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Introduction Amyloidosis is a rare disease and there are currently no FDA approved therapies for AL amyloidosis. Most of the therapeutic and disease data come from expert guidelines, consensus and retrospective review papers. There is a paucity of data specifically for relapsed/refractory AL amyloidosis (RRAL). We conducted this systematic review of clinical trials, retrospective and prospective cohort studies to evaluate patterns of relapse and therapeutic options for RRAL. Methods PubMed and Clinicaltrials.gov were searched for clinical trials, retrospective and prospective cohort studies on RRAL. Studies were selected according to PRISMA guidelines. Cross-trial comparison of included studies and meta-analysis could not be performed for a number of reasons but mainly due to a limited number of studies on one particular treatment regimen. Results From a total of 511 studies, 11 studies (n= 698 patients) met our inclusion criteria. Five were phase I/II clinical trials, five retrospective cohort studies, and one prospective cohort study. Most studies had less than 50 patients. The largest study, a retrospective cohort by Tandon et al. included 366 patients. Mean age was 61.2. Three studies reported 2 median prior lines of therapy (n= 22, 28, and 84 patients); two reported 3 median prior lines of therapy (n= 25 and 24) and 6 studies didn't specify this data. Prior treatment options included proteasome inhibitors (PI), most commonly bortezomib (n= 259), followed by melphalan (n=211), high dose melphalan and stem cell transplant (HDM/SCT [n= 207]) and IMiDs most commonly lenalidomide (n=154). Time to progression (TTP) from first-line treatment was reported in only 4 studies as 1 month, 5 months, 5 months and 34 months respectively. The study reporting a TTP of 34-months had 11 patients who received HDM/SCT as first line treatment. Three studies reported information about their criteria for initiation of subsequent treatment. Subsequent treatment was mostly a combination regimen with dexamethasone or an alkylating agent. The only agent evaluated as single agent was bortezomib in a phase I/II clinical trial by Reece et al. Therapeutic options for RRAL are PI (non-specific) based therapy (n= 145), lenalidomide (n= 105), bortezomib (n= 99), IMiD (non-specific) based therapy (n=83), melphalan based therapy (n= 33), carfilzomib (n=28), pomalidomide (n=27), ASCT (n= 25), daratumumab (n=25) and bendamustine (n=22). Efficacy: Hematologic responses were reported to be following: bortezomib + dexamethasone/melphalan (85%, n=17/20), daratumumab + dexamethasone (76%, n= 19/25), HDM/ASCT (73%, n= 8/11), single agent bortezomib (67%, n=23/34), carfilzomib ± dexamethasone (63%, n= 15/24), lenalidomide + dexamethasone (61%, n=51/84), bendamustine + dexamethasone (55%, 11/22) and pomalidomide + dexamethasone (50%, 12/24). Five of eleven studies reported organ responses which ranged from 18% to 23%. The studies which reported organ responses had evaluated the following agents: single agent bortezomib, carfilzomib ± dexamethasone, lenalidomide + dexamethasone, and bendamustine + dexamethasone. Best survival outcomes were seen with bortezomib with median overall survival (OS) 62 months. With bendamustine and dexamethasone (retrospective cohort study n=22) median OS was 31 months. With lenalidomide + dexamethasone (prospective cohort study n=24 ) median OS was 14 months. For the remaining studies, the median OS was either not reported or not reached at the time of presentation of data. Conclusion AL amyloidosis patients progressing after front line therapy show good responses with bortezomib (median overall survival of 62 months). Novel combinations using lenalidomide, pomalidomide, carfilzomib, daratumumab, and bendamustine show promising efficacy. Ongoing trials of daratumumab (AMYDARA trial) and ixazomib (TOURAMALINE-AL1) will bring further insight into therapeutic armamentarium for RRAL patients. After relapse, a salvage HDM/ASCT can be considered. Comparisons of regimen efficacy between studies are not practical because of multiple factors which include but are not limited to heterogenous nature of AL patients, small sample sizes, variable prior treatments, exposure to novel agents, observational study versus clinical trial and variable endpoints. Table Disclosures Anwer: Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; In-Cyte: Speakers Bureau.

Background The incidence of VTE in African-Americans (AAs) is similar to or higher than in Americans of European ancestry. However, the carrier frequencies of inherited thrombophilias common in whites (i.e., Factor V Leiden, Prothrombin G20210A) are very low in AAs, suggesting that other inherited thrombophilias may be associated with VTE in AAs. Objective To identify potentially novel non-hypothesis-driven single nucleotide polymorphisms (SNPs) associated with VTE in AAs. Methods We used the resources of the eMERGE Network to perform a GWAS of VTE in AAs. The eMERGE Network (funded by NHGRI) is comprised of nine sites each with DNA biobanks linked to electronic health records (EHRs). Approximately 39,206 unique DNA samples have been genotyped using either Affymetrix or Illumina genome-wide SNP arrays. Led by the Coordinating Center and eMERGE genomics workgroup, an imputation pipeline was developed for merging genomic data across the different SNP arrays used by the eMERGE sites, to maximize sample size and the power to detect associations. The imputation was performed using the 1000 Genomes Cosmopolitan reference panel which includes 1092 individuals and over 36 million SNPs. From our previously-identified cohort of Olmsted County, MN residents with incident or recurrent VTE, 1996-2005, we derived and validated an EHR-driven phenotype extraction algorithm that leveraged structured data based on ICD-9-CM codes and unstructured data from clinical notes via natural language processing to identify VTE cases and controls with 100% and 94% positive and negative predictive values, respectively. We tested for an association between each SNP and VTE among AAs using unconditional logistic regression, adjusting for age, sex and eMERGE site. Results Among 294 AA VTE cases and 3,661 AA controls (total n=3,955; females, n=2,512), the Factor V Leiden (F5 rs6025) was not analyzed due to a very low minor allele frequency (MAF=0.0036). The prothrombin G20210A (F2 rs1799963) and ABO blood type O (ABO rs8176719) SNPs were not genotyped in any of the arrays and could not be imputed. Among SNPs with an imputation score >0.8, the most significant SNPs associated with VTE were ITPR3 (inositol 1,4,5-triphosphate receptor type 3) rs2229637 (OR=1.65; p=3.61E-07; MAF=0.19) and CLEC7A (C-type lectin domain family 7, member A) rs59819090 (OR=2.16; p=1.06E-06; MAF=0.056). ITPR3 SNPs have been associated with coronary artery aneurysm in Kawasaki disease, type 1 diabetes mellitus and other autoimmune disorders. CLEC7A rs59819090 encodes for a serine82 to leucine nonsynonymous amino acid change in dectin-1. Dectin-1 is a transmembrane innate immune pattern recognition receptor on myeloid cells that upon binding it’s agonist, β-glucans, stimulates cytokine production and the respiratory burst, a prerequisite for formation of neutrophil extracelluar traps (NETs). NETs have been associated with VTE (van Montfoort, et al. Ateriosclero Thromb Vasc Biol 2013;33:147-51). Dectin-1 serine82 is not evolutionarily conserved and the serine82 to leucine amino acid change is predicted to be tolerated, with a moderate effect on protein function. Conclusions ITPR3 rs2229637 and CLAC7A rs59819090 may be associated with VTE in African-Americans. These observations require replication and functional studies toward understanding how they may lie on the causal pathway to VTE. Disclosures: No relevant conflicts of interest to declare.

AbstractBackgroundThe extent to which obesity and genetics determine postoperative complications is incompletely understood.MethodsWe performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome‐wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease‐9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity‐risk single‐nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components.ResultsIndividuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7–5.5, p < 3.1 × 10−20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2–2.3, p < 2.5 × 10−5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8–2.5], p = 1.4 × 10−6) and postoperative infection (OR 1.6 [95% CI 1.4–1.9], p = 3.1 × 10−6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures.ConclusionsClinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.

Abstract Pharmacogenomics (PGx) clinical decision support integrated into the electronic health record (EHR) has the potential to provide relevant knowledge to clinicians to enable individualized care. However, past experience implementing PGx clinical decision support into multiple EHR platforms has identified important clinical, procedural, and technical challenges. Commercial EHRs have been widely criticized for the lack of readiness to implement precision medicine. Herein, we share our experiences and lessons learned implementing new EHR functionality charting PGx phenotypes in a unique repository, genomic indicators, instead of using the problem or allergy list. The Gen-Ind has additional features including a brief description of the clinical impact, a hyperlink to the original laboratory report, and links to additional educational resources. The automatic generation of genomic indicators from interfaced PGx test results facilitates implementation and long-term maintenance of PGx data in the EHR and can be used as criteria for synchronous and asynchronous CDS.

Objective— It is unclear to what extent genetic susceptibility variants are shared between peripheral artery disease (PAD) and coronary heart disease (CHD), both manifestations of atherosclerotic vascular disease. We investigated whether common and low-frequency/rare variants in loci associated with CHD are also associated with PAD. Approach and Results— Targeted sequencing of 41 genomic regions associated with CHD in genome-wide association studies was performed in 1749 PAD cases (65±11 years, 61% men) and 1855 controls (60±11 years, 56% men) of European ancestry. PAD cases had a resting/postexercise ankle-brachial index ≤0.9, or history of lower extremity revascularization; controls had no history of PAD. We tested the association of common (defined as minor allele frequency ≥5%) variants with PAD assuming an additive genetic model with adjustment for age and sex. To identify low-frequency/rare variants (minor allele frequency <5%) associated with PAD, we conducted gene-level analyses using sequence kernel association test and permutation test. After Bonferroni correction, we found common variants in SH2B3, ABO , and ZEB2 to be associated with PAD ( P <4.5×10 −5 ). At the gene level, the strongest associations were for LPL and SH2B3 . Conclusions— Targeted sequencing of 41 genomic regions associated with CHD revealed several common variants/genes to be associated with PAD, highlighting the basis of shared genetic susceptibility between CHD and PAD.

Background: The Asp358Ala variant (rs2228145; A>C) in the IL (interleukin)-6 receptor ( IL6R ) gene has been implicated in the development of abdominal aortic aneurysms (AAAs), but its effect on AAA growth over time is not known. We aimed to investigate the clinical association between the IL6R -Asp358Ala variant and AAA growth and to assess the effect of blocking the IL-6 signaling pathway in mouse models of aortic aneurysm rupture or dissection. Methods: Using data from 2863 participants with AAA from 9 prospective cohorts, age- and sex-adjusted mixed-effects linear regression models were used to estimate the association between the IL6R -Asp358Ala variant and annual change in AAA diameter (mm/y). In a series of complementary randomized trials in mice, the effect of blocking the IL-6 signaling pathways was assessed on plasma biomarkers, systolic blood pressure, aneurysm diameter, and time to aortic rupture and death. Results: After adjusting for age and sex, baseline aneurysm size was 0.55 mm (95% CI, 0.13–0.98 mm) smaller per copy of the minor allele [C] of the Asp358Ala variant. Change in AAA growth was −0.06 mm per year (−0.18 to 0.06) per copy of the minor allele; a result that was not statistically significant. Although all available worldwide data were used, the genetic analyses were not powered for an effect size as small as that observed. In 2 mouse models of AAA, selective blockage of the IL-6 trans-signaling pathway, but not combined blockage of both, the classical and trans-signaling pathways, was associated with improved survival ( P <0.05). Conclusions: Our proof-of-principle data are compatible with the concept that IL-6 trans-signaling is relevant to AAA growth, encouraging larger-scale evaluation of this hypothesis.

Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a “virtual proteomic” approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08–1.58; P =0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66–0.94; P =0.008) per 1-SD increment in platelet-derived growth factor receptor-β. Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.

Purpose We assessed the decision-making of individuals pursuing genomic sequencing without a requirement for pretest genetic counselling. We sought to describe the extent to which individuals who decline genetic counselling reported decisional conflict or struggled to make a decision to pursue genomic testing. Methods We administered a 100-item survey to 3037 individuals who consented to the Return of Actionable Variants Empirical study, a genomic medicine implementation study supported by the National Institutes of Health (USA) eMERGE consortium. The primary outcomes of interest were self-reported decisional conflict about the decision to participate in the study and time required to reach a decision. Results We received 2895 completed surveys (response rate=95.3%), and of these respondents 97.8% completed the decisional conflict scale in its entirety. A majority of individuals (63%) had minimal or no decisional conflict about the pursuit of genomic sequencing and were able to reach a decision quickly (78%). Multivariable logistic regression analyses identified several characteristics associated with decisional conflict, including lower education, lower health literacy, lower self-efficacy in coping, lack of prior experience with genetic testing, not discussing study participation with a family member or friend, and being male. Conclusion As genomic sequencing is used more widely, genetic counselling resources may not be sufficient to meet demand. Our results challenge the notion that all individuals need genetic counselling in order to make an informed decision about genomic sequencing.