Posts Tagged ‘Quality of life’

Reporter and Curator: Dr. Sudipta Saha, Ph.D.


The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota–gut–brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential.


Out of all the many ways, the teeming ecosystem of microbes in a person’s gut and other tissues might affect health. But, its potential influences on the brain may be the most provocative for research. Several studies in mice had indicated that gut microbes can affect behavior, and small scale studies on human beings suggested this microbial repertoire is altered in depression. Studies by two large European groups have found that several species of gut bacteria are missing in people with depression. The researchers can’t say whether the absence is a cause or an effect of the illness, but they showed that many gut bacteria could make substances that affect the nerve cell function—and maybe the mood.


Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with DialisterCoprococcus spp. was also depleted in depression, even after correcting for the confounding effects of antidepressants. Two kinds of microbes, Coprococcus and Dialister, were missing from the microbiomes of the depressed subjects, but not from those with a high quality of life. The researchers also found the depressed people had an increase in bacteria implicated in Crohn disease, suggesting inflammation may be at fault.


Looking for something that could link microbes to mood, researchers compiled a list of 56 substances important for proper functioning of nervous system that gut microbes either produce or break down. They found, for example, that Coprococcus seems to have a pathway related to dopamine, a key brain signal involved in depression, although they have no evidence how this might protect against depression. The same microbe also makes an anti-inflammatory substance called butyrate, and increased inflammation is implicated in depression.


Still, it is very much unclear that how microbial compounds made in the gut might influence the brain. One possible channel is the vagus nerve, which links the gut and brain. Resolving the microbiome-brain connection might lead to novel therapies. Some physicians and companies are already exploring typical probiotics, oral bacterial supplements, for depression, although they don’t normally include the missing gut microbes identified in the new study.














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Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Reporter: Stephen J. Williams, PhD

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

What is working and what needs to change in pricing models?

Robert:  He sees so many players in the onStevencology space discovering new drugs and other drugs are going generic (that is what is working).  However are we spending too much on cancer care relative to other diseases (their initiative Going Beyond the Surface)

Steven:  the advent of biosimilars is good for the industry

Patrick:  large effort in oncology, maybe too much (750 trials on Keytruda) and he says pharma is spending on R&D (however clinical trials take large chunk of this money)

Robert: cancer has gotten a free ride but cost per year relative to benefit looks different than other diseases.  Are we overinvesting in cancer or is that a societal decision

Gary:  maybe as we become more specific with precision medicines high prices may be a result of our success in specifically targeting a mutation.  We need to understand the targeted drugs and outcomes.

Patrick: “Cancer is the last big frontier” but he says prices will come down in most cases.  He gives the example of Hep C treatment… the previous only therapeutic option was a very toxic yearlong treatment but the newer drugs may be more cost effective and safer

Steven: Our blockbuster drugs could diffuse the expense but now with precision we can’t diffuse the expense over a large number of patients

President’s Cancer Panel Recommendation

Six recommendations

  1. promoting value based pricing
  2. enabling communications of cost
  3. financial toxicity
  4. stimulate competition biosimilars
  5. value based care
  6. invest in biomedical research

Patrick: the government pricing regime is hurting.  Alot of practical barriers but Merck has over 200 studies on cost basis

Robert:  many concerns/impetus started in Europe on pricing as they are a set price model (EU won’t pay more than x for a drug). US is moving more to outcomes pricing. For every one health outcome study three studies did not show a benefit.  With cancer it is tricky to establish specific health outcomes.  Also Medicare gets best price status so needs to be a safe harbor for payers and biggest constraint is regulatory issues.

Steven: They all want value based pricing but we don’t have that yet and there is a challenge to understand the nuances of new therapies.  Hard to align all the stakeholders together so until some legislation starts to change the reimbursement-clinic-patient-pharma obstacles.  Possibly the big data efforts discussed here may help align each stakeholders goals.

Gary: What is the data necessary to understand what is happening to patients and until we have that information it still will be complicated to determine where investors in health care stand at in this discussion

Robert: on an ICER methods advisory board: 1) great concern of costs how do we determine fair value of drug 2) ICER is only game in town, other orgs only give recommendations 3) ICER evaluates long term value (cost per quality year of life), budget impact (will people go bankrupt)

4) ICER getting traction in the public eye and advocates 5) the problem is ICER not ready for prime time as evidence keeps changing or are they keeping the societal factors in mind and they don’t have total transparancy in their methodology

Steven: We need more transparency into all the costs associated with the drug and therapy and value-based outcome.  Right now price is more of a black box.

Moderator: pointed to a recent study which showed that outpatient costs are going down while hospital based care cost is going rapidly up (cost of site of care) so we need to figure out how to get people into lower cost setting

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

Seqster: Seqster is a secure platform that helps you and your family manage medical records, DNA, fitness, and nutrition data—all in one place. Founder has a genomic sequencing background but realized sequence  information needs to be linked with medical records.

HealthShareExchange.org :

HealthShare Exchange envisions a trusted community of healthcare stakeholders collaborating to deliver better care to consumers in the greater Philadelphia region. HealthShare Exchange will provide secure access to health information to enable preventive and cost-effective care; improve quality of patient care; and facilitate care transitions. They have partnered with multiple players in healthcare field and have data on over 7 million patients.


Data can be overwhelming, but it doesn’t have to be this way. To drive healthcare efficiency, we designed a modular suite of products for a smooth transition into a data-driven world within 4 weeks. Why does it take so much money to move data around and so slowly?

What is interoperatibility?

Ardy: We knew in genomics field how to build algorithms to analyze big data but how do we expand this from a consumer standpoint and see and share your data.

Lauren: how can we use the data between patients, doctors, researchers?  On the research side genomics represent only 2% of data.  Silos are one issue but figuring out the standards for data (collection, curation, analysis) is not set. Still need to improve semantic interoperability. For example Flatiron had good annotated data on male metastatic breast cancer.

David: Technical interopatabliltiy (platform), semantic interopatability (meaning or word usage), format (syntactic) interopatibility (data structure).  There is technical interoperatiblity between health system but some semantic but formats are all different (pharmacies use different systems and write different prescriptions using different suppliers).  In any value based contract this problem is a big issue now (we are going to pay you based on the quality of your performance then there is big need to coordinate across platforms).  We can solve it by bringing data in real time in one place and use mapping to integrate the format (need quality control) then need to make the data democratized among players.

Rakesh:  Patients data should follow the patient. Of Philadelphia’s 12 health systems we had a challenge to make data interoperatable among them so tdhey said to providers don’t use portals and made sure hospitals were sending standardized data. Health care data is complex.

David: 80% of clinical data is noise. For example most eMedical Records are text. Another problem is defining a patient identifier which US does not believe in.





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Curated by: Dr. V. S. Karra, Ph.D.

Pain is a major symptom in many medical conditions, and can significantly interfere with a person’s quality of life and general functioning.[1]. It is often caused by intense or damaging stimuli, such as stubbing a toe, burning a finger, putting alcohol on a cut, and bumping the “funny bone.”

English: Illustration of the pain pathway in R...

Pain is an absolutely unpleasant one. Knowing the time of onset, location, intensity, pattern of occurrence (continuous, intermittent, etc.), exacerbating and relieving factors, and quality (burning, sharp, etc.) of the pain will help the examining physician to accurately diagnose the problem. For example, chest pain described as extreme heaviness may indicate myocardial infarction, while chest pain described as tearing may indicate aortic dissection.

Acute pain is usually managed with medications such as analgesics and anesthetics. Management of chronic pain, however, is much more difficult and may require an interdisciplinary approach for treating or easing the suffering and improving the quality of life. Psychological factors such as social support, hypnotic suggestion, excitement, or distraction can significantly modulate pain’s intensity or unpleasantness.

The International Association for the Study of Pain (IASP) states that “Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage”.[2].

Following is the IASP’s classification of pain:

(1) region of the body involved (e.g., abdomen, lower limbs),

(2) system whose dysfunction may be causing the pain (e.g., nervous, gastrointestinal),

(3) duration and pattern of occurrence,

(4) intensity and time since onset, and

(5) etiology

This system has been criticized by Clifford J. Woolf and others as inadequate for guiding research and treatment.

According to Woolf, there are three classes of pain :

Nociceptive pain: is caused by stimulation of peripheral nerve fibers and the stimulants could be Thermal, Mechanical and/ or Chemical. For example “heat or cold” (thermal), “crushing, tearing, etc.” (mechanical) and “iodine in a cut, chili powder in the eyes” (chemical).

Inflammatory pain: is associated with tissue damage and the infiltration of immune cells, and

Pathological pain: is a disease state caused by damage to the nervous system (neuropathic pain) or by its abnormal function (dysfunctional pain, like in fibromyalgia, irritable bowel syndrome, tension type headache, etc.).[3]

Pain will have a very detrimental effect on the quality of life. Experimental subjects challenged by acute pain and patients in chronic pain experience impairments in attention control, working memory, mental flexibility, problem solving, and information processing speed.[4]. Acute and chronic pain are also associated with increased depression, anxiety, fear, and anger.[5].

Patients who often have a background level of pain controlled by medications and whos pain periodically “breaks through” the medication is called breathrough pain and it is common in cancer patients . The characteristics of breakthrough cancer pain vary from person to person and according to the cause.

Harold Merskey said: “If I have matters right, the consequences of pain will include direct physical distress, unemployment, financial difficulties, marital disharmony, and difficulties in concentration and attention…”

Pain perception (point at which the stimulus begins to hurt) and tolerance thresholds (point at which the individual can’t tolerate the pain any more and when the subject acts to stop the pain) are not the same. The perception of pain is influenced by a multitude of variables including gender, age, mood, ethnicity and genetic factors [6],

Thus it is important to:

  • understand mechanisms of susceptibility to (chronic) pain,
  • Explore the genetics, emphasizing the conservation of pain-related genes, their functions and their advantages if any
  • Understand the role of gene polymorphisms in normal and pathological modulation of pain in models, humans, and as future drug targets
  • Explore the latest findings from human genome-wide investigation of genomic variability and gene expression on pain
  • Understand genetic and genomic techniques to study genetic contribution to (human) pain.
  • Study the progress of cutting-edge clinical trials and translate research findings to clinical practice
  • develop preventative approaches and novel treatment strategies

Advances in molecular, statistical and behavioral methodologies have suddenly allowed genetic investigations of complex biological phenomena, including pain. Genetic studies of pain are already showing their power to identify new molecular targets for drug development and create new animal models of pain pathology, says Jeffrey S. Mogil, PhD who is currently the E.P. Taylor Professor of Pain Studies and the Canada Research Chair in the Genetics of Pain and wrote a book on “The Genetics of Pain“.

Pain genetics can explain why we’re not all alike with respect to pain – why some people hurt more, and receive less benefit from existing analgesics. The knowledge gained holds the promise of allowing truly individualized pain therapy, says Mogil.

Algorithms for accessing and integrating available public data to examine disease-relevant mechanisms are of growing interest as publically available data sets grow at an ever-increasing rate. A meta-analysis of publicly available microarray data from rodents exposed to neuropathic or inflammatory pain was able to efficiently prioritize pain-related genes [7].

A similar approach using human gene expression data could be highly beneficial in generating data-driven hypotheses for pain genetics.

Most recent article, published on June 7, 2012, in open access journal  PLoS Computational Biology, on “Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases” presented a novel integrative approach that combines publicly available molecular data and automatically extracted knowledge regarding pain contained in the literature to assist the discovery of novel pain genes. This study was approved by the Institutional Review Boards of Stanford University and SRI International.

In this meta-analysis, they took advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories and

  • Ranked thousands of diseases according to the Figure shown below.

  • Obtained gene expression profiles of 121 of these human diseases from public sources.
  • Selected ‘genes with expression variation significantly correlated with DSPI across diseases’ as candidate pain genes.
  • Genotyped selected candidate pain genes in an independent human cohort, and finally
  • Evaluated for significant association between variants and measures of pain sensitivity.

In this study, the genes were chosen based on their high correlation with the DSPI and plausible biology as assessed by the available literature and human expression profile across tissue using The Scripps Research Institute BioGPS database [8].

The selected genes were:

  • ABLIM3 (actin binding LIM protein family, member 3),
  • PDE2A (phosphodiesterase 2A, cGMP-stimulated),
  • CREB1 (cAMP responsive element binding protein 1),
  • NAALAD2 (N-acetylated alpha-linked acidic dipeptidase 2), and
  • NCALD (neurocalcin delta).

These genes were selected from the candidate list and were prospectively tested for variants that may be associated with differential pain sensitivity in an independent human cohort.

ABLIM3 was selected as the top candidate as it showed the highest correlation with the DSPI. ABLIM3 is a newly characterized protein-coding gene. ABLIM3 is expressed in various tissues, most prominently in muscle and neuronal tissue [9], [10].

Polymorphisms in ABLIM3 (rs4512126) and NCALD (rs12548828, rs7826700, and rs1075791) showed significant association with the cold pressor pain threshold

The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10)  for the sensitivity to cold pressor pain in males, but not in females – a sex-specific association.”

Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively).

Authors said that, “This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates.”

Authors have demonstrated the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This approach was validated through a targeted genetic association study in an independent human cohort, where variants of selected pain gene candidates were evaluated for associations with experimental pain sensitivity measures in humans.

Authors hope that “the outlined approach can complement existing research efforts by assisting the formulation of data-driven hypotheses, and may serve as a template to discover genetic components of other clinically important phenotypes.

Further Reading:

Pain Gene Database (PGD)[11]

MeSH: Medical Subject Heading is a comprehensive vocabulary thesaurus organized in a hierarchical structure allowing the indexing of publications with various levels of specificity.

The 20 diseases with the highest disease-pain ratio from the DSPI are listed out of a total of 2962 diseases are


Curated by: Dr. V. S. Karra, Ph.D.

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