mistressdawnatnight

[mistressdawnatnight]

Data Management - Week 4

Bar Charts of Family Meal Frequency and Marijuana Use

Here is the SAS code that produces the tables and charts in this analysis;

LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly;

DATA new; set mydata.addhealth_pds;

LABEL H1WP8="Family Mealtimes Per Week"  H1FS10="Fearfulness - Feelings Scale"  H1FS11="Happiness - Feelings Scale"  H1FS19="Feel Life is Not Worth Living"  H1TO30="Tried MJ Ever"  H1EE12="Expectation Will Live to Age 35";   /* Remove Unwanted Data */ IF H1WP8 GT 7 THEN H1WP8=.; /* Removes 96, 97, 98 answers */ If H1FS10 GT 4 THEN H1FS10=.; /* Removes 6, 8 */ If H1FS11 GT 4 THEN H1FS11=.; /* Removes 6, 8 */ If H1FS19 GT 4 THEN H1FS19=.; /* Removes 6, 8 */

/* Creating New Variables */ IF H1WP8=0 THEN FAMDINBIN=0; ELSE IF H1WP8=7 THEN FAMDINBIN=1; ELSE FAMDINBIN=.;

IF H1WP8=0 THEN FAMDINFREQ=.; ELSE IF H1WP8 GE 1 AND H1WP8 LE 4 THEN FAMDINFREQ=0; ELSE FAMDINFREQ=1;

If H1TO30=0 THEN NEVERMJ=1; ELSE IF H1TO30 GT 0 THEN NEVERMJ=0;

IF H1TO30=0 THEN INVOLMJ=.; IF H1TO30 GT 0 AND H1TO30 LT 10 THEN INVOLMJ=1; ELSE IF H1TO30 GE 10 THEN INVOLMJ=0;

PROC SORT; by AID;

PROC FREQ; TABLES H1WP8 FAMDINBIN FAMDINFREQ NEVERMJ INVOLMJ;

PROC UNIVARIATE; VAR H1WP8;

/* Univariate Bar Charts */ PROC GCHART; VBAR H1WP8/DISCRETE type=PCT width=20; PROC GCHART; VBAR FAMDINBIN/DISCRETE type=PCT width=20; PROC GCHART; VBAR FAMDINFREQ/DISCRETE type=PCT width=20; PROC GCHART; VBAR NEVERMJ/DISCRETE type=PCT width=20; PROC GCHART; VBAR INVOLMJ/DISCRETE type=PCT width=20;

/* Bivariate Bar Charts */ PROC GCHART; VBAR NEVERMJ/DISCRETE type=MEAN SUMVAR=FAMDINBIN width=20; PROC GCHART; VBAR NEVERMJ/DISCRETE type=MEAN SUMVAR=FAMDINFREQ width=20; PROC GCHART; VBAR INVOLMJ/DISCRETE type=MEAN SUMVAR=FAMDINBIN width=20; PROC GCHART; VBAR INVOLMJ/DISCRETE type=MEAN SUMVAR=FAMDINFREQ width=20;

RUN;

My independent variable, H1WP8, records the number of shared family meal times per week and ranges from 0 to 7. We can see from the table that 7 meals shared per week is the most frequent response with the next most frequent being 5 and 0. The UNIVARIATE procedure was run on this variable to determine its mean(4.6), median(5.0) and mode(7.0).

From the univariate bar chart, we can seethe three maxima and that the responses are shifted right to higher values. The maximum at 5 likely corresponds to weekdays and explains the dip at 6.

Based on this information, and knowing that the dependent variables I would like to check against are categorical, I collapsed the quantitative variable H1WP8 in two ways;

1) Looking at only the extrema, I constructed FAMDINBIN which is set to ‘0′ if no meals were shared and set to ‘1′ if all 7 meals per week were shared. This leaves out all values in between (1-6 meals shared).

2) Removing respondents who never shared any meals each week, would there still be a trend looking at fewer meals vs more meals. For this I constructed FAMDINFREQ which is set to ‘0′ if there were 1-4 meals and set to ‘1′ if there were 5-7 meals shared.

Looking at the extrema, the ratio of no meals shared to all meals shared is 1:4 but looking at the frequency, about 1/3rd have fewer than the median meals per week while 2/3rds have the median or above. 

Finally, I looked at the dependence of the number of meal times on whether kids had ever tried marijuana (NEVERMJ=0) or not (NEVERMJ=1). In these plots, the vertical height of each bar gives us information on the family meals shared. If the bar height is at 0.5 then for that MJ use category, there is no trend in the response w.r.t. number of meals shared. For all of the bivariate plots below, the bars are above 0.5 showing a trend towards more meals shared.

But the difference between the two bars shows how much more of a trend exists for one case over the other. In both the binary variables created for family meals shared, there is a positive trend towards less trying of marijuana when more family meals are shared. Unsurprisingly, the difference in bar heights is greater for the extreme variable FAMDINBIN, than for the binary split along frequency FAMDINFREQ. But for both cases, there is a 15-20% difference.

[mistressdawnatnight]

Brain Damage During Stroke May Point to Source of Addiction

A pair of studies suggests that a region of the brain – called the insular cortex – may hold the key to treating addiction.Scientists have come to this conclusion after finding that smokers who suffered a stroke in the insular cortex were far more likely to quit smoking and experience fewer and less severe withdrawal symptoms than those with strokes in other parts of the brain.

“These findings indicate that the insular cortex may play a central role in addiction,” said Amir Abdolahi Ph.D., M.P.H., lead author of the studies. “When this part of the brain is damaged during stroke, smokers are about twice as likely to stop smoking and their craving and withdrawal symptoms are far less severe.”

Abdolahi is a clinical research scientist at Philips Research North America and conducted the research while an epidemiology doctoral student in Department of Public Health Sciences at the University of Rochester School of Medicine and Dentistry.

While smoking rates have remained flat for the last decade, smoking is still responsible for nearly one of every five deaths in the U.S. and smoking places individuals at a significantly higher risk for heart disease, cancer, and stroke.

The frontline prescription drugs currently used to treat tobacco dependence – which include bupropion and varenicline – primarily target the brain’s “reward” pathways by interfering with the release and binding of dopamine in the brain in response to nicotine.While these drugs are generally well-tolerated, they have relatively high rates of relapse.  Most have a reported success rate of up to 30 percent after six months, meaning that 70 percent of the people who use these treatments eventually start smoking again.Nicotine replacement therapies, such as patches and lozenges, have a similar success rate.  

Recent studies have hinted that a specific part of the brain – a central region called the insular cortex – may also play an important role in the cognitive and emotional processes that facilitate drug and tobacco use.

The authors of the current set of studies – which appear in the journals Addiction and Addictive Behaviors – tested this theory in a somewhat unique fashion: by determining whether smokers whose insular cortex had been damaged during a stroke are more likely to quit smoking.

The researchers examined two different sets of indicators – whether patients have resumed smoking after a stroke and the severity of their craving for a cigarette during their hospitalization.

The studies involved 156 stroke patients who were admitted to three hospitals in Rochester, NY, all of whom were identified as active smokers.The location of the stroke for each patient was determined by MRI and CT scans and the study participants were divided into two groups – those with a stroke occurring in the insular cortex and those with a stroke in another part of the brain.

While recovering in the hospital the researchers measured the participant’s level of smoking withdrawal.Because hospitalization essentially constitutes a period of forced abstinence from smoking, this was an ideal environment to measure the severity of withdrawal symptoms.  

The researchers used two separate survey tools to measure aspects of withdrawal, such as anger, anxiety, cravings, concentration, hunger, sadness, and sleep.They found that patients with strokes occurring in the insular cortex had fewer and far less severe withdrawal symptoms than those with strokes in other parts of the brain.

The researchers also followed the study participants for three months to determine whether or not they had resumed smoking.It is reasonable to assume that the “wake up call” of having a stroke is a powerful motivator for smokers to quit, both because the smoking may have been one of the factors that caused the stroke in the first place and during recovery they would have been strongly urged to quit by their health care providers.  

Regardless, the researchers found a significant disparity in the smoking cessation rates between the two study groups. Almost twice as many patients with strokes in the insular cortex quit smoking compared to those with strokes in other parts of the brain – 70 percent vs. 37 percent.

These findings open the door for researchers to potentially explore therapies that could target this area of the brain and disrupt its role in addiction, potentially with new drugs or other techniques such as deep brain stimulation or transcranial magnetic stimulation.They also speculate that, in addition to smoking, the role of the insular cortex could apply to other forms of addiction.  

“Much more research is needed in order for us to more fully understand the underlying mechanism and specific role of the insular cortex, but is clear that something is going on in this part of the brain that is influencing addiction,” said Abdolahi.

[mistressdawnatnight]

Discrimination During Adolescence has Lasting Effect on Body

In both blacks and whites, everyday feelings of discrimination can mess with the body’s levels of the primary stress hormone, cortisol, new research suggests.

In African-Americans, however, the negative effects of perceived discrimination on cortisol are stronger than in whites, according to the study, one of the first to look at the biological response to the cumulative impact of prejudicial treatment.

The team of researchers, led by Northwestern University, also found that the teenage years are a particularly sensitive period to be experiencing discrimination, in terms of the future impact on adult cortisol levels.

“We found cumulative experiences matter and that discrimination mattered more for blacks,” said study lead author Emma Adam, a developmental psychologist at Northwestern’s School of Education and Social Policy. “We saw a flattening of cortisol levels for both blacks and whites, but blacks also had an overall drop in levels. The surprise was that this was particularly true for discrimination that happened during adolescence.”

The study will be published in the December 2015 issue of the journal Psychoneuroendocrinology and is currently available online.

In times of stress, the body releases several hormones, including cortisol. Ideally, cortisol levels are high in the morning to help energize us for the day. At night, cortisol levels wane as the body prepares for sleep.

Previous research indicates that discrimination can affect the natural rhythm of this process. Work by Adam and others suggests that young adults from racial/ethnic minority groups who perceive more discrimination have higher levels of cortisol in the evening and less decline in cortisol levels across the day than those with lower discrimination.

Having flatter or dysfunctional cortisol levels throughout the day is linked with higher fatigue, worse mental health, cardiovascular disease and mortality, as well as cognitive problems, such as impaired memory.

The latest study suggests for the first time that the impact of discrimination on cortisol adds up over time. Using data collected over a 20–year period, the researchers showed that the more discrimination people experience throughout adolescence and early adulthood, the more dysfunctional their cortisol rhythms are by age 32.

“We’ve been trying to solve the mystery behind why African-Americans have flatter diurnal cortisol rhythms than whites,” said Adam, a faculty fellow at Northwestern’s Institute for Policy Research.

“There’s a fair amount of research on how discrimination affects people in the moment. But we haven’t been sufficiently considering the wear and tear and accumulation of discrimination over lifetimes. Our study offers the first empirical demonstration that everyday discrimination affects biology in ways that have small but cumulative negative effects over time.”

Even after controlling for income, education, depression, times of waking and other health behaviors, they still couldn’t explain or remove the effects of discrimination, “making it unlikely that those other factors play a role,” Adam said.

The researchers measured discrimination from ages 12 to 32, prospectively. They also assessed adult cortisol levels over a seven-day period. Using modeling, they determined the age range during which discrimination most dramatically affected cortisol.

“Adolescence might be an important time period because there are a lot of changes in the brain and body,” Adam said. “When you experience perceived discrimination during this period of change, it’s more likely that those effects are built into the system and have a bigger impact.”

[mistressdawnatnight]

Data Analytics - week 3

Removing unwanted data, grouping data, creating new variables;

In my SAS program to analyze the ADDHealth data set with respect to the frequency of family meal times per week and some measures of emotional health in adolescents, there are several question responses that could use some managing. Mostly, removal of ‘non-answers’, the ‘refused to answer’ and the ‘I don’t know’ categories. I didn’t easily identify any data that could be recovered yet. But I did try to group the data responses of ‘Age at which first tried marijuana (MJ)’ which took values from 0(never), then age 1 to 30. I wanted to split this first into never tried MJ (NEVERMJ=1) versus tried (NEVERMJ=0). Then, I wanted to separate those that were likely given MJ by someone else the first time (ages 1-9) from those that may have decided to take that action themselves (ages 10+), so I created INVOLMJ=1 for those that tried it first involuntarily, covering ages 1-9, and INVOLMJ=0 for those ages 10 and older that had tried it.

Here is the code -

LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly;

DATA new; set mydata.addhealth_pds;

LABEL H1WP8="Family Mealtimes Per Week"  H1FS10="Fearfulness - Feelings Scale"  H1FS11="Happiness - Feelings Scale"  H1FS19="Feel Life is Not Worth Living"  H1TO30="Tried MJ Ever"  H1EE12="Expectation Will Live to Age 35";   /* Remove Unwanted Data */ IF H1WP8 GT 7 THEN H1WP8=.; /* Removes 96, 97, 98 answers */ If H1FS10 GT 4 THEN H1FS10=.; /* Removes 6, 8 */ If H1FS11 GT 4 THEN H1FS11=.; /* Removes 6, 8 */ If H1FS19 GT 4 THEN H1FS19=.; /* Removes 6, 8 */

/* Recover Usable Data */ /* Creating New Variables */ If H1TO30=0 THEN NEVERMJ=1; ELSE IF H1TO30 GT 0 THEN NEVERMJ=0;

IF H1TO30=0 THEN INVOLMJ=.; IF H1TO30 GT 0 AND H1TO30 LT 10 THEN INVOLMJ=1; ELSE IF H1TO30 GE 10 THEN INVOLMJ=0;

/*No subsetting the data */ /*IF BIO_SEX=2;*/

PROC SORT; by AID;

PROC FREQ; TABLES H1WP8 H1FS10 H1FS11 H1FS19 H1TO30 NEVERMJ INVOLVMJ;

RUN;

Here are the results -

First, I removed the categories of answers that don’t correspond to a number of meal times per week spent together, these were 96, 97 and 98 in the original data. This removed 154 data points.

Next, I wanted to remove the codes for ‘refused’ = 6 and ‘unknown’ = 8 for several questions on the feelings scale. This removed 17 for fearfulness, 15 for happiness and 19 for ‘life is not worth living’. Luckily, not many data were lost to this.

Finally, I created two new variables to categorize the MJ (ever tried marijuana) behavior. A simple split into never and had tried MJ (NEVERMJ) and also, a split between those trying before age 10 (values 1-9) and after age 10 (values GE10) to classify likely voluntary vs involuntary use. For the second new variable, the Frequency Missingrecords are those that never tried MJ. Its the same number as NEVERMJ = 1, as it should be. The 4.45% of records for involuntary MJ use the first time are likely in or around home situations with adult drug use. Those data I will keep as a special subset in future analyses.

[mistressdawnatnight]

Activated Neurons Produce Protective Protein against Neurodegenerative Conditions

Activated neurons produce a protein that protects against nerve cell death. Prof. Dr. Hilmar Bading and his group at Heidelberg University’s Interdisciplinary Center for Neurosciences have found out how this effect comes about and defined a crucial player. “We already knew that brain activity promotes neuroprotection,” Prof. Bading says. “Now we have discovered a central mechanism for this process and a key molecule produced by the body to develop a neuroprotective shield.” These results have been published in “Cell Reports”.

When nerve cells die, e.g. as a result of a stroke, Alzheimer’s disease or through age-related processes, the result may be considerable impairments of memory. Earlier studies led by Prof. Bading have shown that brain activity counteracts the death of nerve cells. The NMDA receptor plays a major role at the molecular level. This type of receptor is a molecule set in motion by biochemical neurotransmitters. Due to neuronal activity, the NMDA receptor causes calcium to enter the cell. The calcium signal is spreading within the cell, invades the cell nucleus and switches on a genetic protection programme. Prof. Bading’s group identified this nuclear calcium-induced gene programme a few years ago. “However, it was not clear to us how it leads to a protective shield,” Hilmar Bading explains.

The scientists have now discovered the explanation for this – again by studying NMDA receptors. If these receptors are not located at the neuronal junctions, i.e. the synapses, they do not contribute to the protection of cells. On the contrary, they severely damage nerve cells and cause them to die. “Life and death are only a few thousandths of a millimetre away from one another. Outside the synapse the NMDA receptor is no longer Dr. Jekyll, it becomes Mr. Hyde,” Hilmar Bading comments. The current research results show that toxic extrasynaptic NMDA receptors are suppressed through brain activity. The Heidelberg research team has identified activin A as the protein activating this process.

Activin A plays an important role e.g. in the menstruation cycle and in healing wounds. It is produced in the nervous system thanks to neuronal activity. This leads to a reduction in extrasynaptic NMDA receptors and builds up a protective shield, according to Prof. Bading. Activin A also mediates the well-known protective properties of brain-derived neurotrophic factor (BDNF), a signalling molecule that protects existing neurons and synapses, and helps developing new ones. “Activin A can therefore be regarded as a crucial activator of a common neuroprotective mechanism in the brain.”

The discoveries made by the Heidelberg neurobiologists open up new prospects for treating degenerative diseases of the nervous system. In their study they showed that activin A in mice was able to significantly reduce brain damage after a stroke. “Our research results also indicate that activin A may possibly be used to treat Alzheimer’s disease or Huntington’s disease. The characteristic degeneration of nerve cells associated with these two diseases seems to be due to an increased activity of toxic extrasynaptic NMDA receptors,” says Prof. Bading. “In everyday terms the new findings mean: An active brain produces activin A thereby protecting itself from neurodegeneration.”

[mistressdawnatnight]

(Image caption: The illustration shows that oxytocin can reach the brain in two ways: either indirectly, through the blood, or directly, along nerve pathways. A: Particles from a nasal spray. B: Route. C: Mucous membrane. D: Sensory nerve cell. E: Blood vessel. F: Nerve pathway. G: Nerve.)

Nasal spray device for mental illness

About one out of every hundred Norwegians develop schizophrenia or autism in the course of their lifetime. Moreover, at any one time some 20 000 people are receiving treatment for these problems. Many psychiatric disorders such as autism, schizophrenia and bipolar disorder are characterised by poor social functioning.

Oxytocin is a hormone that influences social behaviour and has shown promise for the treatment of mental illness.

Researchers at UiO have now discovered that low doses of oxytocin may help patients with mental illness to better perceive social signals. As part of this project, they have collaborated with the company OptiNose, who have developed a new device designed to improve medicine delivery to the brain via the nose.

Regulates social behaviour

Oxytocin has historically been known to play a crucial role in child rearing as it facilitates pregnancy, birth, and the release of milk during nursing. Further, oxytocin helps regulate cardiac functions and fluid levels. More recent research has revealed the importance of oxytocin for social behaviour.

Oxytocin is a neuropeptide and was discovered in 1953. Peptides are a group of molecules that consist of a chain of amino acids. Amino acids are also known as the building blocks of proteins, which we find in all types of cells. Oxytocin is produced in the hypothalamus, which is the brain’s coordinating centre for the hormone system.

Medicine through the nose

Because of oxytocin’s role in social behaviour, researchers have explored the possibility of administering the hormone for the treatment of mental illness. As oxytocin is a relatively large molecule, it has trouble crossing the barrier between the brain and circulating blood. Thus, researchers have administered oxytocin to patients through the nose as this route offers a direct pathway to the brain that bypasses this barrier.

However, researchers have a poor understanding of how oxytocin reaches and affects the brain. The most effective dose for treatment has also received little research attention.

Professor Ole A. Andreassen and his research team have collaborated with OptiNose on a project that evaluated two different doses of oxytocin and on how they affect the way in which social signals are perceived.

Low doses work best

Sixteen healthy men received two different doses of oxytocin, along with placebo. Volunteers were also given an intravenous dose of oxytocin, for a comparison of the effects of oxytocin in circulating blood. The research showed that only those administered a low dose of oxytocin experienced an effect on how they perceived social signals.

Professor Ole A. Andreassen explains:

“The results show that intranasal administration, i.e. introducing oxytocin through the nose, affects the function of the brain. As no effect was observed after intravenous treatment, this indicates that intranasally administered oxytocin travels directly to the brain, as we have long believed. The fact that we have shown the efficacy of a low dose of oxytocin on social perception is even more important.

A dose that is lower, but that still influences behaviour, will entail a lower risk of affecting other regulatory systems in the body. Very high doses of oxytocin could, in fact, have the opposite effect on social behaviour.”

The scientists also discovered that individuals with larger nasal cavities had a stronger response to a low dose of oxytocin.

Breathing helps

OptiNose uses a new technology to distribute medicine to the brain, making use of the user’s breath to propel medicine deep into the nasal cavity.

The device administers oxytocin high up into the patient’s nasal cavity. When the medicine is targeted deep inside the nose, it enables brain delivery along nerve pathways from the uppermost part of the nasal cavity. Conventional nasal spray devices are not suited to consistently deliver medicine high up enough into the nose.

The device also expands the nasal cavity, facilitating nose-to-brain medicine delivery. As the user exhales into the device, this closes the soft palate and prevents the medicine from being lost down the throat.

Since less medicine is lost along the way, patients can take smaller doses and accordingly experience fewer side effects.

May yield new treatments

The next step in the research is to carry out the same tests on people with mental illness.

"We are now running tests in volunteers diagnosed with autism spectrum disorders”, says Dr Quintana.

“We hope that this research project is the first step in the development of a series of new medicines that may be of great help to more people with mental illness”, concludes Professor Andreassen.

The study has been published in Translational Psychiatry.

[mistressdawnatnight]

Research shows testosterone changes brain structures in female-to-male transsexuals

Brain imaging shows that testosterone therapy given as part of sex reassignment changes the brain structures and the pathway associated with speech and verbal fluency. This result supports research that women in general may deal with speech and interaction differently than men.

The sex hormone testosterone exerts a substantial influence on human behaviour and cognition. Previous studies have shown that testosterone has a particular influence on verbal fluency. But these investigations (which due to ethical reasons are mostly observational studies or one-off hormone administrations) have been limited in what they can show, as it has been impossible to follow the direct effect of the hormone on the brain structure.

Now a unique study has revealed the changes over time (longitudinal changes) in the brain of female-to-male transsexuals receiving continuous, high-dose hormone therapy as part of their sexual reassignment.

The results show that this therapy induces structural changes in areas of the brain involved in verbal fluency in female-to-male transsexuals. This may have wider implications, for example in the way that men and women handle speech and interaction.

The researchers, from Vienna and Amsterdam, worked with 18 female-to-male subjects (27.6 ±6.4 years), before and during testosterone treatment. The subjects underwent MRI brain scans before and after 4 weeks of the testosterone administration. The results showed that with testosterone treatment the volume of grey matter decreased in two specific regions of the brain, the Broca’s and Wernicke’s areas, which are mainly responsible for language processing. At the same time, the neuronal pathway (white matter) connecting these two regions via the extreme capsule got stronger.

According to researcher Dr Andreas Hahn (Vienna):

‘It has been known for some time that higher testosterone is linked to smaller vocabulary in children and that verbal fluency skills decrease in female-to-male transsexuals after testosterone treatment. This fits in well with our finding of decreased grey matter volume. However, the strengthening of the white matter in these areas was a surprise. We think that when it comes to certain language skills, the loss of grey matter outweighs the strengthened white matter connection’.

Researcher Prof. Rupert Lanzenberger (Vienna, Austria) continued:

‘What we see is a real quantitative difference in brain structure after prolonged exposure to testosterone. This would have been impossible to understand without looking at a transsexual population. In more general terms, these findings may suggest that the genuine difference between the brains of women and men is substantially attributable to the effects of circulating sex hormones. Moreover, the hormonal influence on human brain structure goes beyond early developmental phases and is still present in adulthood’.

Commenting for the ECNP Communications Committee, Dr Kamilla Miskowiak, said:

‘It is well-known that language development differs between girls and boys and that this is related to gender-related differences in brain maturation. However, this intriguing neuroimaging study of transsexuals before and after their female-to-male gender reassignment suggests that even adult men and women differ in brain structure within regions involved in language and speech. In particular, female-to-male gender reassignment resulted in local brain matter decrease within language processing regions, which may explain why verbal abilities are often stronger in women.’

[mistressdawnatnight]

How protein tangles accumulate in the brain and cause neurological disorders

A new Sanford Burnham Prebys Medical Discovery Institute (SBP) study takes a step forward in understanding how similar, yet genetically unrelated neurodegenerative diseases, such as Alzheimer’s disease, frontal temporal dementia, and progressive supranuclear palsy (PSP) are caused by the protein tau. The findings, published in Neuron, create new opportunities to target this key protein that leads to the brain lesions found in patients with impaired motor functions and dementia.

Our research shows how the abundance of a protein called appoptosin increases tau aggregates called tangles, which are toxic to the brain and lead to the progressive deterioration of the central nervous system,” said Huaxi Xu, professor in the Degenerative Diseases Program at SBP. “By understanding how appoptosin drives this process, we can now look at ways to inhibit key triggering points and potentially slow the progression of this class of neurodegenerative diseases which are collectively known as tauopathies.”

What are tauopathies? Tauopathies are neurodegenerative diseases that are signified by the presence of irregular tangle-like clumps of the protein tau that appear in the brain and accumulate during as the disease progresses. Because tau tangles appear in numerous diseases such as Alzheimer’s and PSP, it seemed likely that tau could be a key factor in causing neuron and brain malfunction in these diseases. However, how diseases such as PSP are triggered, and whether similar causes could generate these tau protein tangles were unknown.

Tau is a protein that maintains the integrity of long hollow tube structures called microtubules, which are major structural elements of cells. In neurons, microtubules form long extensions called axons where signals are rapidly transported over long distances when neurons communicate with each other. When tau becomes abnormally modified by hyperphosphorylation, or cleaved by the enzyme caspase-3, which itself can also facilitate its hyperphosphorylation, it loses its biological activity and goes through conformational changes that allow the protein to accumulate and form tangles.

Because it was largely unknown how caspase-3 is triggered to induce tau aggregation in tangles, determining the sequence of events that lead to tau cleavage and aggregation is one of the most important goals for the prevention and treatment of tauopathies.

Key findings of the paper

The new paper highlights a novel role for appoptosin in neurological tauopathy disorders such as PSP. PSP is a neurological disease with tau brain aggregates, where patients experience serious problems with balance, eye movement and thinking. Until now, genetic and biological triggers for PSP were unknown. By examining patients with PSP, it became apparent that variation in the DNA sequence of a single nucleotide (a SNP) was associated with the disease and correlated with elevated levels of appoptosin that increased caspase-mediated tau cleavage, tau aggregation, and synaptic dysfunction.

Neurodegenerative triggering factors appoptosin and caspase-3 cleaved tau were also found to be overabundant or over-activated in brain samples of patients with Alzheimer’s disease and frontotemporal dementia, supporting the importance of their contribution to these neurodegenerative disorders.

“A better understanding of the mechanisms that cause neurofibrillary tangles is of clinical importance for developing therapeutic strategies to prevent and treat tauopathies,” added Xu. “Our findings suggest that appoptosin and/or caspase-3 may be potential targets in the treatment of these neurodegenerative diseases.”

[mistressdawnatnight]

Very excellent article for 3 reasons; 1 - a test that works on blood samples and correlates to brain activity and 2 - reference data set based on healthy aged population (65) and 3 - longitudinal data showing the outcome, over the next 12 years, of those healthy 65 year olds, some who went on to develop cognitive decline. Need larger studies like this and more studies like this!

Early warning gene signature for Alzheimer’s

A ‘gene signature’ that could be used to predict the onset of diseases, such as Alzheimer’s, years in advance has been developed in research published in the open access journal Genome Biology.

The study aimed to define a set of genes associated with ‘healthy ageing’ in 65 year olds. Such a molecular profile could be useful for distinguishing people at earlier risk of age-related diseases. This could improve upon the use of chronological age and complement traditional indicators of disease, such as blood pressure.

Lead author James Timmons, from King’s College London, UK, said: “We use birth year, or chronological age, to judge everything from insurance premiums to whether you get a medical procedure or not. Most people accept that all 60 year olds are not the same, but there has been no reliable test for underlying ‘biological age’.

“Our discovery provides the first robust molecular ‘signature’ of biological age in humans and should be able to transform the way that 'age’ is used to make medical decisions. This includes identifying those more likely to be at risk of Alzheimer’s, as catching those at 'early’ risk is key to evaluating potential treatments.”

The researchers analyzed the RNA of healthy 65 year old subjects, and used the information to develop a signature of 150 RNA genes that indicated ‘healthy ageing’. The signature was found to be a reliable predictor for risk of age-related disease when studying RNA from tissues including human muscle, brain and skin.

With this RNA signature, they developed a ‘healthy age gene score’ which they used to test and compare the RNA profiles of different individuals, and demonstrated that a greater score was associated with better health in men and women.

The researchers studied RNA from healthy 70 year old subjects and analyzed follow-up health data over two decades. Despite all subjects being born within a year of each other, their RNA at around 70 years of age demonstrated a very wide distribution in ‘healthy age gene score’, varying over a four-fold range. This variation was shown to link to long term health. A greater gene score was also associated with better cognitive health and renal function across a 12 year span - both important determinants of mortality.

In particular, they demonstrated that patients diagnosed with Alzheimer’s Disease had an altered ‘healthy ageing’ RNA signature in their blood, and therefore a lower healthy age gene score, suggesting significant association with the disease.

Timmons added: “This is the first blood test of its kind that has shown that the same set of molecules are regulated in both the blood and the brain regions associated with dementia, and it can help contribute to a dementia diagnosis. This also provides strong evidence that dementia in humans could be called a type of ‘accelerated ageing’ or ‘failure to activate the healthy ageing program’.”

Given that early intervention is important in Alzheimer’s and there is a need to identify those at greatest risk, the authors say that their ‘healthy age gene score’ could be integrated to help decide which middle-aged subjects could be offered entry into a preventative clinical trial many years before the clinical expression of Alzheimer’s.

[mistressdawnatnight]

ADD Health Data - Looking at Variable Distributions with SAS

Below is the SAS program code to look at the ADDHealth data set -

LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly;

DATA new; set mydata.addhealth_pds;

LABEL H1WP8="Family Mealtimes Per Week" 

 H1FS10="Fearfulness - Feelings Scale"

 H1FS11="Happiness - Feelings Scale"

 H1FS19="Feel Life is Not Worth Living"

 H1TO30="Tried MJ Ever"

 H1EE12="Expectation Will Live to Age 35";

/*No subsetting the data */

/*IF BIO_SEX=2;*/

PROC SORT; by AID;

PROC FREQ; TABLES H1WP8 H1FS10 H1FS11 H1FS19 H1TO30 H1EE12 BIO_SEX;

RUN;

This program looked at 6 variables adolescents answered about their current situation and recent past. I also asked for the percentage of males (1) and females (2) of the variable BIO_SEX.

These are the code book codes and tables of the results;

The most common answers for how many times they had a parent in the room for the evening meal were 7 times week, 5 times a week and zero times a week. Just over 10% do not ever regularly share meals with their parents and this number does not include kids without parents (’97′ = 2%). About 32% of respondents (31.87%) had 3 or fewer shared meals with their parents, the 50% of respondents mark would be just under 5 meals shared per week and nearly 40% (38.85%) had all 7 meals per week shared.

The next tables asked about how fearful or happy they felt in the last 2 weeks;

For fearfulness, the data show a monotonic decrease from its maximum at ‘Never or Rarely’ (72.48%) to its minimum of 1% for ‘All or Most of the Time”. For happiness, the data shows a maximum at ‘a lot of the time’ (41.36%) and decreases slightly for ‘All or Most of the Time’ (36.85%). Interestingly, lloking at the extrema, while 172 kids were happy never or rarely (2.64%), far fewer (65 kids, 1%) felt fearful most or all of the time.

The monotonic decreasing behavior of the question which asked if life felt not worth living was even more heavily weighted towards kids who think that thought rarely or never (’0′, 88.07%) vs. kids who think that often or all of the time (’3′, 0.97%). Since the kids that think that often/all of the time (63) is very close to the number that are fearful most or all of the time (65), it will be interesting to analyze the overlap of the two groups later on.

This next table asked if kids had tried marijuana and if so, at what age. If a respondent had never tried it, the answer was recorded as ‘0′. We see below that 72.34% of respondents had never tried it. Of those that had, the largest number of respondents had around 14-15 years old (~5% each year).

This survey had slightly fewer male respondents (’1′ --> 48.39%) than females (’2′ --> 51.6%). One student refused to answer.

It will be interesting to analyze the dependence of these variables on each other in future programs/analyses.

[mistressdawnatnight]

Nourishing Adolescents Through Family Mealtimes – An analysis of frequency of family mealtime with positive and negative adolescent behaviors.

Coursera – Data Management and Visualization

Student: Shirley Louise-May

Week 1 Assignment: Getting your research project started (due 09/20/15)

Research Project Title:

Nourishing Adolescents Through Family Mealtimes – An analysis of frequency of family mealtime with positive and negative adolescent behaviors.

Selected Data Set:

The National Longitudinal Study of Adolescent Health (AddHealth) is a representative school-based survey of adolescents in grades 7-12 in the United States. The Wave 1 survey focuses on factors that may influence adolescents’ health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities.

Research Question and Hypothesis:

As a parent of three adolescents (13, 16 and 18 years old) and a fulltime working single parent, I have searched my soul and consulted books, online experts and friends for the most effective ways to positively affect my teens growth into healthy, happy, forward thinking adults. The advice has been diverse and often contradictory. In the end, I have tried to ensure that consistency in several areas, small as they are, will have a much larger downstream positive effect – we have sit down meals together. Not all the time, but enough so that they ask for them when its been a few days. That to me is a good sign.

With the ADDHealth survey, I have a chance to explore and test my hypothesis in a comprehensive manner. In section 16 on ‘Relations with Parents’, question H1WP8 asks “On how many of the past 7 days was at least one of your parents in the room with you when you ate your evening meal?” There were 6504 respondents. Available choices for answers are numerical 0 days to 7 days, and 3 alternate categories. While less than 3% (154/6505) responded in the alternate categories, interestingly, there are 3 data peaks in the 0-7 day numerical range; 0 days(11%), 5 days(11%) and 7 days(39%). This should lead to some interesting analysis on not only whether being present for meal is an influencing factor in adolescents growth, but also, if there is an optimal amount.

The factors this interaction may influence are many, but I have identified several specific questions to analyze the dependence on;

Section 3 – General Health;

·         Q1 Health (H1GH1)

·         Q17 Poor appetite (H1GH17)

·         Q18 Trouble with sleep (H1GH18)

·         Q22 Fearfulness (H1GH22)

·         Q28 Perception of weight (H1GH28)  

Section 10 – Feelings Scale;

·         Q2 – Poor appetite (H1FS2)

·         Q4 – Felt worthwhile (H1FS4)

·         Q5 – Focus Issues (H1FS5)

·         Q6 – Depression (H1FS6)

·         Q9 – Failure Issues (H1FS9)

·         Q10 – Felt Fearful (H1FS10)

·         Q11 – Felt Happy (H1FS11)

·         Q19 – Life Not Worth Living (H1FS19)

Section 16 – Relations to Parents;

·         Q9 – How close to Mom (H1WP9)

·         Q13 – How close to Dad (H1WP13)

·         Q17A-K – Things done with Mom last 4 wks (H1WP17A-K) * esp F – had a talk about a personal problem

·         Q18A-K – Things done with Dad last 4 wks (H1WP18A-K) * esp F – had a talk about a personal problem

Section 28 – Tobacco, Alcohol and Drug Use

·         Q1, Q3 – Tried smoking, habitual smoker  (H1T01, H1T03)

·         Q12, Q14, Q15 – Tried alcohol, not with parents, frequent alcohol use (H1T012, H1T014, H1T015)

·         Q30, Q32 – Tried marijuana (H1T030, H1T032)

·         Q43, Q37, Q40, Q43 – Tried cocaine, inhalants, any other illicit, any needle drug (H1T034, H1T037, H1T040, H1T043)

Section 29 – Delinquency Issues (vandalism, theft, violence, weapons)

·         Q1-Q15 – Past 12 months, report delinquent behaviors; H1DS1-H1DS15

Section 33 – Suicidal Thoughts

·         Q1 – Past 12 months, thought about suicide (H1SU1)

·         Q2 – Past 12 months, attempted suicide (H1SU2)

·         Q8 – Self Administered Answer Honesty (H1SU8)***

Section 38 – Educational, Employment, Financial & Life Expectations

·         Q1 – Desire to go to college (H1EE1)

·         Q2 – Expectation will go to college (H1EE2)

·         Q12 – Expectation will live to age 35 (H1EE12)

·         Q13 – Expectation will marry by age 25 (H1EE13)

·         Q14 – Expectation will die by age 21 (H1EE14)

·         Q15 – Expectation will get HIV or AIDS (H1EE15)

Over these seven sections of adolescent feelings, behaviors and life expectations – what I want to explore through data analysis is if the simple act of regularly sharing meals with them is effective at tipping the scales away from dangerous, risky or self-damaging behavior or perceptions?   Is it a positive influence on their present state of well-being and their optimism for the future? And how much of our time, as busy parents, should be invested in this simple act?

Literature Review (Google Scholar search “Family Meals and Adolescent Behavior”):

Summary of findings from Literature Review

In both small and large samples, single surveys and longitudinal studies, there seems to be general agreement that frequent family meals are positively associated with positive behaviors and negatively associated with negative behaviors. It is noted that several studies made adjustments in the statistics for measures of family connectedness. I am curious to read in more detail how and why this was done. I can imagine that you can have closely connected families who do not share meals and disconnected families that stringently share meals, but these should be very small populations in any large data set. 

My primary question will be to assess how ‘cared about’ by their parents adolescents feel as a function of frequency of meals together as I hypothesize that all positive and negative effects downstream are modulated by that primary association. As a parent, it is the negative association with dangerous and risky behaviors that, if substantiated, would provide ample motivation for me to overcome the logistical challenges of single parenting, full time work and making time for family meals as often as I can.

References Reviewed (4 full text articles, 4 abstracts only available without purchase)

·         2011 Journal for Nurse Practitioners (abstract only) Fruh et al. The Surprising Benefits of the Family Meal Summary; Literature review – family meal has declined drastically since 1966. Frequent family meals often see the following benefits: demonstration of positive values and avoidance of high risk behaviors (substance abuse, sexual activity, depression/suicide, violence, etc.)

 ·         2010 Journal of Adolescence (abstract only) Sen, B. The relationship between the frequency of family dinner and adolescent problem behaviors after adjusting for other family characteristics Summary; Data from the National Longitudinal Survey of Youth 1997. Data was adjusted for family connectedness, parental awareness, and other potentially confounding factors. Problem behaviors analyzed included substance abuse, physical violence, property destruction, stealing, running away, gang membership. Frequency of family meals is negatively associated with substance abuse and running away in females, drinking, physical violence, property destruction, stealing and running away for males.

 ·         2009 Journal of Adolescent Health (abstract only) Fulkerson et al. Are there nutritional and other benefits associated with family meals among at-risk youth? Summary; N=145, 52% male, 61% non-white, alternative high-schools à family dinner frequency negatively associated (p<0.05) with depressive symptoms, adolescents who reported never eating family dinner were more likely to be overweight ([OR]=2.8) and food insecure than those reporting 5-7 meals per week.

 ·         2008 Archive of Pediatric Adolescent Medicine (full text article) Neumark-Sztainer, D. et al. Family Meals and Disordered Eating in Adolescents:Longitudinal Findings from Project EAT Summary; 5-year longitudinal associations from 1999 to 2004, N= 2516. For girls, >/= 5 family meals a week in 1999 led to lower incidences of extreme weight control behaviors in 2004. No association for boys was observed.

 ·         2006 Journal of Adolescent Health (full text article) Fulkerson et al. Family Dinner Meal Frequency and Adolescent Development: Relationships with Developmental Assets and High-Risk Behaviors Summary; N= 99,462, 49.4% male, 86% Caucasian. Positive associations found between frequency of family dinners and developmental assets both external (support, boundary, expectation [OR]=2.1-3.7) and internal (learning, values, social skill, positive identity [OR]=1.8-2.6).

 ·         2006American Journal of Preventative Medicine (full text article) Ackard D., et al. Parent-Child Connectedness and Behavioral and Emotional Health Among Adolescents Summary; N=4746 public school students Project EAT (Eating Among Teens Survey 2001) Examined parental caring and behavioral outcomes in detail.

 ·         2004 Archive of Pediatric Adolescent Medicine (full text article) Eisenberg, M. et al. Correlations Between Family Meals and Psychosocial Well-being Among Adolescents Summary; N=4746 1998-1999 school-based survey of adolescents from diverse communities in the Minneapolis/St Paul metropolitan area. Determined negative associations between frequency of family meals and tobacco, alcohol, and marijuana use; low grades; self-esteem; depressive symptoms; and suicide involvement) after controlling for family connectedness ([OR]=0.76-0.93).

 ·         2000 Psychology of Addictive Behaviors (abstract only) Griffen, K. W. et al. Parenting practices as predictors of substance use, delinquency, and aggression among urban minority youth: Moderating effects of family structure and gender Summary; 228 6th grade students, Findings indicated boys and kids from single-parent families engaged in the highest rates of problem behavior. More parental monitoring was associated with less delinquency and less drinking in boys only. Eating family dinners together was associated with less aggression and less delinquency in youth from single-parent families and girls. Unsupervised time at home alone was associated with more smoking for girls.