichment of these loci in enhancer regions that are active in stimulated T-cells, as well as within loci previously identified as controlling central memory T-cell levels. Egger regression analysis between the traits suggests that perception of itchiness and attractiveness to mosquitoes is driven, at least in part, by the genetic determinants of bite reaction size.Our findings illustrate the complex genetic and immunological landscapes underpinning human interactions with mosquitoes.

Utilization of Positive and Negative Controls to Examine Comorbid Associations in Observational Database Studies.

BACKGROUND: Opportunities to leverage observational data for precision medicine research are hampered by underlying sources of bias and paucity of methods to handle resulting uncertainty. We outline an approach to account for bias in identifying comorbid associations between 2 rare genetic disorders and type 2 diabetes (T2D) by applying a positive and negative control disease paradigm. RESEARCH DESIGN: Association between 10 common and 2 rare genetic disorders [Hereditary Fructose Intolerance (HFI) and α-1 antitrypsin deficiency] and T2D was compared with the association between T2D and 7 negative control diseases with no established relationship with T2D in 4 observational databases. Negative controls were used to estimate how much bias and variance existed in datasets when no effect should be observed. RESULTS: Unadjusted association for common and rare genetic disorders and T2D was positive and variable in magnitude and distribution in all 4 databases. However, association between negative controls and T2D was 200% greater than expected indicating the magnitude and confidence intervals for comorbid associations are sensitive to systematic bias. A meta-analysis using this method demonstrated a significant association between HFI and T2D but not for α-1 antitrypsin deficiency. CONCLUSIONS: For observational studies, when covariate data are limited or ambiguous, positive and negative controls provide a method to account for the broadest level of systematic bias, heterogeneity, and uncertainty. This provides greater confidence in assessing associations between diseases and comorbidities. Using this approach we were able to demonstrate an association between HFI and T2D. Leveraging real-world databases is a promising approach to identify and corroborate potential targets for precision medicine therapies.

Identification of 15 genetic loci associated with risk of major depression in individuals of European descent.

Despite strong evidence supporting the heritability of major depressive disorder (MDD), previous genome-wide studies were unable to identify risk loci among individuals of European descent. We used self-report data from 75,607 individuals reporting clinical diagnosis of depression and 231,747 individuals reporting no history of depression through 23andMe and carried out meta-analysis of these results with published MDD genome-wide association study results. We identified five independent variants from four regions associated with self-report of clinical diagnosis or treatment for depression. Loci with a P value <1.0 × 10(-5) in the meta-analysis were further analyzed in a replication data set (45,773 cases and 106,354 controls) from 23andMe. A total of 17 independent SNPs from 15 regions reached genome-wide significance after joint analysis over all three data sets. Some of these loci were also implicated in genome-wide association studies of related psychiatric traits. These studies provide evidence for large-scale consumer genomic data as a powerful and efficient complement to data collected from traditional means of ascertainment for neuropsychiatric disease genomics.

Genome-wide association analysis of pain severity in dysmenorrhea identifies association at chromosome 1p13.2, near the nerve growth factor locus.

Dysmenorrhea is a common chronic pelvic pain syndrome affecting women of childbearing potential. Family studies suggest that genetic background influences the severity of dysmenorrhea, but genetic predisposition and molecular mechanisms underlying dysmenorrhea are not understood. In this study, we conduct the first genome-wide association study to identify genetic factors associated with dysmenorrhea pain severity. A cohort of females of European descent (n = 11,891) aged 18 to 45 years rated their average dysmenorrhea pain severity. We used a linear regression model adjusting for age and body mass index, identifying one genome-wide significant (P < 5 × 10) association (rs7523086, P = 4.1 × 10, effect size 0.1 [95% confidence interval, 0.074-0.126]). This single nucleotide polymorphism is colocalising with NGF, encoding nerve growth factor. The presence of one risk allele corresponds to a predicted 0.1-point increase in pain intensity on a 4-point ordinal pain scale. The putative effects on NGF function and/or expression remain unknown. However, genetic variation colocalises with active epigenetic marks in fat and ovary tissues, and expression levels in aorta tissue of a noncoding RNA flanking NGF correlate. Participants reporting extreme dysmenorrhea pain were more likely to report being positive for endometriosis, polycystic ovarian syndrome, depression, and other psychiatric disorders. Our results indicate that dysmenorrhea pain severity is partly genetically determined. NGF already has an established role in chronic pain disorders, and our findings suggest that NGF may be an important mediator for gynaecological/pelvic pain in the viscera.