Researchers at Johns Hopkins Medicine say they have added to evidence that rapid resistance gene sequencing technology can accurately speed the identification of specific antibiotic-resistant bacteria strains that sicken and kill some patients. A report on a proof of concept study, published in the January 2019 issue of Antimicrobial Agents and Chemotherapy, suggests the technology has the potential to hasten the "personalized" choice of antibiotics critically ill patients need. "Delays in prescribing effective antibiotic therapy for drug-resistant infections increase the risk of poor outcomes," says Pranita Tamma, M.D., M.H.S., associate professor of pediatrics at Johns Hopkins Children's Center and one of the study authors. "The current standard process of identifying appropriate treatment options for highly drug-resistant bacteria can take up to 96 hours from the time the lab receives samples, but our findings suggest that with the use of a rapid whole genome sequencing method, we might reduce that time to about one day less," Tamma adds. Tamma notes that drug-resistant bacterial infections are rising dramatically, in great part due to the overuse of antibiotic drugs and in part to the ease with which bacteria can acquire new resistance genes from other bacterial strains or species, especially in hospital settings where different strains might intermingle. Efforts to develop new antibiotics are underway but are limited, Tamma says. The U.S. Centers for Disease Control and Prevention estimates that each year at least 2 million people develop an antibiotic-resistant infection, and at least 23,000 people die from them. Currently, typical laboratory tests to identify specific bacterial strains require 24 hours to grow the microbial culture sampled from patients, plus an additional 24 to 48 hours to determine which commonly used antibiotics would be effective against it. For bacteria resistant to multiple drugs, further tests may require an additional 24 to 48 hours more to determine what antibiotics of last resort can eradicate the infection. For years, scientists have been able to screen bacterial genomes for specific antibiotic-resistant genes, a laborious and protracted process until the recent advent of newer technologies able to sequence and analyze bacterial genomes within hours. These technologies also offer fast ways to identify exactly what type of resistant genes the pathogens contain. In their study designed to test the proof of concept of such methods, Tamma and Patricia J. Simner, Ph.D., D.(A.B.M.M.), the senior author of the study and an associate professor of pathology and medical microbiology at the John Hopkins University School of Medicine, used a nanopore DNA sequencer--a newer type of technology that gives results much faster than other DNA sequencing tools as it measures an electrical signal when a string of DNA moves through a tiny pore (i.e., nanopore). The electrical signal is monitored in real time, allowing for analysis of sequencing results within minutes. Other sequencers require a minimum of 24 hours before result analysis can take place. The researchers used the new sequencer to spot antibiotic resistance genes in several strains of Klebsiella pneumoniae, bacteria that may harmlessly dwell in the human intestinal tract, but can cause serious infections if they enter the bloodstream, the urinary tract or lungs. While all typical strains of K. pneumoniae can be treated with common antibiotics such as ceftriaxone, those with acquired antibiotic-resistant genes can turn dangerous and deadly. Those most at risk are hospitalized, have been exposed repeatedly to antibiotics, or are coming from parts of the world known for high antibiotic resistance rates. The team collected clinical samples that grew K. pneumoniae in culture from 40 adult patients hospitalized at The Johns Hopkins Hospital, extracted the bacterial DNA, and ran the DNA through the nanopore sequencer. The researchers used two different approaches to spotting the antibiotic resistance genes. A real-time analysis approach, which let researchers comb through the already sequenced genome parts while the rest of the DNA was still being read, revealed resistance genes within eight hours. An assembly-based approach took 14 hours, but proved to be more accurate and less prone to errors. The real-time approach correctly identified K. pneumoniae resistance genes and mutations in 77 percent of cases and the assembly-based one in 92 percent. "While we still need to wait 24 hours to get the culture to grow, we were able to cut time to identifying effective antibiotic therapy by at least 20 hours, compared to our current standard of care," says Simner. The team also believes that further automation of sample preparation could reduce the wait for optimal therapy. Tamma and Simner caution that their study does not mean the technology is ready for clinical use, or that it will prove to be less expensive or cost-effective. The study was limited by a small sample size and only one bacterial organism. Further studies are needed to test the new sequencer's value with other bacteria, and the methods applied still need refinements to make it easily useful in clinical settings. Tamma says their findings are a logical outgrowth of the commitment to precision, or personalized, medicine, which uses genetic specificity to guide treatment for patients with infections, cancer, heart disease and other disorders.详情>>

2019-01-22 00:00:00


最近发表在Nature Genetics上的最全面的全基因组关联研究(GWAS)结果发现了40种新的与结肠癌的风险增加有关的遗传变异。 由Fred Hutchinson癌症研究中心的一个研究小组领导的这项研究同时确定了第一种罕见的散发性结直肠癌保种。总之,这些发现对于创建个性化筛查策略和更好地为结直肠癌的药物开发提供了重要的信息。 这些研究结果也阐明了研究作者在药物开发中所谓的“错失机会”。作者认为,使用GWAS结果为癌症药物开发提供信息可以提高药物开发成功率,甚至可以为高风险人群提供化学预防药物。 “使用GWAS结果为抗癌药物的靶点发现提供了很大的潜力。对于2型糖尿病和心脏病等疾病,GWAS方法推动了新生物学和潜在药物靶点的发现,”该研究的作者,Jeroen Huyghe博士解释说:“迄今为止,对癌症治疗新目标的研究主要集中在癌症细胞的分子特征上。我们认为使用GWAS方法为结直肠癌的药物开发提供了一个巨大的机会。” Huyghe解释说:“大规模的全基因组测序研究已经发现了数百种尚未系统检查与疾病相关的遗传变异。我们的研究充分利用了Haplotype Reference Consortium面板的可用性,该面板是来自超过32,000个个体的序列数据的群体参考面板。通过将该策略与定制设计的基因分型芯片相结合,我们能够稳健地识别罕见的变异关联信号以及涉及低频变种的多个附加信号。“ 之前针对结直肠癌风险的GWAS仅考察了常见的遗传变异。相比之下,这项研究涉及超过2,000个人的全基因组测序,旨在检查罕见遗传变异对结直肠癌风险的贡献。 “通过这项研究,我们已经将已知数量的结直肠癌风险变种带到了近100个,”该研究的共同第一作者,Fred Hutch的遗传流行病学家Tabitha Harrison说。 “接下来,我们将研究人群扩大到包括来自不同种族背景的人。这将使我们更全面地了解整个人口的风险。” 资讯出处:Study discovers 40 new genetic variants associated with colorectal cancer risk 原始出处:Jeroen R. Huyghe et al, Discovery of common and rare genetic risk variants for colorectal cancer, Nature Genetics (2018). DOI: 10.1038/s41588-018-0286-6详情>>

2018-12-07 00:00:00


BACKGROUND Many patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added. METHODS We evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care. RESULTS A total of 1519 patients (53% female) were referred to the UDN, of whom 601 (40%) were accepted for evaluation. Of the accepted patients, 192 (32%) had previously undergone exome sequencing. Symptoms were neurologic in 40% of the applicants, musculoskeletal in 10%, immunologic in 7%, gastrointestinal in 7%, and rheumatologic in 6%. Of the 382 patients who had a complete evaluation, 132 received a diagnosis, yielding a rate of diagnosis of 35%. A total of 15 diagnoses (11%) were made by clinical review alone, and 98 (74%) were made by exome or genome sequencing. Of the diagnoses, 21% led to recommendations regarding changes in therapy, 37% led to changes in diagnostic testing, and 36% led to variant-specific genetic counseling. We defined 31 new syndromes. CONCLUSIONS The UDN established a diagnosis in 132 of the 382 patients who had a complete evaluation, yielding a rate of diagnosis of 35%. (Funded by the National Institutes of Health Common Fund.)展开>><<收起

N Engl J Med 2018; 379:2131-2139  0


Osteoarthritis has a highly negative impact on quality of life because of the associated pain and loss of joint function. Here we describe the largest meta-analysis so far of osteoarthritis of the hip and the knee in samples from Iceland and the UK Biobank (including 17,151 hip osteoarthritis patients, 23,877 knee osteoarthritis patients, and more than 562,000 controls). We found 23 independent associations at 22 loci in the additive meta-analyses, of which 16 of the loci were novel: 12 for hip and 4 for knee osteoarthritis. Two associations are between rare or low-frequency missense variants and hip osteoarthritis, affecting the genes SMO (rs143083812, frequency 0.11%, odds ratio (OR) = 2.8, P = 7.9 × 10−12, p.Arg173Cys) and IL11 (rs4252548, frequency 2.08%, OR = 1.30, P = 2.1 × 10−11, p.Arg112His). A common missense variant in the COL11A1 gene also associates with hip osteoarthritis (rs3753841, frequency 61%, P = 5.2 × 10–10, OR = 1.08, p.Pro1284Leu). In addition, using a recessive model, we confirm an association between hip osteoarthritis and a variant of CHADL1 (rs117018441, P = 1.8 × 10−25, OR = 5.9). Furthermore, we observe a complex relationship between height and risk of osteoarthritis.展开>><<收起

Nature Geneticsvolume 50, pages1681–1687 (2018)  0


Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care.展开>><<收起

Autoimmunity Reviews,Available online 5 November 2018  0


Small chemical changes in the DNA building blocks, which may be influenceable by lifestyle factors, can reduce the amount of IGFBP2. A DIfE / DZD research team has now reported in the journal Diabetes that these epigenetic changes increase the risk of type 2 diabetes. Moreover, people with high blood levels of the binding protein IGFBP2 are less likely to develop this metabolic disorder. The changes in the blood are already detectable a few years prior to the onset of the disease. According to the German Diabetes Health Report 2018, more than 5.7 million people in Germany suffer from type 2 diabetes. The affected individuals react inadequately to the hormone insulin, which leads to elevated blood glucose levels. This in turn can lead to strokes, heart attacks, retinal damage, kidney damage and nerve disorders. Since the metabolic disease develops gradually, initial damage has usually already occurred at the time of diagnosis. "In the future, our findings may help to identify risk potentials for type 2 diabetes even earlier and help to counteract the disease with preventive measures," said Professor Annette Schürmann, head of the Department of Experimental Diabetology at the German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE) and speaker of the German Center for Diabetes Research (DZD). Uncovering the molecular mechanisms In addition to insulin, insulin-like growth factor 1 (IGF-1) is also involved in the metabolism of sugar and fat. The effect of this growth factor is weakened by binding to the IGF-binding protein 2 (IGFBP2). If the liver does not release enough IGFBP2 into the blood, the balance of the glucose and lipid metabolism may be disrupted. The research team led by Schürmann and Professor Matthias Schulze, head of the Department of Molecular Epidemiology at DIfE, therefore investigated how the diminished effect of the IGFBP2 gene could influence the development of type 2 diabetes. Human studies show that people suffering from fatty liver produce and release less IGFBP2. Schürmann's team observed similar effects in earlier mouse experiments, which showed that IGFBP2 levels were already reduced prior to the liver disease. This is due to the transfer of methyl groups at certain sites of the IGFBP2 DNA sequence, which inhibited the gene in the liver. These so-called epigenetic changes are caused, among other things, by lifestyle factors. Such modifications of the DNA in the IGFBP2 gene were also previously detected in blood cells of overweight people with impaired glucose tolerance. Translational research from mouse to human studies The interdisciplinary research team led by Schürmann and Schulze used findings from the clinic and laboratory to evaluate blood samples and data from the EPIC Potsdam Study. "This study is a good example of how translational research works: A clinical finding is taken up, analyzed mechanistically in the laboratory and finally examined in a population-wide study," said Schürmann. Recent analyses by the researchers indicate that inhibition of the IGFBP2 gene promotes type 2 diabetes. In addition, the team of scientists observed that leaner study participants and study participants with lower liver fat levels had higher concentrations of the protective binding protein in the blood. Higher plasma concentrations of IGFBP2 were associated with a lower risk of developing type 2 diabetes in subsequent years. "Our study confirms the hypothesis that the IGF-1 signaling pathway also plays an important role in the development of type 2 diabetes in humans," added Dr. Clemens Wittenbecher, research associate in the Department of Molecular Epidemiology at DIfE and first author of the study. Story Source: Materials provided by Deutsches Zentrum fuer Diabetesforschung DZD. Note: Content may be edited for style and length. Journal Reference: Clemens Wittenbecher, Meriem Ouni, Olga Kuxhaus, Markus Jähnert, Pascal Gottmann, Andrea Teichmann, Karina Meidtner, Jennifer Kriebel, Harald Grallert, Tobias Pischon, Heiner Boeing, Matthias B. Schulze, Annette Schürmann. Insulin-Like Growth Factor Binding Protein 2 (IGFBP-2) and the Risk of Developing Type 2 Diabetes. Diabetes, 2018; db180620 DOI: 10.2337/db18-0620详情>>

2018-11-09 00:00:00


CD84 (SLAMF5) is a member of the SLAM family of cell-surface immunoreceptors. Broadly expressed on most immune cell subsets, CD84 functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function depending on the cell type and its stage of activation or differentiation. CD84-mediated signaling regulates diverse immunological processes, including T cell cytokine secretion, natural killer cell cytotoxicity, monocyte activation, autophagy, cognate T:B interactions, and B cell tolerance at the germinal center checkpoint. Recently, alterations in CD84 have been related to autoimmune and lymphoproliferative disorders. Specific allelic variations in CD84 are associated with autoimmune diseases such as systemic lupus erythematosus and rheumatoid arthritis. In chronic lymphocytic leukemia, CD84 mediates intrinsic and stroma-induced survival of malignant cells. In this review, we describe our current understanding of the structure and function of CD84 and its potential role as a therapeutic target and biomarker in inflammatory autoimmune disorders and cancer.展开>><<收起

Clinical Immunology,Available online 26 October 2018  0


Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can impair communication ability, socialization, and verbal and motor skills. It generally starts in early childhood and is diagnosed through behavior observation. This means of assessment can be imprecise, which is especially problematic when early identification is vital for developmental follow up. A strong need exists for objective and measurable clinical indicators, known as biomarkers. Now, a team of researchers at Kanazawa University in Japan have made an important step towards identifying a biomarker based on motor-related brain activity. Their work followed on from the key hypothesis that autism results from an excitatory and inhibitory imbalance in the brain, which is associated with repetitive brainwaves called gamma oscillations. A reduction in this type of brain activity has been seen during visual, auditory, and tactile stimulation in individuals with ASD. The researchers set out to further explore motor-induced gamma oscillations in children with ASD, and recently reported their findings in The Journal of Neuroscience. They formed two groups of children who were 5-7 years old. Those in the first group were conventionally diagnosed with ASD, while the second group was made up of children classed as developing typically. The children each performed a video-game-like task where they had to press a button with their right finger, while in a relaxed environment. Magnetoencephalography, which records magnetic activity from neurons, was used to monitor the children's brainwaves during the task. "We measured the button response time, motor-evoked magnetic fields, and motor-related gamma oscillations," study corresponding author Mitsuru Kikuchi says. "As found in other studies, the ASD children's response time was slightly slower and the amplitude in their magnetic fields was a bit decreased. The gamma oscillations were where we saw significant and interesting differences." There was a considerably lower peak frequency of the gamma oscillations in the ASD group. A lower peak frequency of motor-related gamma oscillations also signaled low concentration of the inhibitory neurotransmitter GABA, which has also been found associated with ASD. The findings additionally suggest delayed development of motor control in young children with ASD. Collectively the behavioral performance and brainwave findings offer promise for ASD diagnosis. "Early diagnosis of ASD is highly important so that we can actively manage the disorder as soon as possible," first author Kyung-min An says. "These findings may prove to be extremely useful in helping us understand the neurophysiological mechanism behind social and motor control development in children with ASD. Using magnetoencephalography in this way gives us a noninvasive and quantifiable biomarker, which is something we are in great need of." Story Source: Materials provided by Kanazawa University. Note: Content may be edited for style and length. Journal Reference: Kyung-min An, Takashi Ikeda, Yuko Yoshimura, Chiaki Hasegawa, Daisuke N. Saito, Hirokazu Kumazaki, Tetsu Hirosawa, Yoshio Minabe, Mitsuru Kikuchi. Altered Gamma Oscillations during Motor Control in Children with Autism Spectrum Disorder. The Journal of Neuroscience, 2018; 38 (36): 7878 DOI: 10.1523/JNEUROSCI.1229-18.2018详情>>

2018-10-29 00:00:00


Myeloproliferative neoplasms, such as polycythemia vera, essential thrombocythemia, and myelofibrosis, are chronic hematologic cancers with varied progression rates. The genomic characterization of patients with myeloproliferative neoplasms offers the potential for personalized diagnosis, risk stratification, and treatment.展开>><<收起

N Engl J Med 2018; 379:1416-1430  0
Gritstone登陆纳斯达克 打造个体化抗癌疗法

新闻Gritstone登陆纳斯达克 打造个体化抗癌疗法

本周,生物技术公司在纳斯达克市场掀起了一波IPO的热潮,共有5家公司先后上市。其中,今日上市的Gritstone Oncology作为打造个体化抗癌疗法的新锐,广受业界看好。 Gritstone成立于2015年,是一家专注开发肿瘤特异性免疫疗法的生物技术公司。我们知道,在不同患者的不同肿瘤上,会出现具有高度特异性的新抗原。如果能靶向这些新抗原开发免疫疗法,就有望对这些患者的癌症进行有效治疗。 然而在肿瘤细胞中,只有少量的DNA突变会转化为新抗原,这也给新抗原的鉴定带来了困难。目前,常规技术无法精准预测肿瘤特异的新抗原,因此也给免疫疗法的开发带来了困难。 为了解决这一难题,Gritstone开发了一款叫做EDGE的人工智能平台。利用海量的人类肿瘤数据,这一人工智能平台有望从中寻找到“鉴别肿瘤新抗原”的洞见,并将其应用于临床。目前,这一平台上已经获取了300多位患者的数据,多肽数量超过100万条。值得一提的是,这些患者罹患多种肿瘤类型,且祖源来自全球各地。这些多样化的数据,有助于提升其人工智能平台的能力。 目前,Gritstone已有两款免疫疗法进入了临床前阶段。第一款叫做GRANITE-001,针对患者特异新抗原所开发。具体来看,这款疗法会先从患者体内获取活检组织,对肿瘤进行测序。随后,EDGE人工智能平台会对肿瘤新抗原进行预测,从而推动个体化疗法的设计与使用。Gritstone相信,在罹患常见肿瘤的患者群体中,大约有70%-80%的患者有望从中受益。 其另一款疗法SLATE-001则有所不同。如果说GRANITE-001是一种疗法治疗一位患者,SLATE-001就是一种疗法治疗多名患者。这是由于不同的患者可能具有共同的突变(如常见的癌症驱动基因突变)。因此,针对特定新抗原的免疫疗法,有望使多名患者从中受益。 Gritstone的治疗理念得到了业界的普遍看好,并已和bluebird bio等公司达成合作协议。先前,这家公司的A轮与B轮融资总额约2亿美元,参与投资的包括Versant Ventures、The Column Group、Clarus Funds、Frazier Healthcare Partners、Redmile Group、Casdin Capital、Lilly Asia Ventures、Trinitas Capital、GV、Alexandria Venture Investments、以及Bay City Capital等知名风投机构。2017年,它也入选了“生物技术猛公司”(FierceBiotech's 2017 Fierce 15)榜单。评语指出,“这些公司有着杰出的科学平台,有着卓越的管理团队,有着光明的未来前景”。 我们期待随着成功登陆纳斯达克市场,Gritstone能进一步获得资本助力,推进个体化肿瘤免疫疗法的研发,为全球更多患者带来创新抗癌方案。详情>>

2018-09-30 00:00:00