Obesity Surgery: VA Outcome Study

Weight loss (bariatric) surgery is likely to become increasingly important to address the obesity epidemic in the U.S. and other nations.

There are several types of surgical techniques used for bariatric surgery.

One of the most invasive is the Rous-en-Y gastric bypass (RYG) operation. This operation involves bisection of the small intestine and reattachment of the upper section to a position lower down the small intestine. This provides for a shorter distance for food to be absorbed.

Less invasive techniques using a sleeve (sleeve gastrectomy SB) or adjustable gastric banding (AGB) around the stomach are also common surgical approaches.

A recent large Veterans Administration bariatric surgery outcome study helps in understanding the long-term relative weight loss efficacy of three types of operations. This study compared outcomes between three types of operations (RYGB

The chart I have put together from data abstracted from the manuscript is above. The summary findings include the following key items:

• All three surgical interventions were superior to no operation controls
• All three surgical interventions maintained significant weight loss at five years
• Rous-en-Y (RYB) was superior to SG and AGB at one and five years.
• The study supports about a 30%/20%/10% five year weight reduction for the RYG/SG/AGB operations

I have included a schematic of the RYG procedure from the Wikipedia Commons file here. This schematic has the tranverse colon cut away to show the small intestine re-attachment site.

There are some significant limitations of this study. Surgical procedures were not randomized and study subjects differed on some clinical and demographic features at baseline. VA subjects are predominantly male and results may not be generalizable to women.

There was not a detailed report of risks and complications for each procedure.

Nevertheless, this is an important study that supports use of bariatric surgery as an option in the treatment of high-risk severely obese U.S. veterans.

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Chart above is an original chart produced by me from data abstracted from the manuscript.

Readers can access the manuscript abstract by clicking on the PMID link below

The Wikipedia Commons file was originally uploaded by Topnife at English Wikipedia - Transferred from en.wikipedia to Commons., Attribution, https://commons.wikimedia.org/w/index.php?curid=3153491

Maciejewski ML, Arterburn DE, Van Scoyoc L, Smith VA, Yancy WS Jr, Weidenbacher HJ, Livingston EH, & Olsen MK (2016). Bariatric Surgery and Long-term Durability of Weight Loss. JAMA surgery PMID: 27579793

Genetics of Depression: Secondary Markers

In my previous post, I highlighted a recent study of genetics and major depression from the 23andMe database.

I have had a chance to review this manuscript in more detail. One of the findings of interest involved secondary marker or secondary phenotypes.

Fifteen genetic loci were identified in this 23andMe sample using a discovery and replication data set.

Secondary phenotypes with the highest correlation with the 17 SNPs identified in the study included (effect) :

• Taking a selective serotonin reuptake inhibitor (SSRI) (.448)
• Any medication for mental health reasons (.421)
• Self-reported anxiety (.323)
• Self-reported panic attacks (.319)
• Early age of onset depression (.283)
• Insomnia (.272)
• Prescription pain medication (.236)
• Obesity with BMI>30 (.216)
• Overweight BMI >27 (.212)

The research team was able to identify one SNP (rs12552 in the OLFM4 or olfactomedin 4 region) that correlated with reporting of panic attacks, use of medication for mental health, pain, insomnia problems, BMI >27 and early age of onset of depression.

This study supports use of self-report of depression diagnosis or treatment of depression for genetic studies. Such approaches may open large data sets for understanding the genetics of neuroscience medicine disorders like depression.

Click on the PMID link to access the study abstract.

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Photo of fisherman at sunset is from my files.

Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, Tung JY, Hinds DA, Perlis RH, & Winslow AR (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature genetics PMID: 27479909

"The Biggest Loser": Long-term Effects

Yesterday I posted a link to a New York Times article that posted a summary outcome in fourteen participants in TV's "The Biggest Loser" show.

The study found a trend towards post-show weight gain for 13/14 of the participants.

Four participants actually gained so much weight that after six years they weighed more than before participating in the show.

A key finding from the study was this weight gain could be explained by a metabolic response resulting in up to 800 calories less burned daily after weight loss.

I have previously posted notes from a lecture I attended by Dr. Kevin Hall who is mentioned in the NYT piece.

For me, the take home message is that long-term weight loss maintenance is extremely difficult. A better strategy might be to aim for consuming a healthy diet and achieving daily recommended exercise levels.

A link to the NYT article is here:

Notes on Dr. Hall's lecture at the Laureate Institute for Brain Research is here:

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Graphic is an original screen shot from my Twitter feed.

Fothergill, E., Guo, J., Howard, L., Kerns, J., Knuth, N., Brychta, R., Chen, K., Skarulis, M., Walter, M., Walter, P., & Hall, K. (2016). Persistent metabolic adaptation 6 years after “The Biggest Loser” competition Obesity DOI: 10.1002/oby.21538

Dogs, Exercise and Diabetes via @NPR

Recommended Viewing:

Which States Have Highest Obesity Rates?

In a previous post I examined the geographic variability of physical activity in the U.S. West coast states tended to have the highest rates of physical activity.

The CDC map of rates of obesity (BMI of 30 or greater) shows a similar pattern of distribution. States with higher physical activity rates show lower rates of obesity.

The five states with the highest prevalence of obesity in the general population are:

1. Mississippi 35.1%
1. West Virginia 35.1%
3. Arkansas 34.6%
4. Tennessee 33.7%
5. Kentucky 33.2%

States with the lowest rates of obesity.

1. Colorado 21.3%
2. Hawaii 21.8%
3 District of Columbia 22.9%
4. Massachusetts 23.6%
5. California 24.1%
5. Utah 24.1%

Data and chart are from the CDC website.

For more information see:

Nutrition, Physical Activity and Obesity Data, Trends and Maps web site. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition, Physical Activity and Obesity, Atlanta, GA, 2015. Available athttp://www.cdc.gov/nccdphp/DNPAO/index.html.

Who Meets Physical Activity Goals?

The Center for Disease Control (CDC) in the U.S. recommends adults participate in a minimum of 150 minutes of moderate exercise or 75 minutes of intense exercise weekly.

There is significant geographic variability in percentage of adults meeting recommended levels of physical activity.

The chart in this post is generated from the CDC website and plots individual states and the rates for adults achieving the physical activity goal. Darker blue colors indicate greater physical activity. 

The 12 states with over 55% of adult meeting the physical activity goals include:
1. Washington
2. Oregon
3. California
4. Montana
5. Utah
6. Colorado
7. New Mexico
8. Alaska
9. Vermont
10. New Hampshire
11. Hawaii
12. District of Columbia

The 6 states with less than 45% of adults meeting the physical activity goals include:
1. Texas
2. Oklahoma (my state)
3. Arkansas
4. Mississippi
5. Tennessee
6. Indiana

The reasons for this significant variation between states is unclear. There appears to be some inverse correlation between state physical activity level rates and obesity rates.

More information about these patterns can be found in the citation below:

Nutrition, Physical Activity and Obesity Data, Trends and Maps web site. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition, Physical Activity and Obesity, Atlanta, GA, 2015. Available at http://www.cdc.gov/nccdphp/DNPAO/index.html

Obesity, Inflammation and Cognitive Decline

The rate of cognitive decline with aging is quite variable. 

Identifying important components of this process is needed for developing interventions to reduce the burden of Alzheimer's and other dementias.

Excess inflammation has been linked to obesity as well as aging-related cognitive decline.

Archana Singh-Manoux and colleagues recently published a study of the association between blood markers of inflammation and cognitive decline.

This study used data from the U.K. Whitehall II cohort, a group of men and women between the ages of 35-55 at intake.

This cohort has now been studied over a 20 year follow up with interval assessments about every five years.

Two blood markers of inflammation were studied in this cohort: interleukin-6 (IL-6) and C-reactive protein (CRP).

The study found strong associations between both blood markers of inflammation and rates of obesity (BMI >30) in the chart shown here.

Cognitive decline was measured by decrease scores on the Minimental Status Exam and other neuropsychological tests during the follow up period.

The primary finding from the study was that elevated IL-6 levels but not CRP levels at baseline were associated with accelerated cognitive decline.

Subjects in the highest IL-6 blood level group showed an 85% increased rate in losing 3 or more points on the Minimental Status Exam.

The authors note there study does not prove causality between IL-6 levels and cognitive decline but that:

"Inflammation is likely to play a role because of its impact on cerebral small-vessel disease, which could lead to changes that affect cognitive ageing."

It is also possible, that some of the link between obesity and cognitive decline may be attributable to increased obesity-related inflammation.

The practical clinical potential would be to attempt to identify and reduce inflammation in those most at risk. Anti-inflammatory drugs such as naproxen (Aleve in U.S.) have not been generally effect in trials to reduce rates of Alzheimer's disease.

However, these trials have typically not targeted groups with the highest blood markers of inflammation.

Readers with more interest in this topic can access the free full-text manuscript by clicking on the link in the citation below.

Photo of great blue heron from South Padre Island, TX is from the author's files.

Chart is an original figure from data abstracted from the manuscript.

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Singh-Manoux A, Dugravot A, Brunner E, Kumari M, Shipley M, Elbaz A, & Kivimaki M (2014). Interleukin-6 and C-reactive protein as predictors of cognitive decline in late midlife. Neurology, 83 (6), 486-93 PMID: 24991031

Topiramate Augmentation in Major Depression

Molecular Model of the Drug Topiramate

Currently available antidepressants provide significant relief from major depression in many patients.  However, a significant number of patients receive little or limited relief following an initial trial of a standard first-line drug from the selective serotonin re-uptake inhibitor class of agents.


A common clinical strategy after initial drug non-response and non-remission is to consider pharmacological augmentation.  Augmentation options for clinicians include lithium carbonate, triiodthyronine (thyroid hormone), a second antidepressant, an atypical antipsychotic or adding psychotherapy if it is not already being provided.


Despite the number and range of augmentation options, additional options need to be explored given the persistence of depressive symptoms in many individuals.  A small study from Iran suggests one alternative to consider may be the drug topiramate.


Topiramate is a drug approved by the FDA for the treatment of epilepsy and migraine headaches  in the United States.  It is not approved for the treatment of any primary psychiatric disorder.  The exact mechanism of action for topiramate is unknown although it is known to have effects on the sodium channel, gamma-amino butyric acid (GABA) receptors, glutamate receptors and act as a carbonic anhydrase inhibitor.


Mowla and Kardeh have published a small study of 42 subjects randomized to topiramate or placebo.  The key elements of the study include:

• Subjects: Adults with DSM-IV major depressive disorder who had failed to respond to eight weeks of treatment with an SSRI drug (fluoxetine, citalopram or sertraline)
• Drug: Topiramate 25 mg per day increased by 25 mg per week throughout the trial (mean dosage 175 mg/day) or placebo
• Clinical trial design: Double-blind, randomized controlled trial with primary outcome measure the Hamilton Depression Rating scale (HAM-D) administered by a psychologist not involved in treatment

Fifty three subjects started the study with 11 dropouts (six in the topiramate group and five in the placebo group).  HAM-D scores statistically decreased more in the topiramate group (21.6 at baseline to 14.7 at 8 weeks) than in the placebo group (21.9 at baseline to 20.8 at 8 weeks).


Since a score of seven or more is considered remission in MDD, the mean score of 14.7 in the topiramate groups suggests significant residual symptomatology.  The authors do not provide the number of subjects meeting remission criteria in the topiramate and placebo groups by 8 weeks.


Nevertheless, topiramate has some potential significant advantages in the treatment-resistant major depression population.  First, it is a generic drug and would have some cost advantages in comparison to some of the other options.  Second, topiramate it typically weight neutral or produces a slight weight reduction.  Most antidepressants increase weight over time so this might be an important advantage.  Third, topiramate might hold an advantage in treatment of MDD populations with migraine or epilepsy--disorders with an indication for the drug.


This study is too small to change clinical practice patterns or guidelines.  Additional larger replication studies need to be considered.  

Molecular model of the drug topiramate from Wikipedia Creative Commons file released to the public domain.  Author of the model is: Fvansconsellos

Mowla A, & Kardeh E (2011). Topiramate augmentation in patients with resistant major depressive disorder: a double-blind placebo-controlled clinical trial. Progress in neuro-psychopharmacology & biological psychiatry, 35 (4), 970-3 PMID: 21291943

Obesity, Inflammation and Depression

Obesity commonly occurs in the context of markers of inflammation.  Additionally, there is increasing evidence of a link between depression and systemic markers of inflammation such as the cytokine marker interleukin-6 (IL-6).  How these three conditions might tie together is an important research question.

Capuron and colleagues from France recently published a manuscript that looked at a specific group with obesity--women who were severely or morbidly obese and were waiting for gastric obesity surgery. The study published in Psychological Medicine prospectively followed these women after gastric surgery and monitored serum markers of inflammation as well as psychological function.

The research team focused on neuroticism as a key measure of personality as potentially related to systemic inflammation and potentially improved following bypass surgery.  Using the NEO-PI-R inventory, neuroticism can be broken down into components of anxiety, hostility, depression, self-consciousness, impulsiveness and vulnerability.

Baseline obesity levels as measured by the body mass index (BMI) in the sample correlated with baseline inflammatory markers IL-6 and C-reactive proteins.  These inflammatory markers also correlated with anxiety and depression---the higher the level of these inflammatory markers, the higher the level of self-reported anxiety and depression.

The women in the study lost approximately 30% of their body weight in the year following bypass surgery (mean weight reduction 47 kg = 103 pounds) with significant reductions in the blood markers of inflammation.  NEO-PI-R markers of depression and anxiety also dropped significantly over the one year following gastric surgery.  Reduction in C-reactive protein levels correlated with the reductions in the levels of anxiety.

This type of study is a association and not a causation study.  Nevertheless, it suggests that severe obesity is a disorder associated with systemic inflammation.  This systemic inflammation may contribute to adverse affective symptoms such as depression and anxiety.  Reducing inflammation through reducing obesity (via methods such as bypass surgery) may have additional central nervous system benefits.  Psychological benefits of weight loss may also be at work through improved body and self-esteem.

The role of inflammation in a variety of disorders including heart disease and diabetes is becoming better understood.  This study suggests inflammatory mechanisms should be explored for anxiety and depressive disorders, particularly in populations with obesity and diabetes mellitus.  

Photo of Juno Beach sunrise through filter from the author's collection.

Capuron, L., Poitou, C., Machaux-Tholliez, D., Frochot, V., Bouillot, J., Basdevant, A., Layé, S., & Clément, K. (2010). Relationship between adiposity, emotional status and eating behaviour in obese women: role of inflammation Psychological Medicine, 41 (07), 1517-1528 DOI: 10.1017/S0033291710001984

Brain Response to Eating the Same Foods

One potential contributing factor to increasing rates of overweight and obesity is the availability and affordability of a wide range of food choices.  A variety of inexpensive fast food options provides consumers the ability to rotate restaurant selection and reduce the risk of monotony in food selection.


Animal studies demonstrate that animals provided the same types of food (or other types of rewards) tend to reduce the level of consumption.  This is a behavioral trait known as habituation.  Habituation represents the tendency to  reduce total caloric intake when eating the same foods and to increase caloric intake when presented novel food choices.


Food habituation in humans has received limited attention.  For example, it is unclear whether being presented the same food weekly results in habituation.   Additionally, it is unclear whether food habituation occurs in similar manner for those who normal weight compared to those who are overweight.

Understanding habituation in humans may provide an insight in how to use food presentation to reduce or increase caloric intake.

Epstein and colleagues recently published a simple but important study of food habituation in a group of normal weight and obese women in the American Journal of Clinical Nutrition.  The study design was relatively straightforward.  Each group of normal weight and obese women were divided in two and were studied in one of two longitudinal experiments:

• Daily group: Every day for 5 days over the lunch hour, women in this group were brought into the lab and provided an opportunity to earn a 125 calorie portion of macaroni and cheese.  Subjects could decide to persist for up to 14 portions over 28 minutes or if they elected they could leave the food station and attend to a station where a newspaper and Sudoko puzzles were available.
• Weekly group:  The weekly group performed an identical experiment except they attended once a week for five weeks

So the experiment essentially tried to determine how enticing a single food (macaroni and cheese) was when offered on a daily compared to a weekly basis.  The key results of the study were:

• Women presented daily macaroni and cheese reduced caloric consumption of mac and cheese by about 100 calories from day 1 to day 5 and reduced their rating of how much they liked mac and cheese over the course of the study
• Women presented weekly macaroni and cheese increased caloric consumption of mac and cheese by about 100 calories from week 1 to week 5
• The pattern in obese women looked identical to that found in women of normal weight

So, if you are interested in losing weight, eating the same thing daily may be a way to use the habituation process to aid calorie restriction.  However, if you eat the same thing every day you do need to worry about the nutritional profile of what you are eating.  Appetite and drive for specific foods may be a biological mechanism to assure intake of all necessary nutritional components.

This study confirms that humans, like animals develop food habituation when presented the same food daily.  Habituation does not appear to be influenced by being obese.  It is unclear why this biological process develops.  Perhaps it is a mechanism to encourage exploration for novel foods that may add nutritional diversity.

Photo of sunrise at Juno Beach, Florida from author's collection.

Epstein LH, Carr KA, Cavanaugh MD, Paluch RA, & Bouton ME (2011). Long-term habituation to food in obese and nonobese women. The American journal of clinical nutrition, 94 (2), 371-6 PMID: 21593492

Hoarding Linked to BDNF Gene in OCD

In two previous posts on hoarding, I have reviewed some the pathway and profile of animal hoarding as well as the common mental health problems found with hoarding.

Today I will review a study that provides some insight into potential genetic contributions to hoarding behavior.  Of interest, this genetic link also appears to carry some increased risk for obesity.

Timpano from the University of Miama along with colleagues at Florida State University and the National Institute of Mental Health Intramural programs have recently published a study of 301 subjects with obsessive compulsive disorder (OCD).

In previous posts it was noted that hoarding can occur in the context of OCD but that not all hoarders will meet criteria for OCD.  In the Timpano et al study, subjects started with a diagnosis of OCD and then were grouped into those with hoarding and those without hoarding behaviors.

The hoarding classification status was assigned based upon the subject response to two items found on the Yale Brown Obsessive Compulsive Scale (YBOCS).  One item queried about tending to save objects and second item queried about difficulty discarding objects.  Hoarding subjects were required to endorse both items.

The research team then looked at the subjects and the brain-derived neurotrophic factor (BDNF) status.  BDNF has been a genetic region of interest in a variety of clinical neuroscience conditions including schizophrenia, anxiety and aggression.  Additionally it appears to be involved in memory function and variants of BDNF have been linked to higher rates of obesity.

BDNF appears to serve a role as a central neurological system plasticity factor and modulates both serotonin and glutamatergic neurotransmitter systems.  The BDNF gene codes for a protein that can vary in an region in status of two amino acids valine and methionine.  At this regions, individuals can be assigned one of three genetic types: Val/val, val/met or met/met.

The Timpano et al team found the following key findings:

• About 25% of those with OCD met criteria for being hoarders

• The BDNF val/val genotype was found in 77% of the hoarding group versus only 60% of the non-hoarding OCD group
• The BDNF val/val genotype correlated with increased hoarding symptom severity and BMI
• 45% of the hoarding group met criteria for obesity (BMI >30) versus only 21% of the OCD only group

The authors note that there are animal models of hoarding where hoarding behaviors have been linked to dysregulation of feeding behaviors.  When humans begin to hoard objects, there may also be a overlapping drive to hoard (and consume) food.  The authors note there may be a complex gene mechanism whereby individuals display hoarding, increased body weight and psychopathology as evidence of a "thrifty gene" strategy that may have survival and evolutionary manifestations.

It would be informative to examine the BDNF gene status of hoarders without a diagnosis of OCD.  The authors note that interaction between BDNF and serotonergic function may partially explain some other the BDNF-hoarding-obesity triad.

There role of serotonin in OCD has received significant research attention. In the next post, I will look at the potential for selective serotonergic antidepressants pharmocotherapy in the treatment of hoarding behaviors.

The molecular model of BDNF above is in the public domain from a Creative Commons Attribution-ShareAlike 3.0 file (Wikepedia) authored by Microswitch.

Timpano, K., Schmidt, N., Wheaton, M., Wendland, J., & Murphy, D. (2011). Consideration of the BDNF gene in relation to two phenotypes: hoarding and obesity. Journal of Abnormal Psychology DOI: 10.1037/a0024159

Paranoia: Prevalence and Correlates

Clinicians dealing with psychiatric disorders commonly encounter patients with paranoia in their clinical practices.  However, it is important for clinicians to understand the relatively frequency of paranoia endorsement by people in the general population.  Whether paranoia is a pathological phenomenon commonly depends on the degree of paranoia, associated signs and symptoms and presence (or absence) of a formal psychiatric diagnosis.  Freeman and colleagues from the Institute of Psychiatry other colleagues in London published an important paper to address this issue.

Their data and research stems from a general population study of over 7,000 general population survey respondent in England.  To assess paranoia in the general population, subjects were asked three questions where positive responses reflected increasing severity of paranoia.  The three questions in the survery (and the general population rate of endorsement) were:

• Paranoia level 1. ‘Over the past year, have there been times when you felt that people were against you?  (18.6%)
• Paranoia level 2. ‘In the past year, have there been times when you felt that people were deliberately acting to harm you or your interests ? (8.2%)
• Paranoia level 3. ‘In the past year, have there been times you felt that a group of people was plotting to cause you serious harm or injury?  (1.8%)

I found it interesting the relatively high rate of endorsement of paranoia level 1 in the general population.  Nearly one in five endorsed feeling times in the last year when they felt that people were against them.  As the severity of paranoia increased, the prevalence rates decreased to less than 2% of the population fealing a good of people was plotting to cause them harm or injury.

The research also looked at some of the correlates of paranoia.  Those endorsing each level of paranoia were compared to those with no endorsement of paranoia.  The paper is packed with data but here are some of the things that stood out for me:

• Level 1 paranoia was more likely to be endorsed by women while level 3 paranoia was more likely to be endorsed by men
• Paranoia rates were higher in populations with a variety of medical conditions including: diabetes, hearing or visual problems, recent heart attack/angina.  There was a trend for increased level 3 paranoia in those with obesity (BMI greater than 30 kg/m2)
• Paranoia rates were higher in a variety variables indicating social isolation, i.e. separated, divorced or single marital status, fewer number of close family members or friends, fewer supportive relationships
• Paranoia rates were higher along with a variety of other psychiatric symptoms/disorders, i.e. insomnia, depression,worry, anxiety, panic and PTSD
• Paranoia rates were increased in those endorsing suicidal thoughts in past year, history of a suicide attempt, anxiolytic and antidepressant drug use and not surprisingly antipsychotic medication use
• Paranoia rates were strongly and progressively associated with cannabis use and less strongly associated with heavy drinking

In summary, this research manuscript provides a valuable overview of paranoia.  Elements of paranoia are relatively common in the general population.  Paranoia is a marker for many other psychiatric syndromes and cannabis abuse.  Clinicians should include screening questions for paranoia in routine clinical assessment.

Photo of Japanese Maple Courtesy of Yates Photography

Freeman, D., McManus, S., Brugha, T., Meltzer, H., Jenkins, R., & Bebbington, P. (2010). Concomitants of paranoia in the general population Psychological Medicine, 41 (05), 923-936 DOI: 10.1017/S0033291710001546

Phentermine/Topiramate Combo for Obesity

Molecular Model of Topiramate

Previous Brain Posts summarized some of the pharmacologic agents in the pipeline for weight loss as well as some drug combinations.  A recent research study published in Lancet provides additional data on one of the drug combinations being studied: phentermine and topiramate.

This new study is important because it looked at 56 weeks of treatment and target obese individuals with at least two obesity-related medical complications.  Subjects were required to have significant obesity (BMI 27-45 kg/m2) and at least two of the following:  hypertension, dyslipidemia, diabetes or prediabetes, abdominal obesity).  Each of these factors increases the risk of mortality associated with being overweight.

The key findings from the study--number of pounds lost at 56 weeks:

• placebo-- 3.1 pounds (1.4 kg)
• phentermine 7.5mg/topiramate 46 mg-- 17.8 pounds (8.1 kg)
• phentermine 15.0mg/topiramate 92 mg-- 22.4 pounds (10.2 kg)

The weight loss outcome in the highest dose group was approximately 10% of body weight--a significantly positive result in light of previous single agent trials.

One area of outcome caught my eye, the change in physiological and metabolic parameters over the course of the study.  Waist circumference decreased about an inch (2.4 cm) in the control group but three (7.6 cm) to three and one half inches (9.2 cm) in the low dose and high dose treatment group.  Blood lipid changes were also pretty impressive with LDL and triglycerides falling more in the treatment groups while good cholesterol values (HDL) increased more with the active drug combination.  Fasting insulin levels dropped significantly more in the active groups also.

Given historical problems with use of weight loss drugs, safety issues are important to monitor closely.  The most common adverse events in the active agent groups with rates higher than placebo were dry mouth (21%), paresthesias (numbness and tingling) (21%),  constipation (17%), dysguesia (10%), insomnia (10%), dizziness (10%), anxiety (4%) and irritability (3%).  Although infrequent (1%) depression was noted in the high dose group more than placebo.  One potential red flag with this combination was report of 11 cases of renolithiasis (kidney stones) in the high dose active agent group.

Topiramate inhibits the action of carbonic anhydrase.  This effect can cause decreases in serum bicarbonate and potassium as well as increasing risk of renolithiasis.  The rate of renolithiasis was lower in the low dose group suggesting a dose-related effect.  Additional, inhibitors of carbonic anhydrase have been noted to cause alterations in sensation (paresthesias) and in taste (dysguesia).

The authors note several relevant areas of caution.  Subjects with clinically relevant depression were excluded from the study due to concern about drug-induced depression.  Also some subjects noted cognitive adverse events, attention or memory problems, and this needs to be monitored in those more prone to such effects.  Additionally, the first application to approve this combination of phentermine and topiramate was turned down for lack of long-term cardiac safety data and data on risk of use during pregnancy.  This additional data is likely being collected for analysis and possible re-application given the impressive level of weight loss associated with this combination.

Molecular model of topiramate from Wikipedia Creative Commons, Author fvasconcellos.

Kishore M Gadde, David B Allison, Donna H Ryan, Craig A Peterson, Barbara Troupin, Michael L Schwiers, Wesley W Day (2011). Eff ects of low-dose, controlled-release, phentermine plus
topiramate combination on weight and associated
comorbidities in overweight and obese adults (CONQUER):
a randomised, placebo-controlled, phase 3 trial Lancet : 10.1016/S0140- 6736(11)60205-5

Exercise May Reduce Appetite But Increases Calorie Consumption

The relationship between exercise, appetite and food intake is a complex relationship.  Aerobic exercise has been touted as a way to reduce appetite potentially increasing weight loss.  This effect has been termed the anorexia of exercise.  The effect appears to be commonly found after exercising at greater than 60% of maximum oxygen consumption.  This decreased appetite after exercise has been  possibly due to the redistribution of blood flow from the gastrointestinal tract to the peripheral muscles.   However, a temporary reduction in appetite following exercise may not actually correlate with a reduced caloric consumption over a more extended period of time.

Derek Laan and colleagues from Purdue University and the University of Missouri recently published a further look at the relationship between exercise, appetite and caloric intake.  In addition to aerobic exercise, they examined the effect of resistance exercise on appetite and calorie consumption.  The key issues in the design of this study included:

• Subjects: Male and female from the Purdue community, ages 18 to 29, BMI between 18 and 29 (normal weight to overweight but obesity excluded), percent body fat less than 20% for men and less than 35% for women, not currently dieting with no recent weight loss/gain, nonsmokers, nondiabetic and exercising at least twice per week for 30 minutes in each of aerobic and resistance categories.
• Experimental Design: Three sessions: 1.) one aerobic session of 35 minutes cycling at 70% maximum heart rate, 2.) one resistance training session of 35 minutes including 3 sets of 5 weight lifting exercising at 75% maximum, 3.)  a control session of no exercise
• Appetite and Calorie Consumption:  1.) Perceived appetite rated before and after exercise using 13 point scale with 1=not at all hungry and 13=extremely hungry, 2.) Thirty minutes after exercise subjects were given 30 minutes to consume a pasta salad meal with instructions to eat as much or as little as desired until feeling comfortably full.

The key results of the research included:

• Aerobic exercise but not resistance exercise reduced hunger ratings 10 minutes after exercise.  The effect lasted about 30 minutes when hunger ratings returned to levels experience by resistance exercise and controls
• Mean caloric meal intake was 897 calories for aerobic exercise group, 924 calories for the resistance exercise group and 784 calories for the control group (both exercise groups consumed more than controls—14 to 18% more, a statistically significant amount

The authors concluded that in healthy adults, aerobic exercise does temporarily reduce hunger ratings but the effect is small, transient and not related to reduced calorie consumption in an unrestricted meal setting.  A similar study would be interesting in a group of patients with anorexia nervosa who commonly exercise to excess in an attempt to lose weight and maintain weight below medically healthy levels.   Additionally, similar studies in obese subjects might be helpful in prescribing the best exercise and diet regimens for weight loss.   This study suggests resistance training alone may increase caloric intake more than the calories expended in resistance exercise.   The increase caloric consumption with aerobic exercise probably contributes to the limited weight loss found in starting an aerobic exercise program.

Photo of March 2011 sunrise at Juno Beach, Florida courtesy of Yates Photography.

Laan DJ, Leidy HJ, Lim E, & Campbell WW (2010). Effects and reproducibility of aerobic and resistance exercise on appetite and energy intake in young, physically active adults. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme, 35 (6), 842-7 PMID: 21164556

Is the M3 Receptor a Target for Obesity Drug Development?

Acetylcholine (ACH) is a key neurotransmitter involved in modulating a variety of central and peripheral nervous systems.  ACH acts on two types of receptors-nicotinic receptors and muscarinic receptors.  There are at least 5 submits of the muscarinic receptor (M1 through M5).  Each receptor appears to have specific functions.

Knockout mice (mice with absence of a specific gene) can provide some insight into the function of individual neurotransmitter receptors.  But translating mice findings into humans is complicated.  A recent study by Pomper et al published in the journal Neurology provided a unique analysis of a man felt to have a specific deficiency of the M3 receptor.

A 38 year old man presented for assess with the following signs and symptoms:

• Big pupils (mydriasis) unresponsive to light
• (Pupil size and responsive appeared normal in photos of patient at age 18)
• Reduce ability to empty his bladder (external pressure only method of voiding)
• Recurring bladder infections related to incomplete bladder emptying
• Lean body habitus (BMI 18.5)
• Impaired sweating function with dry hands and feet

These symptoms were consistent with findings of mice with absent M3 receptors following genetic manipulation.  These mice typically are lean with pupil size abnormalities with limited response to ACH agonist drugs such as pilocarpine.  M3 knockout mice also show bladder function abnormalities.

Specific deficiency of the M3 receptor protein was found in testing of this case study.  The authors examined this man for genetic abnormalities involving the M3 receptor and were unable to find an abnormality.  However, the man showed high levels of auto antibodies of no specific pattern.  Anti-nuclear antibodies found in Sjogren syndrome were not present.  The authors note that patients with Sjogen syndrome have symptoms suggestive of M3 receptor dysfunction including impaired sweating.

The intriguing finding in this man to me was the lean body habitus.  We know that anticholinergic drugs such as Benadryl (diphenhydramine) when used over extended periods of time can cause increased appetite and weight gain.  It is possible that drugs designed to decrease M3 receptor activity may have potential in the treatment of obesity.  However, it is likely such drugs would have effects on bladder and ocular function.


Drug model of muscarine, the muscarinic receptor agonist, courtest of Creative Commons, author RingO 

Pomper JK, Wilhelm H, Tayebati SK, Asmus F, Schüle R, Sievert KD, Haensch CA, Melms A, & Haarmeier T (2011). A novel clinical syndrome revealing a deficiency of the muscarinic M3 receptor. Neurology, 76 (5), 451-5 PMID: 21282591

All-Cause Mortality Risk and BMI

Elevated BMI (body weight in kilograms divided by height in meters squared) increases risk for heart disease and some types of cancer.  There is less data on the relationship and effect size on all-cause mortality.   A recent pooled study analysis of approximately 1.5 million adults in the U.S. provides important new data.

The authors of the study pooled (aggregated) 19 longitudinal studies of white (non-Hispanic) samples.    The large sample size allows for controlling for possible confounding variables.  The variables controlled in this study included:

• Alcohol intake
• Educational level
• Marital status
• Physical activity level
• Smoking status (current smoker, former smoker and never smoked)

The graph summarizes the findings for all-cause mortality.  The summary measure is the hazard ratio.  The death rates for those in the normal BMI range (20.0 to 24.9) is set at 1.0 and those in other weight ranges compared against this standard.   For example, a hazard ratio of 1.5 would indicate a 50% increase in risk of death during the follow-up period compared to the normal weight group.

The study found a progressive increase in mortality risk for those with increasing BMI.  The highest BMI group showed a hazard ratio of about 2.5.  Of note, those with low BMI also had higher mortality risk although not as great as for those in the highest BMI.   The authors broke down the cause of death into 3 groups: cardiovascular death, death due to cancer, and other causes.   Among those who never smoked, the highest BMI groups showed greater risk for cardiovascular death (HR 4.4), other causes of death (HR 3.0) and cancer deaths (HR 1.9).  The lowest BMI group (15.0-18.4) showed excess deaths in the other death causes category (HR 1.84) and cardiovascular death (HR 1.47).  Cancer deaths were not statistically higher in this low weight group.

The authors note that the low weight group risk for mortality may be an artifact of undiagnosed or presence of a disease not assessed in the study.   The hazard ratio in this low weight group was weaker among those with high physical activity (lean and fit) compared to those who were inactive and may have “illness-induced” wasting.  An interesting finding was that the lowest BMI had relative high rates of smoking (25%) compared to the other weight groups.  This association was controlled for in the analysis and the authors note, “we cannot rule out the possibility that being underweight is associated with increased mortality.”

 The authors note this study reflects findings in a relatively affluent white population and may not be generalizable to other populations.  The study underscores the need for public health measures to prevent obesity and improve the treatment success rates in those already significantly overweight.


If you would like to calculate your own BMI, you can use this link from the National Heart Lung and Blood Institute.

Graph of study summary findings is an original figure provided by Brain Posts.

Berrington de Gonzalez A, Hartge P, Cerhan JR, Flint AJ, Hannan L, MacInnis RJ, Moore SC, Tobias GS, Anton-Culver H, Freeman LB, Beeson WL, Clipp SL, English DR, Folsom AR, Freedman DM, Giles G, Hakansson N, Henderson KD, Hoffman-Bolton J, Hoppin JA, Koenig KL, Lee IM, Linet MS, Park Y, Pocobelli G, Schatzkin A, Sesso HD, Weiderpass E, Willcox BJ, Wolk A, Zeleniuch-Jacquotte A, Willett WC, & Thun MJ (2010). Body-mass index and mortality among 1.46 million white adults. The New England journal of medicine, 363 (23), 2211-9 PMID: 21121834