Complete registration is difficult to obtain. This study investigated the reasons for missing HbA1c measurements.Glycated haemoglobin  of the patients. The main reason stated in 50% of the cases was that the patient was under specialized care.HbA1c measurements. This study provides insight into why HbA1c measurements were not present in the patients' electronic medical record.The general practitioners provided multiple reasons for the missing HbA The guidelines emphasize annual evaluation of micro-vascular complications, as well as cardiovascular risk factors and vascular damage . The ides type 2 .In several countries (e.g. the UK and the Netherlands), GP practices are required to obtain a certain number of measurements and outcomes as guideline-based diabetes care indicators for pay-for-performance purposes -8. AlthoTo improve understanding regarding non-adherence to the guideline-based care, we formulated the following research questions:1c measurement data?1) How complete are HbA2) Which factors can explain missing data?We used a subset of data from the GP registration network of the department of General Practice of the Academic Medical Center-University of Amsterdam (AMC). The network uses routinely recorded data in electronic medical records for research purposes. Diagnoses are coded according to the International Classification of Primary Care (ICPC). Four health centres in south-east Amsterdam participate in this network. At these health centres, 22 GPs and 8 practice nurses provide primary care to 35,700 patients. The four centres belong to the same umbrella organization (GAZO), which signs the pay-for-performance contract with a health insurance company for standard, structured multidisciplinary diabetes care under GP coordination. Since 2007, the registration of diabetes care indicators has been implemented within this network as part of a disease management programme that includes feedback sessions. This registration was implemented in order to enhance efforts to improve the quality of diabetes care and to provide an infrastructure for diabetes-related research. All of the health centres use the same computerized patient electronic medical record system (MIRA). Patients with diagnosed diabetes type 2 are coded ICPC T90.2 in their electronic medical records. Only patients whose were under structural care by the GPs were included in our study.1c blood levels are measured in a blood laboratory. Results of these measurements are forwarded electronically to the patients' electronic medical records.Following regular care, patients visit their health centres every three months for lifestyle consultations, medication evaluations and evaluations of their well-being, and annually for comorbidity screening and therapy planning. A minimum of two weeks before the annual visits, HbA1c was calculated over the year 2007. This 12-month period is in line with the regional pay-for-performance contract. Nineteen of twenty-two practices at the four health centres agreed to participate in this study. The number of measurements was presented to these practices during feedback sessions. After the sessions, each GP was given a form with the numbers referring to patients for whom HbA1c measurements were missing. The GPs were asked to state the main reason for each missing HbA1c measurement.The number of practice-based measurements of the diabetes-care indicator HbAThe stated reasons were collected and grouped into categories by one of the authors (HJB). This grouping was presented to the other authors. Disagreements were resolved through discussion.1c measurements were absent over a 12-month calendar year period. Table 1c measurements, grouped into eight categories. In 50% of the cases, the stated reason is that the patient is under treatment by a specialist (reason 1). Reasons 2 and 3 (both 7%) are inherent to the chosen timeframe of one calendar year. Reason 4 (3%) is caused by the administrative process. Reasons 5 and 6  are patient related. The missing HbA1c measurements attributed to reason 7 (7%) are due to misclassification of the diagnoses of patients with pre-diabetes conditions . Reason 8 (6%) refers to practical problems in performing regular patient monitoring. Reason 9 (6%) comprised 'other' reasons (e.g. dementia or recent registration at the practice). In 3% of the cases, the GP provided no reason. The practices of the non-participating GPs (n = 3) did not have higher rates of missing HbA1c measurements  than did the participating GP practices .In 2007, 1485 patients diagnosed with diabetes type 2 visited the participating GPs (n = 19). For 356 (23.9%) of these patients, HbA1c measurements. The majority of the missing values are due to patients being in specialized care. A true reflection of the well-being of a population calls for a set of measurements that is as complete as possible, regardless of whether the goal is to obtain data for performance indicators or to conduct scientific research.The GPs provided multiple reasons for missing HbA1c measurements were not present in the patients' electronic medical records when calculating the percentage of available measurements over a 12-month period. Several factors underlie the stated reasons for the missing measurements. Evidence emerged to suggest discrepancies in the diagnostic coding of patients with hyperglycaemia or gestational diabetes (reason 7). In some cases, these conditions were registered as diabetes type 2, which prompted the monitoring system to generate reminders to provide these patients with structural screening for diabetes type 2. The practical implementation of a guideline should be well supported by a logistical system for regular patient appointments. In some cases, this system did not work properly (reason 8). Lack of patient compliance with structural care was absent in some cases (reason 5 and 6). In other cases, there were no clear agreements concerning changes in a patient's data (e.g. due to death or relocation) and how these changes should be recorded (reason 4). If the focus of data collection is a 12-month period, as prescribed by the guideline, newly diagnosed patients and patients whose HbA1c measurements were made just outside the 12-month period fall outside the scope of this registration. Also, patients who are under specialized care but not defined as such also fall outside this scope. Due to the use of different electronic medical systems, the health records of patients who are under specialized diabetes care are not uploaded into the GP system. There is currently no way for GP practices or researchers to extract the data that are necessary for monitoring these patients. Because reasons 1 to 4 are currently inevitable, efforts to improve the registration of HbA1c measurements will not be able to increase the percentage to more than 84% of all diabetic type 2 patients registered at GP practices.Our study provides insight into why HbA1c measurements.Since the implementation of the Quality and Outcome Framework in the UK, several studies have been published describing evaluations ,12 that 1c registrations of the non-participating practices did not differ from those of the participating practices. In addition, our results are built on a single cross-section of data concerning a patient population living in a limited geographical area; the south-east Amsterdam. The population in this area comprises patients of various ethnic backgrounds and a high percentage of low-income groups. In 2009, 72% of this population was made up of first or second-generation migrants (i.e. either they or at least one of their parents were not born in the Netherlands) [1c measurements not comparable to corresponding percentages observed in the UK  , whilst erlands) . In 2006erlands) . These c Tahrani ) after t Tahrani ). FinallWe believe that GPs in several countries will recognize the various reasons we have enumerated for missing HbA1c measurements and the existence of barriers to registration. This information will be useful to GPs, not only in their efforts to implement quality procedures related to diabetes, but also as a way of showing insurance companies why it is not always possible to reach the required minimum registration threshold. The limitations we have identified can be used to improve guideline adherence and the quality of indicator registration.The authors declare that they have no competing interests.DGK, HJB, PSK and RCB designed the study. HJB collected and interpreted the data. HJB performed the analysis, in discussion with DGK, PSK and RCB. DGK drafted the manuscript. All authors were involved in the revision and final approval of the manuscript.


Diabetologia, official mouthpiece of the European Association for the Study of Diabetes (EASD), sounded the alarm in a press release regarding a possible association between the use of insulin glargine and an increased risk for the development of certain malignancies compared to human insulin and other insulin analogs.Diabetologia website.Diabetologia sensibly commissioned three additional studies in an effort to reach more clarity on the issue. These studies were done in Sweden,5On 26 June 2009 et al., no distinction was made between the different types of insulin or the effect of insulin dose. The hazard ratio (HR) of colorectal cancer associated with ≥ one year of insulin use was 2.1 (95% CI: 1.2–3.4). The odds ratio of developing colorectal cancer increased by 21% for each incremental year of therapy. This increase in risk is comparable to that of patients with familial colorectal cancer. Since there is no alternative to insulin therapy in patients with type 2 diabetes and failing beta-cell function, the recommendation from Yang et al.. was to assess the cost-effectiveness of a more stringent colorectal cancer-screening programme among patients with type 2 diabetes receiving insulin.The German study followed an earlier retrospective UK study, which showed an increased risk for colorectal cancer in patients with type 2 diabetes receiving chronic insulin treatment.et al. was a retrospective cohort study of 127 031 patients without any known malignancy who exclusively received human insulin or only one type of insulin analogue for the first time. The type of insulin analogue was restricted to the short-acting analogues insulin aspart or lispro and the long-acting analogue, glargine. The mean follow-up time was 1.63 years and the period of interest was between 1 January 2001 and 30 June 2005. During this period, malignant neoplasms were observed in 5 009 patients.The German study1 reported by Hemkens et al. concluded that this issue should be investigated in a properly designed prospective study.A positive association between cancer incidence and insulin dose was found for all insulin types. A dose-dependent increase in cancer risk was found for insulin glargine compared to human insulin in contrast with insulin aspart or lispro. The HR was 1.09 (95% CI: 1.00–1.19) for a daily dose of 10 IU, 1.19 (95% CI: 1.10–1.30) for a daily dose of 30 IU, and 1.31 (95% CI: 1.20–1.42) for a daily dose of 50 IU. The number needed to harm was 100 patients treated for a period of 18 months.et al.In the first of the three commissioned studies, Jonasson et al.In the second of the commissioned studies, Currie Compared to meformin, the adjusted HR for metformin plus sulphonylurea was 1.08 (95% CI: 0.96–1.21), while the HR for sulphonylurea monotherapy was 1.36 (95 CI: 1.19–1.54), and that for insulin-based regimens was 1.42 (95% CI: 1.27–1.60). Insulin therapy compared to metformin increased the risk of colorectal cancer  and pancreatic cancer  but did not increase the risk of breast or prostate cancer. The results for sulphonylureas were similar to those for insulin. In this study, the use of insulin analogues (including glargine) compared to human insulin was not associated with increased risk of cancer.In the third commissioned study,After adjusting for age and gender, those patients who used non-glargine plus glargine insulin compared to those using nonglargine insulin alone had a lower rate of cancer but the difference was not significant. However, those using insulin glargine alone had a higher rate of cancer compared to those patients who used non-glargine insulin. This difference was only of borderline statistical significance and only so for breast cancer. The authors attributed this slight increase in risk for breast cancer associated with insulin glargine to allocation bias.n = 12 852) with definite type 2 diabetes and who received insulin for the first time between January 2002 and 31 December 2005 were investigated. A total of 378 cancers occurred in this group. Overall, the incidence of cancer was no different between the insulin glargine users (regardless of what other type of insulin they used) compared to the users of non-glargine insulin alone. Likewise, the incidence rate of cancer in the glargine-only users was not higher than in users of non-glargine insulin alone. In this cohort, the incidence of breast cancer was not increased in the glargine users compared to the non-glargine users.In the second approach, a group of patients  in those receiving any insulin glargine (regardless of what other insulin they used), compared to the non-glargine insulin users. This HR was even lower in subjects who had had an exposure of at least two years. For breast cancer there was a slight but non-significant increase in incidence in glargine-only users compared to non-glargine insulin users. In this study, the insulin glargine-only users at baseline differed substantially as a group from those using non-glargine plus glargine insulin or those using non-glargine insulin alone. The authors concluded that in spite of shortcomings in their study, the results were reassuring that use of insulin glargine was not associated with an increased incidence of cancer. Although their data do not provide complete reassurance, they do not point to unequivocal evidence of harm either.● The German study found that a patient on insulin glargine was more likely to be diagnosed with cancer than a patient on the same dose of human insulin. This difference was equivalent to one extra case of cancer for every 100 patients taking glargine insulin for one year.● The Swedish study found no increase in risk of cancer in patients taking glargine along with other types of rapid-acting insulin. Women on glargine alone were twice as likely to be diagnosed with breast cancer. This risk was equivalent to one new case of breast cancer for every 1 000 women treated for one year.● The UK study found no increase in risk of any cancer including breast cancer between the four insulin regimens studied. Patients on metformin tablets were less likely to be diagnosed with cancer than patients on other forms of treatment. This was also seen when metformin was taken with other tablets or with insulin.● The Scottish study found a slightly reduced risk of cancer in those patients (who were younger and included patients with type 1 diabetes) who took glargine insulin along with other insulins, compared to those who took only human insulin. The patients who took glargine only (who were older) were more likely to have any form of cancer including breast cancer, although the risk was statistically not significant.● The researchers involved in all four studies agreed that these findings were not conclusive since the studies were observational and not clinical trials. The possibility that differences between groups of people were responsible for the different rates of cancer cannot be excluded. Further studies are needed before a final conclusion can be reached.● Insulin glargine is widely used and was found to be helpful on an individual basis, although clinical trials did not show that it provided better overall glucose control than human insulin in patients with type 2 diabetes. However, some patients with troublesome hypoglycaemia may find it beneficial.● The EASD does not recommend that patients should stop taking insulin glargine on the basis of evidence presented in these trials. Patients do, however, have the option of using long-acting human insulin or a mixture of short- and long-acting human insulin twice a day instead of the once-daily analogue. Especially patients who already have cancer or women with a family history of breast cancer may wish to consider this option.The American Association of Clinical Endocrinologists (AACE) takes a slightly different view from the EASD.The American Diabetes Association (ADA) was even more cryptic in its comments.The EASD, the AACE and the ADA do not suggest the introduction of any cancer screening programme in patients with type 2 diabetes who were exposed to insulin or any form of diabetes therapy over a long period. It is however clear that the relationship between type 2 diabetes, including its therapy, and the risk of cancer, warrants further research. Meanwhile, it may be prudent to emphasise that patients with type 2 diabetes are not only at risk of macro- or microvascular disease but that they have a similar or even increased risk of certain cancers compared with to the non-diabetic population. Patients with type 2 diabetes should at least be offered the standard screening guidelines for commonly occurring cancers.


A genetic component in the susceptibility to multiple sclerosis (MS) has long been known, and the first and major genetic risk factor, the HLA region, was identified in the 1970’s. However, only with the advent of genome-wide association studies in the past five years did the list of risk factors for MS grow from 1 to over 50. In this review, we summarize the search for MS risk genes and the latest results. Comparison with data from other autoimmune and neurological diseases and from animal models indicates parallels and differences between diseases. We discuss how these translate into an improved understanding of disease mechanisms, and address current challenges such as genotype-phenotype correlations, functional mechanisms of risk variants and the missing heritability. Multiple sclerosis (MS) is a common neurological disorder characterized by inflammation, demyelination and axonal loss . The disThe Human Leukocyte Antigen (HLA) region on chromosome 6p21 is characterized by an exceptional degree of polymorphism or genetic variation between individuals in the population. With the use of serology, these were amongst the first polymorphisms that could be studied in the ‘70s. It became quickly evident that the HLA region plays a role in nearly all immune-related disorders, including MS , 10. StrThe linkage strategy, looking for cosegregation of a genomic region with a disease within multiplex families, has proven extremely effective in mapping monogenic forms of neurological diseases. In MS, 20% of patients report a relative with the disease, but families with more than four affected relatives over more than one generation are extremely rare . This li-7 to 5x10-8 are highly indicative of genuine associations that replicate in independent follow-up studies [With decreasing effect size of a risk factor, the number of affected sibling pairs required for linkage studies increases dramatically. If we assume that common variants each with a modest effect on disease risk contribute substantially to common diseases such as MS (‘common disease - common variant’ hypothesis), association studies in large study populations are much more suited than linkage studies . Early c studies , 26.IL2RA) and interleukin-7 receptor (IL7R) [1). Since, additional GWAS published keep the list of risk variants growing [Thirty-five years after the first report on the role of the HLA region in MS, association studies identified the first genetic risk factors for MS outside of the HLA region: variants in the cytokine receptor genes interleukin-2 receptor alpha (r (IL7R) -29. In tr (IL7R) -44. Wherr (IL7R) . This inr (IL7R)   demonstrate that the current set of risk alleles is just the tip of the iceberg likely to include hundreds of variants with modest effects and thousands of variants with very small effects . StudiesGWAS are most powerful in identifying regions of association. These regions are typically 384 kb in size and contain an average of 6 genes (range 0-33) . HoweverGWAS are based on the ‘common disease - common variant’ hypothesis, and effectively screen the vast majority (>80%) of the 10 to 15 million common  variants in the genome . The effTNFRSF1A gene has recently been identified as a risk variant for MS [A common variant in the t for MS , 39, 43.t for MS . One of t for MS . Two stut for MS , but thiCYP27B1. After follow-up in a total of 3564 MS patients and 1873 controls, they suggest association of five rare variants in this gene with MS [As a strategy to identify rare variants, a recent study applied exome sequencing in index patients from 43 multiplex families with at least 4 affected individuals. No rare functional variant was present in more than one family. Subsequently, the authors looked for rare variants in genes already implicated by common MS risk variants and identified three such variants, including one in  with MS . In an a with MS .With an established list of 5 HLA and 57 non-HLA risk factors for MS, we can finally start to consider the picture of pathways emerging and convert lists of variants into an improved understanding of disease mechanisms.-8). Considering the genes nearest to each of the association signals, 30% of these versus 7% of all human genes are annotated in public databases as having an immunological function [1). Often, the same variants are associated in the same direction with several autoimmune diseases and hence appear to influence susceptibility to autoimmunity in general. An example is the B cell specific transcription factor BACH2 in which variants are associated with at least five other autoimmune diseases besides MS: type 1 diabetes [A hypothesis-free investigation of regions implicated by GWAS indicates that these regions are heavily enriched for immunological genes . This may indicate that these key immune system controlling genes, and not other genes within the same region of association, are functional in susceptibility to MS.Common MS risk variants do not only tend to cluster within the same genes with common risk variants for other autoimmune diseases. In several instances, common risk variants implicate genes in which rare mutations are known to cause monogenic immune-related diseases characterized by autoimmunity, autoinflammation or immunodeficiency  for the most likely functional genes near each of the established MS risk variants. This points once again to different particular pathways of the immune system implied by currently known genetic risk factors for MS. Table IL12A, IL12B) and cytokine receptors , co-stimulatory molecules , and signal transducer molecules  [The current state of knowledge of MS genetics hence provides us with new insights into the pathogenesis of the disease and implicates a major role for the immune system, and specifically for lymphocyte differentiation and proliferation. Selected candidate genes within the regions of association implicated by GWAS include cytokines  .MANBA) (OMIM: 248510) and galactosylceramidase (GALC) (OMIM: 245200) lead to lysosomal storage disorders with neurological symptoms or myelination problems, and anti-galactosyl ceramide antibodies are specific for MS [2). Two members of the kinesin family have been implied in the risk of MS. The first, KIF1B, could not be replicated in independent study populations [KIF21B, has an effect in the same direction on the risk of MS as well as other autoimmune diseases such as ankylosing spondylitis [The neurodegenerative component of MS that is apparent in pathological studies is less well reflected in the list of currently known genetic risk factors. None of the risk genes overlap with those for neurodegenerative diseases such as amyotrophic lateral sclerosis, Alzheimer’s disease or Parkinson’s disease. Only a few candidate genes implied by genome-wide association studies have an obvious neurological function. Mutations in β-A-mannosidase  and disease activity (relapse rate and accumulation of disability). Studies indicate that there may be a genetic component in some of these clinical characteristics . In contThere was limited evidence only for factors contributing to differences in age at onset: a higher genetic risk tends to be correlated with an earlier age at onset . For exaClinical heterogeneity may be an endpoint reflecting many different disease processes. Using intermediate measures (endophenotypes) that capture specific biological processes, are at least in part genetically determined and can be measured accurately may hence be more useful. Examples of such endophenotypes are antibody production in the cerebrospinal fluid and magnetic resonance imaging (MRI) based measurements. Relatively small studies of the HLA region have so far suggested that different HLA alleles are associated with oligoclonal band positive or negative MS -85. In oAnother aspect of heterogeneity important to clinical practice is that of response to treatment. First examples of investigations of this trait are discussed below.As described above, currently known risk variants for MS are estimated to account for approximately 25% of the sibling recurrence risk , with anA first possible explanation for this missing or hidden heritability implicates novel sources of genetic risk such as less common and rare variants (see previously), non-SNP risk variants such as structural variants (copy number variants and inversions) and inherited epigenetic variation. It has not been possible to explore these sources of genetic variation systematically and in sufficiently large sample sizes as yet. A second explanation for the missing or hidden heritability is an underestimation of the fraction of the genetic risk that is already explained by currently known variants. First, there are indications that current estimates of familial clustering and heritability may be overestimated, and hence the proportion currently explained underestimated , 88. SecAs in most other complex diseases, the vast majority of risk variants implicated by GWAS are not located in the coding region or correlated with coding variants, but are situated in introns, promoters or intergenic regions . Such va3). For example, tyrosine kinase (Tyk2) knockout (KO) mice showed complete resistance against EAE with no infiltration of CD4+ T cells in the spinal cord and reduced Th1 cells in the periphery. Furthermore, induction of EAE in MOG-primed Tyk2 KO mice by transferring wildtype (WT) Th1 cells suggests that the diminished Th1 response is involved in the mechanism for disease resistance [4). However, extrapolation between the mouse model and human disease and between gene knock-out and more subtle polymorphism is not always possible. The MS susceptibility gene CD58 for example does not have an orthologue in mice. The tumor necrosis factor receptor superfamily member 1A (Tnfrsf1a) KO mouse is resistant to EAE and administration of neutralizing antibodies delayed the onset of disease and clinical symptoms in this animal model [A role for some genes is suggested by data on the effect of knocking out the homologous gene in mice  expression on naive T cells and monocytes, whereas variants that are neutral in MS but associated with type 1 diabetes are correlated with changes in expression on memory T cells [Given the limitations of animal models described above, human material is essential to examine the mechanism of action of genetic risk variants directly in humans. Many studies have demonstrated the appropriateness of the peripheral blood system to capture variation that is of importance for MS . Possibled above . An eleg T cells . StudiesVCAM1 - natalizumab, IL2RA - daclizumab) are implicated by GWAS [TNFRSF1A, the receptor for TNF-α. Variants in this gene are associated with susceptibility to MS and primary biliary cirrhosis but not with other autoimmune diseases [The potential for currently known risk variants as a prediction tool for MS is limited, as in other complex diseases, and is not the aim of genetic studies, as has extensively been discussed elsewhere , 88. Mor by GWAS . A few G by GWAS . A recen by GWAS . An examdiseases , 39, 101diseases . This midiseases , 95 and diseases . It remaThe field of MS genetics has come a long way, with the list of genetic risk factors having doubled over the past year to >50. On the basis of this list a picture is emerging of key immunological genes and pathways being involved in MS susceptibility, with much less representation of common variants in genes with neurological function so far. Current challenges are understanding the functional mechanisms, with a few pioneering studies leading the way. Established risk variants explain only part of the genetic component of MS and the search for the missing heritability goes on with novel tools addressing additional sources of variation that were beyond the reach of systematic investigation so far. The heterogeneity in clinical aspects such as age at onset, disease course and severity remains largely unexplained at the genetic level, with the exception of an effect on age at onset. However, an important aim of genetic studies is translation to novel targets for treatment or optimal treatment choice based on the genetic profile and ‘proof of principle’ examples are hopeful.


A number of aversive and appetitive unconditioned stimuli (such as shock and food) are known to produce memory enhancement when they occur during the post-training period. Post-training exposure to conditioned aversive stimuli has also been shown to enhance memory consolidation processes. The present study shows for the first time that post-training exposure to conditioned stimuli previously paired with consumption of a sucrose solution also enhances memory consolidation. Male Long Evans rats were trained on a one-session conditioned cue preference (CCP) task on a radial arm maze. Immediately or 2 hours after training, rats consumed a sucrose solution or were exposed to cues previously paired with consumption of sucrose or cues previously paired with water. Twenty-four hours later, the rats were tested for a CCP. Immediate, but not delayed, post-training consumption of sucrose enhanced memory for the CCP. Immediate, but not delayed, post-training exposure to cues previously paired with sucrose, but not with water, also enhanced CCP memory. The possibility that rewarding and aversive conditioned stimuli affect memory by a common physiological process is discussed. Events such as electroconvulsive shock8 or anaesthetization10 can weaken a memory; events such as injections of epinephrine13 or amphetamine18 can strengthen a memory. In all such demonstrations, the post-training treatment was given shortly after a learning trial and retention was measured one or more days later. When administration of the same treatments was delayed for one or more hours after training, they were ineffective. This pattern of effects is consistent with the idea that memory consolidation is a time-limited process19 during which the neural representation of the memory is labile and subject to change22.Certain kinds of events that occur during the period immediately after a new task is learned can modulate memory for the task25 and of rewarding events such as electrical self-stimulation of the brain26, and ingestion or injection of sucrose or glucose33 are well-documented. Furthermore, Holahan and White35 found that post-training exposure to conditioned aversive cues previously paired with shock also enhanced memory consolidation. The present study was designed to determine if post-training exposure to rewarding conditioned cues, previously paired with consumption of sucrose, can also enhance consolidation of the memory for a recently acquired task.The memory enhancing effects of post-training aversive events such as footshockSubjects were 36 test naïve, male Long-Evans rats  that weighed 250–275 g (56–58 days old) at the start of the experiment. They were housed in individual cages with free access to water. The temperature (22°C) and lighting (lights on: 0700 to 1900) of the animal housing unit were controlled. Behavioral testing took place from 1000 to 1400. Care of rats and all procedures were conducted in accordance with the guidelines of the Canadian Council on Animal Care and protocols approved by the McGill University Animal Care Committee (protocol number: 1417) as well as the Guide for the Use and Care of Laboratory Animals.Radial-arm maze. The maze was located in a windowless 2.8 × 3.7 × 2.8 m (w × l × h) room partitioned with a sound attenuating divider (1.2 m long) that created a 2.8 × 2.3 m area for the maze. This area contained a number of distal cues. A video camera hung about 1 meter above the maze.2 area at the end of an arm during training. The panels confined a rat’s view of the room to an arc of approximately 180° facing away from the maze.The maze was made of wood painted flat gray and consisted of an octagonal center platform 29.3 cm edge to edge with arms 42.8 cm long and 9 cm wide. Each arm was surrounded by a wall 15.8 cm high at the entrance; 10 cm out from the entrance the wall height decreased to 5 cm. The surface of the maze was 54 cm from the floor of the room. Wooden blocks (30 cm high) also painted flat gray were placed in the entrances of unused arms. Similar blocks with wooden panels attached (28 cm wide) were used to confine a rat to a 35 cmConditioning boxes. This apparatus consisted of a large box made of wood, except the front wall, which was Plexiglas. The box was divided into two compartments of equal size (45 × 45 × 30 cm) by a wooden partition. One of the compartments was painted grey; the other was painted with vertical black and white stripes. The floors in both compartments were made of wood and covered with wood chips. The apparatus was situated in a room across a hallway from the radial arm maze room.Groups of 7–8 rats were habituated to handling daily for 5 days. They were placed into a large plastic box (70 × 54 × 33 cm) with wood chips covering the floor for 2 h per day while the experimenter picked up and held each rat for 5 min. During these 5 days, food was removed from the rats’ home cages. When returned to its home cage after handling, each rat was given 10 Froot Loops  and approximately 5 g of rat chow. At the end of the handling period, all rats weighed 85% ± 3% of their initial free feeding weights. They were maintained at these weights throughout the remainder of the experiment by adjusting the number of pellets given after testing each day. Froot Loops were not given in the home cage after the 5-day handing period.On days 3–5 of the handling period, water was removed from each rat's cage at 17h00 and replaced with a bottle containing 20 ml of a 10% (w/v water) sucrose solution. At 8h00 the next morning the sucrose bottles were removed and replaced with water.36.This experiment compared the effects of immediate and delayed post-training consumption of sucrose on memory for a conditioned cue preference (CCP)35. Placement on the two arms was always done in this order so that exposure to the unpaired arm was last. When a rat was moved between arms, the experimenter lifted the rat off the arm and placed it onto the other arm. The number of Froot Loops remaining in the paired arm was counted at the end of training and subtracted from 30 to provide a measure of consumption.Each rat was randomly assigned to a different pair of food-paired and unpaired arms on the radial maze. Food-paired arms contained 30 Froot Loops; unpaired arms were empty. The two arms assigned to each rat were separated by at least 2 other arms. Rats were confined in their food-paired arms for 5 min and then moved to their unpaired arms for 5 min. This sequence was then repeated once moreEach rat was returned to its home cage when its maze training trials were complete. Rats in the immediate post-training sucrose condition (n=6) were given a 20 ml bottle of 10% sucrose in their home cages and allowed to drink for 20 min. Rats in the delay condition (n=6) were given access to the same solution 2 hrs after being returned to their cages. After the 20 min access period the sucrose bottles were replaced with water bottles for the rats in both groups.24 hours after the post-training treatments, each rat was placed on the center platform of the maze with the food-paired and unpaired arms open and no food in either arm. The entrances to the other arms were blocked. Each rat was allowed to move freely for 20 min and observed on a monitor connected to the TV camera above the maze. The times of entry into and exit from each arm were recorded and used to calculate the total time spent in each arm. An entry into or an exit from an arm was scored when a rat’s shoulders crossed a line separating the arm from the central platform.37, (p. 73) following a two-way ANOVA (group by arm) with one repeated measure. The rats in the immediate post-training sucrose group spent significantly more time in their food-paired than in their unpaired arms  = 5.03, p < 0.05) while the group that drank sucrose 2 hours after maze training spent similar amounts of time in their food-paired and unpaired arms  < 1.0). These results show that immediate, but not delayed; post-training exposure to sucrose had a retroactive enhancing effect on memory consolidation rather than a proactive effect on performance.The results are shown inThis experiment compared the effects of immediate and delayed post-training consumption of sucrose on memory for a conditioned cue preference (CCP).Click here for additional data file.This experiment tested the hypothesis that exposure to sucrose conditioned cues would modulate memory in the same way as consumption of sucrose did in Experiment 1.After the initial handling period, all rats in this experiment were given 3, two-day training trials in the conditioning boxes. On one of the two days of each trial each rat was confined in one of the large compartments for 20 min with the 10% sucrose solution. On the other day, each rat was confined in the other large compartment for 20 min with water. The assignment of sucrose-paired compartments and order of sucrose- and water-pairing were counterbalanced within each experimental group.24 hours after the end of the conditioning trials the rats were trained on the CCP task as described in Experiment 1.After each rat completed maze training, it was placed in the conditioning box for 20 min. Neither the sucrose solution nor water was available in either compartment. Rats in the immediate sucrose-paired (ISP) condition (n=8) were placed in their sucrose-paired compartments immediately after training; rats in the immediate water-paired condition  were placed into their water-paired compartments immediately after training. The rats in the 2-hour delayed sucrose-paired (DSP) condition (n=8) were returned to their home cages for 2 hours with no food or water and were then placed into their sucrose-paired compartments.24 hours after the post-training treatments all rats were tested on the maze as described in Experiment 1.The results are shown inThis experiment tested the hypothesis that exposure to sucrose conditioned cues would modulate memory in the same way as consumption of sucrose did in Experiment 1.Click here for additional data file.Exposure to sucrose or sucrose-conditioned cues immediately after training enhanced retention of information required for expression of a CCP in the radial maze. Increasing the delay between maze training and either post-training treatment to 2 hours eliminated this effect, showing that this is a classic time-dependent memory modulation effect. This appears to be the first demonstration that post-training exposure to appetitive conditioned cues enhances memory consolidation.The enhanced CCP in the immediate groups was not due to learning about the temporal relationship between exposure to the food-paired of unpaired maze arms and any rewarding or conditioned rewarding effects either of the post-training treatments may have had. This is because the rats were always exposed to their unpaired arms immediately before the treatments. Learning that exposure to an arm led to reward would therefore have increased the time spent in the unpaired arm at the expense of time in the food-paired arm. The fact that the rats in the sucrose and ISP groups spent more time on their food-paired than on their unpaired arms shows that this form of learning did not influence the rats' behavior. Moreover, the absence of modulation in the 2 hour delay groups shows that the enhanced CCP for the food-paired arm was due to a retroactive enhancement of memory.27 found that post-training consumption of water failed to modulate memory for a conditioned emotional response in an aversive conditioning situation. If it is true that, unlike consumption of sucrose solutions, consumption of water does not have memory modulating effects, it is not surprising that exposure to conditioned stimuli that have been paired with water also lacks these effects.Immediate post-training exposure to water-paired cues in the IWP group did not have a memory modulation effect. Messier and White38, as does the consumption of sucrose solutions28. Both of these UCSs produce UCRs in the form of salivation39 and glucose or insulin release41, among other responses. Aversive events such as foot shock also modulate memory34 and produce UCRs, including increased heart rate42 and release of stress-related hormones43. When a rat is exposed to a UCS, memory modulation can be seen as resulting from the action of a UCR, either one of those mentioned here, or some other as yet unidentified UCR. These UCRs are subject to conditioning45 so it can be presumed that when they occur as conditioned responses (CRs) after conditioning, they have the same effect as the UCRs.A number of other aversive and appetitive unconditioned stimuli (UCS) are known to produce memory modulation when they occur during the post-training period and each of these is also associated with several well-studied unconditioned responses (UCRs). For example, food (the classic UCS) improves retention when consumed during the post-training period43, elevation in catecholamine levels such as norepinephrine and dopamine50 and activation of the hypothalamic-pituitary-adrenal (HPA) axis53, all of which have been shown to modulate memory (see55). Thus, memory modulation by unconditioned rewarding or aversive events and by rewarding or aversive conditioned stimuli may result from similar internal responses.Interestingly, rewarding and aversive UCSs produce many of the same UCRs and CRs. These include increases in blood glucose I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


Genome-wide association studies (GWAS) have recently identified several new genetic variants associated with obesity. The majority of the variants are within introns or between genes, suggesting they affect gene expression, although it is not clear which of the nearby genes they affect. Understanding the regulation of these genes will be key to determining the role of these variants in the development of obesity and will provide support for a role of these genes in the development of obesity.We examined the expression of 19 GWAS obesity genes in the brain and specifically the hypothalamus, adipose tissue and liver of mice by real-time quantitative PCR. To determine whether these genes are nutritionally regulated, as may be expected for genes affecting obesity, we compared tissues from fasting and non-fasting animals and tissues from mice consuming a high fat high sucrose diet in comparison to standard rodent chow.Bat2 expression was increased ~10-fold in the brain of fed mice but was lower or unchanged in the hypothalamus and adipose tissue. Kctd15 expression was upregulated in the hypothalamus, brain and adipose tissue of fed mice and downregulated by high fat feeding in liver, adipose tissue and the hypothalamus but not the remainder of the brain. Sh2b1 expression in the brain and Faim2 expression in adipose tissue were specifically increased >20-fold in fed mice. Tmem18 expression in adipose tissue but not the brain was reduced 80% by high fat feeding. Few changes in the expression of these genes were observed in liver.We found complex, tissue-dependent patterns of nutritional regulation of most of these genes. For example, These data show nutritional regulation of nearly all these GWAS obesity genes, particularly in the brain and adipose tissue, and provide support for their role in the development of obesity. The complex patterns of nutritional and tissue-dependent regulation also highlight the difficulty that may be encountered in determining how the GWAS genetic variants affect gene expression and consequent obesity risk in humans where access to tissues is constrained. FTO, which have the strongest effects on obesity risk[MC4R, CTNNBL1, NPC1, MAF, PTER, PRL, SH2B1, NEGR1, the SEC16B-RASAL2 region, TMEM18, the SFRS10-ETV5-DGKG region, BDNF, FAIM2, KCTD15, the NCR3AIF1BAT2 region, GNPDA2, and MTCH2[Advances in our understanding of the genetic contribution to obesity have come from recent genome wide association studies (GWAS). GWAS have identified several new genetic variants associated with obesity and its related traits such as body mass index (BMI). Most prominent amongst these are SNPs within ity risk-5. Additity risk. These iand MTCH2.MC4R, mutations are the most common cause of monogenic severe obesity and missense variants within the gene have been associated with altered risk for common obesity[BDNF, regulates feeding, its expression is altered by consumption of high fat diet, and variants within the gene have previously been associated with obesity[Sh2b1 knockouts are obese, and this gene is known to play important roles in leptin signalling[Alterations in a few of these genes have previously been shown to affect body weight-16. Mela obesity. Brain d obesity,14,16,18gnalling,19. UndeFTO was shown to be regulated by feeding and fasting in the hypothalamus[The SNPs identified by the GWAS generally do not affect the amino acid sequence of the mature protein. They are typically intronic or intergenic. The location of these SNPs suggests they likely affect the regulation of the gene they are located within or of nearby genes, and in some cases it is not clear which of the nearby genes they may be affecting,8,11,20.thalamus. Thus weKnowledge of the regulation of the GWAS obesity genes is critical for understanding how the associated SNPs alter the function of their cognate genes and thus how these genes may affect the development of obesity. This requires knowledge of the tissues where the gene is normally expressed and an understanding of the physiological processes that regulate it. We sought to determine whether metabolic factors affect the regulation of the newly discovered obesity genes. We examined the regulation of these genes by feeding/fasting status and by the consumption of a diet high in fat and sugar. Here we show that most of the recently identified obesity genes are regulated by dietary status, providing support for their role in processes relevant to the development of obesity. These patterns of regulation were often tissue-dependent and largely unique for each gene, suggesting that many of these genes affect distinct pathways in the development of obesity and that analysis of the effects of the GWAS SNPs on gene expression may need to be performed in all physiologically relevant tissues and under multiple physiological contexts.2 asphyxiation at 8 weeks of age. Tissues were rapidly dissected and immediately placed in liquid nitrogen then stored at −80°C. Prior to sacrifice, animals were either fasted 4 hours (9 am – 1 pm) or dissections were performed at 9 am without prior removal of food (“fed”). All procedures were approved by the UBC Committee on Animal Care and were performed according to Canadian Council on Animal Care guidelines.Animals were housed in an environmentally controlled facility with 14 hour light cycles (7 am – 9 pm). Female C57BL/6 J mice were given free access to water and either a standard rodent chow  or a diet containing 60% calories from fat (primarily lard) and 20% calories from sugar  from weaning. This high fat diet has a cholesterol content of 300.8 mg/kg from the lard. The mice were sacrificed by COPrior to extraction, tissue samples were cut into small pieces and placed in RNA Later Ice  at −20°C for at least 24 hrs. RNA was extracted using a commercially available kit . The integrity of the RNA was verified by performing formaldehyde denaturing agarose gel electrophoresis for all samples except the hypothalamus, for which too little RNA was obtained. Following DNAse I digestion  to remove any contaminating genomic DNA, cDNA synthesis  was performed using 1 μg of RNA with mixed oligo-dT and hexamer primers  according to the manufacturer’s directions. RNA was subsequently removed with RNase H digestion . Successful cDNA synthesis was verified by PCR amplification of our control genes and visualization of a band of the appropriate size on an agarose gel.Aif1, Bat2, C10orf97, Ctnnbl1, Dgkg, Etv5, Faim2, Gnpda2, Kctd15, Maf, Mtch2, Negr1, Npc1, Pter, Rasal2, Sec16b, Sfrs10, Sh2b1, and Tmem18. Primer sequences are provided in Additional filehttp://www.genome.ucsc.edu), we designed the primers in regions common to all isoforms. All primer pairs spanned an intron. Ncr3 is a pseudogene in mice. It does not encode a functional protein due to the presence of premature stop codons[We examined the dietary regulation of p codons and was Relative gene expression was measured using a StepOne Plus real time thermocycler , using SYBR green I for detection . Forty cycles of amplification were performed followed by melt-curve analysis for verification that only a single product was amplified from each sample. This verification was also performed by direct visualization of PCR amplification products on an agarose gel. Baseline correction, threshold setting, and calculation of the Ct value were performed automatically by the StepOne software .Ppib) was chosen as the reference gene, as it proved most robust to changes in expression by experimental condition across each of the tissues in comparison to beta-actin (Actb), Gapdh, and Arbp. This control gene was included on several plates contemporaneous with the genes being assessed, and for each sample the average value of this gene across its multiple replicates was used for normalization of that sample. Delta Ct (ΔCt) values were calculated by subtracting the cycle threshold (Ct) value for each gene from this average value. Delta delta Ct (ΔΔCt) values were calculated for each sample by subtracting its ΔCt value from the average ΔCt for the chow-fed, fasted controls in the same experiment. Initially, single measurements were made for each sample (n = 5 per dietary group). When there was a potential difference between groups, replicate experiments were performed, including additional samples . The numbers vary for each tissue and gene because of poor-quality or low yields of RNA obtained from some samples and the number of samples with sufficient RNA available at the time for analysis. For each sample, the average ΔΔCt of all its replicates across experiments was used for statistical analysis.Cyclophilin ; chow-fed mice not fasted prior to tissue collection, “fed”; and high fat diet-fed mice that were fasted prior to tissue collection. The average ΔΔCt values of the high fat-fed and fed groups were compared to that of the fasted chow-fed control group and the significance of each assessed by a non-parametric Mann–Whitney U test because of the small sample size. Because this results in two comparisons for each gene , the resulting P-values were subsequently Bonferroni corrected by multiplying them by 2. This approach was chosen over a Kruskal-Wallis test because the comparison between chow-fed “fed” mice and fasted high fat diet-fed mice that is accounted for in the Kruskal-Wallis test is not meaningful. The average fold change for each group shown in the figures was calculated as 2 ± its SE.Kctd15 and likely Mtch2, were regulated by both conditions. The expression of many genes was increased in non-fasted animals. Kctd15 expression was increased 2.1-fold in fed animals, C10orf97 expression was increased 2.3-fold, and expression of Sfrs10 was also increased an average of 2.2-fold. The expression of Pter was increased 1.6-fold, and we detected a 1.8-fold increase in Gnpda2 expression. In addition, Ctnnbl1 expression was increased an average of 1.5-fold, although this did not reach statistical significance. Similarly, the expression of Mtch2, Faim2 and Dgkg were also increased in the fed mice compared to fasted, however due to the large variability in expression levels, these were not significant.All 19 of the GWAS genes we examined were expressed in the hypothalamus. Many were regulated by either feeding/fasting or by consumption of the high fat diet . Bat2 and Sh2b1 mRNA levels were decreased ~10-fold in animals fed the high fat diet. Npc1 gene expression was decreased by ~4-fold. Maf expression was ~3-fold lower, but due to the high variability in the control group did not quite statistical significance after Bonferroni correction. Expression of Etv5 and Negr1 was only 15% and 19%, respectively, of that observed in controls, although neither reached statistical significance. Mtch2 was the only gene that had increased expression with high fat feeding in the hypothalamus. We did not observe any significant changes in hypothalamic gene expression with feeding or consumption of a high fat diet for Aif1, Dgkg, Faim2, Rasal2, Sec16b or Tmem18 (not shown).In contrast to the small differences in gene expression observed in fed compared to fasted animals, chronic feeding of a high fat diet resulted in substantial changes in expression Figure. Kctd15 Kctd15 and Sh2b1 were increased >20-fold, and expression levels of Bat2, Etv5, Negr1and Tmem18 were increased ~10-fold in the fed group. Changes in Kctd15 expression likely did not reach statistical significance due to a large variability in the increase in expression. While the magnitude was variable, most samples had at least 15-fold increased Kctd15 expression. Feeding was also associated with a 2 to 4 fold increase in the expression of Sec16b, Rasal2, and Npc1. We observed similar trends in the expression of Maf that did not reach statistical significance.Many regions of the brain outside the hypothalamus are also important for the regulation of food intake and energy balance. We deteFaim2 was reduced ~50% in the high fat-fed group compared to the chow-fed mice .In marked contrast to what was observed in the hypothalamus where several genes were substantially downregulated by high fat feeding, the expression of only a single gene in the remainder of the brain was altered by high fat feeding. Expression of Negr1 in the high fat-fed mice compared to the chow-fed controls. Etv5 and Kctd15 were also markedly downregulated in mice consuming the high fat diet . Decreased expression of Maf, Npc1, Rasal2, Sec16b, Sh2b1, and Tmem18 in high fat diet-fed mice ranged from ~2.5-fold for Npc1 to 6-fold for Rasal2. We observed a similar decrease in Bat2 expression with high fat feeding (3-fold), although this did not reach statistical significance. In contrast, Aif1 had a small but significant increase in gene expression in adipose tissue of the mice fed a high fat diet (2.1-fold).All the GWAS genes we assessed were also expressed in white adipose tissue. Several GWAS obesity genes were highly differentially regulated in adipose tissue from high fat-fed compared to chow-fed mice. Many genes had reduced expression in high fat diet-fed mice Figure. Most stFaim2 was upregulated a remarkable 20-fold in fed versus fasted mice consuming normal chow , but these were not significant. We did not detect any significant differences in gene expression for Dgkg, Ctnnbl1, Sfrs10, Bat2, Pter, Gnpda2, or C10orf97 in either group.We found the expression of three genes changed significantly by feeding status in adipose tissue. w Figure. ExpressFaim2 and Negr1 were expressed in the liver. In contrast to the tissues above, we observed few differences in gene expression in the liver  likely due to the variability of the controls. Rasal2 expression was decreased an average 3.4-fold in the high fat diet-fed mice. Expression of Gnpda2 was decreased 2-fold in the high fat-fed mice, and by a similar amount in fed animals compared to fasted. Similarly, Npc1 expression was decreased an average 2.6-fold in fed animals compared with fasted. Interestingly, expression of Dgkg was low but detectable in both groups of chow-fed mice, whereas expression could not be detected in five of six high fat diet-fed mice. No differences were observed in the expression of the other genes expressed in liver  in response to fed status or consumption of the high fat diet.Of the 19 genes we assessed, all except r Figure. ExpressGWAS have identified many new SNPs associated with the development of obesity. Most of these SNPs are located in introns or intergenic regions, suggesting they affect the regulation of the corresponding gene or nearby gene(s), but which gene or genes they affect is unknown. Little is known about most of these genes or how they may affect the development of obesity, but understanding their regulation is a key step that may provide important clues. Many genes involved in metabolism and maintaining energy balance are regulated in response to feeding and fasting or by dietary components. Identification of such regulatory patterns would provide support for a potential role in the development of obesity. To begin to understand the regulation of the GWAS obesity genes and if they are nutritionally regulated we examined how changes in dietary conditions affect their expression.Dgkg), did not significantly change under any condition tested. However, given the role of this kinase in second messenger signalling, it is likely that it may not be physiologically regulated at the level of transcription but rather by activity of the enzyme. Note that this does not preclude the possibility that the GWAS SNPs may affect its basal transcription levels. The regulation of some genes was highly tissue specific. Four transcripts, Sfrs10, C10orf97, Pter, and Ctnnbl1 were increased in hypothalami of fed animals compared to fasted, but were not changed by this condition in other regions of the brain, liver or adipose tissue, or by high fat feeding in any tissue. Thus these genes may have unique functions in the hypothalamus regulating energy balance and the development of obesity. Similarly, Aif1  expression was increased by high fat feeding only in adipose tissue, whereas no differences in its expression were observed in the other tissues or in fed animals. It is unclear whether this reflects increased inflammation of adipose tissue in the high fat-fed mice (e.g. expression from increased amounts of inflammatory cells in the tissue), or whether this suggests that the role of Aif1 in obesity may be mediated via specific actions in adipose tissue.We observed complex, tissue-dependent regulation of most of these new obesity genes. Only one gene, diacylglceryol kinase gamma  and decreased by high fat diet consumption in hypothalamus, adipose tissue and liver (but not brain). A recent study has also found decreased Kctd15 expression in hypothalamus and adipose tissue of high fat-fed rats, although they did not observe reduced expression in liver[In contrast to the above genes whose expression was affected by a single condition in a single tissue, the expression of other genes was more complex and altered in multiple tissues or by both conditions. fed rats. Severalin liver.Kctd15 was increased >20-fold in the brain of fed animals, but only by 2- to 4-fold in the hypothalamus and adipose tissue. These complex and tissue-dependent patterns of regulation in response to nutritional status suggest that these genes have important and perhaps distinct roles in several tissues.We also observed a large range in the magnitude of the changes in gene expression, and for each transcript the magnitude of the change in expression was not the same in each tissue. For example, expression of Npc1 and Gnpda2 in liver, FigureFaim2) was regulated by high fat feeding in the brain. Interestingly, however, there was little overlap in the genes regulated by feeding between the hypothalamus and the remainder of the brain, suggesting that distinct nutrient-responsive regulatory pathways operate in various regions of the brain. In contrast, consumption of a high fat diet was associated with a reduction in expression of all of the regulated transcripts with the exception of Mtch2 in hypothalamus and Aif1 in adipose tissue. High fat diet consumption affected gene expression mainly in adipose tissue and the hypothalamus but not the rest of the brain, suggesting energy storage and homeostatic regulation of energy balance may be preferentially affected by today’s obesogenic diets. This also suggests that high fat diets may predominantly down-regulate pathways important for normal adipose tissue function. Previous studies have shown reduced adipogenic gene expression in obese individuals[Although each gene showed distinct patterns and magnitude of regulation across tissues and nutritional conditions, we observed striking consistency in the overall pattern of regulation by feeding and chronic high fat diet consumption. With few exceptions . A recent study examining the expression of a partially-overlapping subset of GWAS obesity genes also found modest changes in expression of only a few genes in liver and muscle[Our findings further suggest that the effects of these genes on the development of obesity may occur in tissues in addition to the brain, which was previously suggested to be their likely site of action,11. Consnetworks. Mtch2 eividuals and has ividuals, althougividuals, very fed muscle.The nutritional regulation of these new obesity genes provides support for their potential role in the regulation of energy balance. These data have several important implications for studies examining the effects of the GWAS SNPs on gene regulation and ultimately the mechanisms by which these genes affect the development of obesity. The highly tissue-dependent patterns of regulation suggest that all tissues where a gene is expressed will need to be examined to determine whether the particular SNPs identified by the GWAS affect the expression of a gene. This is further highlighted by the complex patterns and variability in magnitude of expression changes for a transcript in different tissues. Analysis of the effects of the GWAS SNPs on gene expression in lymphocytes has been suggested since this is a readily accessible source of RNA, and differences in lymphocyte gene expression between lean and obese individuals have been detected. This maTranscriptional regulatory elements can be located before, within, or even following a gene, and can be located at substantial distance (up to 1 Mb) from the gene. Thus itSEC16BRASAL2, SFRS10ETV5DGKG, and NCR3AIF1BAT2. We examined the expression of the genes in each cluster with the hope of discovering regulatory patterns that may point to the more likely causative gene in each cluster. Unfortunately these studies provide little support favoring one of the genes over the other(s). All the genes were expressed in tissues relevant to the regulation of body weight. For the first cluster, both Sec16b and Rasal2 were increased in the fed state in the brain and decreased by high fat feeding in adipose tissue. Neither was altered in the hypothalamus, while Rasal2 expression was also decreased in response to high fat feeding in the liver. The similar expression patterns make it difficult to prioritize one over the other as likely being the causative gene and also suggest that there may in fact be common regulatory elements affecting multiple genes in the region. The genes in the second and third clusters showed very different expression patterns from each other. In the second cluster, Sfrs10 expression was increased in the hypothalamus in fed mice but did not change in any of the other tissues. Etv5 expression in the hypothalamus was decreased by high fat feeding and its expression increased in the brain and adipose tissue of fed animals. Dgkg expression, although relatively high in the hypothalamus and remainder of the brain, was not affected by fasting or the consumption of a high fat diet. For the third cluster, differential expression of Aif1 was detected in adipose tissue, where it was the only gene to increase in response to a high fat diet. In contrast, Bat2 expression was decreased by the high fat diet in hypothalamus, increased by feeding in brain, and was not changed in liver or adipose tissue. The expression of the Ncr3 pseudogene was not analyzed. Thus each member of the last two groups has a differential regulation in response to changing dietary conditions, which suggests that the causative variant(s) at these loci may affect just one of the genes rather than the coordinate regulation of multiple genes. However, for each cluster all the genes had potentially relevant changes in expression and it is unclear which of the genes is most likely to be affected by the GWAS SNP based on these analyses.Three of the obesity SNPs identified by Thorliefsson and colleagues were fouTmem18 is expressed in most neurons[Tmem18 expression in response to chronic consumption of a high fat-sucrose diet. In contrast, however, we found ~8-fold higher levels of Tmem18 in the brain of non-fasted animals (FigureEtv5 and Sh2b1 in the hypothalamus and Kctd15 in the hypothalamus and adipose tissue of high fat-fed animals[Kctd15 and Gnpda2 in the hypothalamus and Tmem18 in the liver, hypothalamus and soleus muscle, and increased expression of Mtch2 in adipose tissue and Pter in adipose tissue and liver of high fat-fed rats, which we did not observe[. The reasons for these discrepancies may relate to experimental design, such as differences in the species and strain studied; the diet used and its duration; the time of day of sacrifice; and the fasting conditions used, and require further investigation.Recently other studies have reported expression patterns of some of these genes. One of these has shown that  neurons. These s neurons. Consists Figure. A recen animals. In cont observe. The reaThese studies have shown that the regulation of these new GWAS obesity genes in response to dietary conditions is complex and often tissue-dependent. Knowledge of the regulation of these genes will help in determining their role in obesity. These data provide supportive evidence for a role of these genes in the regulation of energy metabolism, but suggest that discovery of the mechanism by which the regulatory SNPs identified in the GWAS affect these genes will require tissue and context specific analysis.Aif1: Allograft inflammatory factor 1; BMI: Body mass index; Ctnnbl1: Catenin, beta-like 1; C10orf97: Chromosome 10 open reading frame 97 a; Fam188a: Which is now known as Family with sequence similarity 188 member A; Ct: Cycle threshold; Dgkg: Diacylglycerol kinase gamma; Etv5: Ets variant 5; Faim2: Fas apoptotic inhibitory molecule 2; GWAS: Genome-wide association study; Gnpda2: Glucosamine 6 phosphate deaminase 2; HFD: High fat diet; Bat2: HLA-B associated transcript 2; Mb: Million base pairs; Mtch2: Mitochondrial carrier homolog 2; Negr1: Neuronal growth regulator 1; Npc1: Niemann Pick type C1; Pter: Phosphotriesterase related; Kctd15: Potassium channel tetramerisation domain containing 15; Rasal2: Ras protein activator like 2; Sec16b: SEC16 homolog b from S. cerevisiae; SNP: Single nucleotide polymorphism; qPCR: Real-time quantitative reverse transcription PCR; Tra2b originally named Sfrs10: Transformer 2 beta homolog; Sh2b1: Sh2b adaptor protein 1; Tmem18: Transmembrane protein 18; Maf: v-maf musculoaponeurotic fibrosarcoma oncogene homolog.The authors confirm that they have no competing interests to disclose.PY, SK and MMH conducted the study and participated in writing the manuscript. SMC designed the study, analyzed and interpreted the results and wrote the manuscript. All authors read and approved the final manuscript.Table S1. Primer sequences used in these studies.Click here for file


Intra-arterial (IA) chemotherapy has more risks of procedural complications in neonates and young infants. For these reasons, we have developed a strategy of bridge intravenous single agent chemotherapy to postpone IA chemotherapy in these childrenNeonates and young infants with retinoblastoma who required chemotherapy were treated with systemic carboplatin chemotherapy (18.7 mg/kg IV every 3–4 weeks) until they reached the age of 3 months and a weight of 6 Kg. If necessary, IA chemotherapy was subsequently performed at 4 weeks intervals. Efficacy was judged by tumor regression on ophthalmological examination. Retinal toxicity was judged by electroretinography.Eleven children (19 eyes) were treated. All patients are alive and no patient has developed metastatic disease or second malignancies . Intravenous carboplatin  combined with cryotherapy and laser was given to all children. This was effective for five eyes, which did not require IA chemotherapy. IA chemotherapy was administered to 14 eyes . No radiation therapy was required. The Kaplan Meier estimate of ocular radiation-free survival was 94.7% at one year . One eye was enucleated due to tumor progression. ERG showed no deterioration of retinal function.Bridge IV-IA chemotherapy was feasible and safe, and is a promising strategy to treat retinoblastoma in neonates and young infants. In neonates and young infants, retinoblastomas are often bilateral, multiple and occur most often in the posterior pole (in or near the macula), where preserving central vision is especially challenging The institutional review board of Weill Cornell Medical College has approved this study. Written informed consent was obtained from the parents, carers or guardians on the behalf of all the children involved in this study. Following a (previously reported) case of failed catheterization of the ophthalmic artery in a one month-old infant Each ophthalmic examination was performed (every 3–4 weeks) under general anesthesia and included indirect ophthalmoscopy, fundus photography, ophthalmic ultrasonography, and electroretinography as a surrogate for measurement of visual acuity in these very young children Once the child had reached 3 months of age and a weight of 6 kg, IA chemotherapy was considered and was performed if tumor regression was insufficient and if we judged that continuing intravenous chemotherapy with local treatments would not be curative. In such cases, IA chemotherapy was performed on the affected eye(s) every 4 weeks, usually the day following ophthalmic examination under anesthesia.We have previously described the technique and results of IA chemotherapy in detail Three chemotherapy drugs were used: melphalan, topotecan, and carboplatin. Melphalan was the drug of first choice, at an ocular dose of 2.5 mg in 6–7 Kg and 3 mg in >7 Kg infants. Melphalan may induce neutropenia when given at a dose exceeding 0.4 mg/kg of body weight, which is why a dose of 2.5 to 3 mg per eye cannot not be given during the same procedure to both eyes in infants . Carboplatin, ocular dose 25–30 mg, was given as an alternative to melphalan when both eyes needed IA chemotherapy at the same time, or was added to melphalan in case of insufficient tumor regression in unilateral treatments. Topotecan, ocular dose ranging from 0.3 to 0.5 mg, was not used alone but given in addition to melphalan and/or carboplatin.From a prospective database of all retinoblastoma patients seen in our center, we selected the cases referred to us in the first 3 months of life and in whom we decided to use bridge IV-IA chemotherapy. We included one foreign patient who had intravenous chemotherapy performed according to our bridge protocol close to home. We did not include patients referred to us after having failed therapies elsewhere.From August 2008 till October 2011 we treated 11 children (19 eyes) with the bridge IV-IA technique. There were 5 females and 6 males. Retinoblastoma was diagnosed before 3 months in ten patients and at 4 months in one; this last child was treated with the bridge technique because her weight was less than 6 kg. Retinoblastoma was bilateral in nine patients and unilateral in two. Four of the 11 children had a positive family history including one of the unilateral cases. The 19 eyes were classified in the Reese-Ellsworth classification Group I-III in 10, Group IV in 2 and Group V in 7; in the International Classification of Retinoblastoma they were classified Group A in 2, B in 7, C in 3, D in 5, and E in 2. Each patient had at least one Group B or worse eye necessitating chemotherapy.One eye (Patient #11) was enucleated at diagnosis (prior to chemotherapy) in a child with bilateral retinoblastoma for chemosis and proptosis, and is not included in the analysis. One eye (Patient #1) was enucleated due to failed catheterization and progression of disease.Intravenous chemotherapy: the 11 patients (19 eyes) received a median of 2 cycles of carboplatin (range 1 to 5 cycles) at a dose of 18.7 mg/kg delivered every 3–4 weeks.rd IA chemotherapy procedure we blocked permanently the middle meningeal artery, so that all drug injected into the ophthalmic artery would stay intra-ocular; unfortunately, after embolization the ophthalmic artery shrunk so much to adapt to the newly reduced flow conditions that we were unable to catheterize the reduced ophthalmic artery during the fourth procedure; the eye was enucleated.IA chemotherapy was performed in 14 eyes of 11 patients , median 3.5 cycles per eye (range 1 to 6), and 4 cycles per patient (range 1 to 6). There were 51 IA attempts at chemotherapy infusions, 50 (98%) were successful: 38 were performed using the ophthalmic artery (OA), 6 the middle meningeal artery (MMA), and 6 using temporary balloon occlusion of the internal carotid artery . The only catheterization failure was the fourth procedure in patient #1. During the first three procedures, the ophthalmic artery was large because of an anatomical variant . This eye had multiple vitreous seeds that were not responding well to IA chemotherapy, and we attributed the lack of response to the diversion of the chemotherapy drug in the middle meningeal artery. To compensate for this, during the 3The 50 successful IA infusions were performed with melphalan only in 24 cases, carboplatin only in 5, melphalan plus topotecan in 10, carboplatin plus topotecan in 6, melphalan plus carboplatin plus topotecan in 5.Complications of intravenous carboplatin: Of the 28 cycles, there were 12 episodes of Grade 3 and 4 episodes of Grade 4 toxicity. One patient required an injection of granulocyte colony-stimulating factor, no patient required a blood product transfusion.Complications of IA chemotherapy: Procedural complications included one allergic reaction to iodine contrast that was prevented during subsequent procedures with standard premedication; one mild bronchospasm during the catheterization of the internal carotid artery; one transient pulse loss on the side of the femoral puncture that was treated with further heparinization until the pulses re-appeared after 3 hours (this child was admitted overnight). Hematologic toxicity consisted of four episodes of Grade 4 neutropenia , four episodes of Grade 3 neutropenia, one Grade 3 anemia (one patient received a red blood cell transfusion) and one Grade 3 thrombocytopenia. Ocular complications were all transient and included transient loss of the medial eyelashes in one case, ptosis in one, and frontal erythema in the cutaneous distribution of the ophthalmic artery in three .All patients are alive and none have developed extra-ocular disease or a second cancer at a mean follow-up of 27 months from diagnosis (range 9–46 months). All 11 patients (19 eyes) have completed the bridge IV-IA chemotherapy protocol. Results are detailed in ERGs were measured during the first EUA before any treatment, during and after treatment. ERG results are detailed in We found that bridge IV-IA chemotherapy was feasible and safe, and is a promising strategy to treat retinoblastoma in neonates and young infants. Although most (18/19) eyes were preserved, longer follow-up is necessary because recurrences and appearance of new tumors are common in young children. Furthermore, patients 10 and 11 have short follow-up after last treatment. So far, no patient has received external beam radiation therapy, and at least one eye was preserved in all children with bilateral retinoblastoma. Using ERG as a surrogate for visual potential, 14 of the 19 preserved eyes have good vision potential (75.1 µV or greater). In the first patient, the fourth catheterization through the ophthalmic artery failed, resulting in tumor growth and enucleation. This was early in our experience, and if this eye were treated now, we would have used the alternate technique with transient balloon occlusion of the internal carotid artery to perform more IA chemotherapy, and maybe we would have been able to save this eye also.Our small patient group is representative of early-diagnosed retinoblastoma: at presentation, 10/20 eyes were classified as Group I–III in the Reese-Ellsworth classification, while the other 10 eyes had advanced tumors classified as Group IV–V, confirming that “detection at early age does not guarantee early stage” Preserving vision is especially challenging in early-diagnosed retinoblastoma: the tumors are often in a posterior location -close to the optic disc and the macula- where extensive local treatments such as cryotherapy, laser or radioactive plaque would permanently compromise vision We think that IA chemotherapy greatly improves the treatment of retinoblastoma, but we have hesitated to treat the youngest children, as IA chemotherapy is an invasive technique that requires repeated placements of an arterial sheath in the femoral artery and catheterizations of the ophthalmic artery. Our direct microcatheterization technique, which consists of advancing the microcatheter from the femoral sheath to the ophthalmic artery without the help of a larger intermediary catheter, allows for reduction in the size of the femoral access sheath to 1.3 mm diameter instead of the usual 2.5 mm. Still, in neonates and young infants, where these arteries are just slightly larger than the catheters, catheterization might not be successful or may result in complications, such as arterial thrombosis or dissection. Vasospasm might also be an issue, although it is usually enough to wait for its resolution before pursuing catheterization; on the contrary, atherosclerosis, the largest cause of neurological complication in adults due to emboli from atherosclerotic plaques, is not an issue in young children. Finally, the current drug of choice for IA chemotherapy  may induce significant neutropenia when given at a dose higher than 0.4 mg/kg For the intravenous component of the bridge therapy, we have used single agent carboplatin rather than multi-agent chemotherapy (as other centers might have used) because it was intended to act as a bridge to IA chemotherapy and was not aimed to be curative. Our previous experience with single-agent carboplatin had shown that, although it appeared to be associated with inferior ocular event-free survival than tri-therapy together with vincristine and etoposide, the response rate was comparable and it was generally well tolerated For the intra-arterial component of the bridge therapy, we used the drugs and dosage previously described by our group In conclusion, although these results are preliminary and more follow-up is needed, bridge IV-IA chemotherapy seems to potentiate the advantages and decrease the disadvantages of both intravenous and IA chemotherapy in the youngest children with retinoblastoma: initial single agent intravenous chemotherapy acts to bridge the time from diagnosis to when threshold criteria are met for IA chemotherapy. It allows for the initiation of treatment while invasive IA chemotherapy is postponed, and avoids the potential toxicity of multi-agent chemotherapy. Then, and if necessary, the more effective IA chemotherapy can be performed more easily and safely when the child is older and bigger.


Mounting evidence suggests a link between low zinc levels and depression. There is, however, little knowledge about zinc levels in older persons with other psychiatric diagnoses. Therefore, we explore the zinc status of elderly patients suffering from a wide range of psychiatric disorders.Clinical data and blood samples for zinc analyzes were collected from 100 psychogeriatric patients over 64 of age. Psychiatric and cognitive symptoms were assessed using the Montgomery and Aasberg Depression Rating Scale, the Cornell Scale for Depression in Dementia, the Mini-Mental State Examination, the Clockdrawing Test, clinical interviews and a review of medical records. In addition, a diagnostic interview was conducted using the Mini International Neuropsychiatric Interview instrument. The prevalence of zinc deficiency in patients with depression was compared with the prevalence in patients without depression, and the prevalence in a control group of 882 older persons sampled from a population study.2 = 44.81, df = 1, p<0.001). In a logistic model with relevant predictors, zinc deficiency was positively associated with gender and with serum albumin level. The prevalence of zinc deficiency in the patient group was significantly higher in patients without depression (i.e. with other diagnoses) than in patients with depression as a main diagnosis or comorbid depression .There was a significant difference in zinc deficiency prevalence between the control group (14.4%) and the patient group (41.0%) (χZinc deficiency is quite common among psychogeriatric patients and appears to be even more prominent in patients suffering from other psychiatric disorders than depression.This study does not provide a clear answer as to whether the observed differences represent a causal relationship between zinc deficiency and psychiatric symptoms. The blood sample collection time points varied in both the control group and the patient group. No data regarding zinc supplementation were collected. Zinc is a trace element that is essential for the optimal function of the human body, especially the brain. The highest concentrations of zinc in the brain are found in the hippocampus and amygdala regions Important sources of zinc include meat and fresh fish Several studies have revealed a connection between low plasma zinc levels and depression Several randomised controlled trials (RCT) have been conducted to explore the impact of zinc supplementation on depressive symptoms. Two trials have examined zinc supplementation as an adjunct to antidepressant drug treatment in patients with clinical depression. In a study by Nowac et al., 14 patients received an antidepressant and either placebo or zinc supplementation. Zinc supplementation significantly reduced scores on the Beck Depression Inventory (BDI) and the Hamilton Depression Rating Scale (HADRS) after 6 and 12 week of supplementation compared with placebo treatment Most studies of zinc deficiency have focused on depression. However, zinc has also been linked to a possible role in the pathogenesis of Alzheimer's disease (AD), but a causal role in AD has not yet been demonstrated Moreover, to our knowledge, no studies have compared the zinc status of a psychogeriatric population (exhibiting a broad range of psychiatric disorders) with that of healthy controls. It is important to examine whether zinc deficiency is common elderly patients with diagnoses other than depression. A better knowledge of zinc status in the elderly is important beyond the possible association between low zinc levels and psychiatric disorders. Low zinc levels are also associated with poor wound healing and an impaired immune response The aims of this investigation were 1) to compare the prevalence of zinc deficiency in patients referred to a psychogeriatric department and in a control group and 2) to compare the prevalence of zinc deficiency in patients with depression and in patients with other psychiatric diagnoses.Patients older than 64 years who were referred to a psychiatric hospital in the northern part of Norway during the study period of March 2010 to December 2011 were eligible for inclusion in the study. The hospital covers a population of 255,000. We excluded patients with ongoing infections or who were not able to communicate due to their medical condition . In total 107 patients were asked to participate in the study, and five patients refused to participate. Two patients were excluded due to ongoing physical illness (infection). The participants were diagnosed using the structured Mini International Neuropsychiatric Interview (MINI+) th Tromsø Survey, 2007–2008). We restricted the analysis to participants older than 64 years. In total, 4017 men and women in this age group participated in the study, resulting in an overall participation rate of 66%. Non-fasting blood samples were drawn, and serum from all participants was frozen. Serum zinc and albumin from a random selection of 882 individuals were later analyzed and used for further comparison with the patient group.The control group included persons who were recruited from a population-based health study in Tromsø, a town with 70,000 inhabitants in northern Norway .In the patient group, blood samples were collected in the morning (before 10 AM). However, due to other considerations, 64% of the samples were collected after patients fasted overnight and 36% of the samples were collected under non-fasting conditions. In the control group, all samples were collected under non-fasting conditions between 8 AM and 12 AM. The International Zinc Nutrition Consultative Group (IZiNCG) p-value <0.05 was accepted as statistically significant.For the statistical analysis, SPSS 20  was used. Descriptive analyses were conducted to describe the characteristics of the sample, and the Kolmogorov-Smirnov test was used to examine assumptions of normal distributions. Due to a difference in the cut-off values in the fasting and non-fasting conditions, we based the statistical between group tests (patient vs. control) on a dichotomously defined zinc deficiency score . Differences in baseline characteristics between patients and controls were analyzed using Chi-square tests (dichotomous data) and independent samples t-tests (continuous data). Differences in the prevalence of zinc deficiency between different patient groups were analyzed with Chi-square tests. The association between zinc deficiency and the sample (patient vs. control) was expressed as an odds ratio (OR) with 95% confidence intervals (CI) from a logistic regression analysis. Differences in zinc levels across different patient groups were tested using one-way analysis of variance. A All patients who were deemed candidates for participation were provided oral and written information about the study. For patients who were unable to provide consent alone due to their medical conditions, their next of kin were provided similar information. Patients and the next of kin (when relevant) provided written consent prior to inclusion in the study. Competency to provide consent was assessed according to previously established guidelines The 100 psychogeriatric patients  included in the present study suffered from a range of disorders, including dementias, psychotic disorder, bipolar disorder, unipolar depressive disorder, and anxiety disorders. We found that 41 patients had a depressive disorder (mean MADRS = 25.3 (7.9)), as a first time depressive episode, recurrent depression or as part of a bipolar disorder. We also identified 20 patients who had depression comorbid with another diagnosis, such as dementia or organic mood disorder (mean MADRS = 19.9 (10.4)). In 39 of the patients, we did not identify any depressive disorders (mean MADRS = 4.9 (3.7)). In this group, 20 patients had dementia (10 cases of Alzheimer's disease), 11 patients had a psychotic disorder, and 8 patients had other non-depressive disorders. The diagnostic distribution in these three groups is presented in 2df = 1 = 44.81, p<0.001). We found a non-significant difference in the prevalence of zinc deficiency between males (47.4%) and females (37.1%) in the patient group. In the control group, the prevalence of zinc deficiency was 18.5% in males and 10.4% in females, which was a significant difference .The prevalence of zinc deficiency in the psychogeriatric patient group was compared to the prevalence in a control group of 882 persons . The median zinc level in the non-fasting patient group (n = 36) was 10.7 µmol/L compared to 12.2 µmol/L in the control group . The median zinc levels in the fasting patient group was 11.2 µmol/L. In the patient group, the prevalence of zinc deficiency was 42.2% in the fasting group and 38.9% in the non-fasting group, which was a not a significant difference.The association between zinc deficiency and the patient or the control group status was further analyzed with logistic regression analyses. Zinc deficiency was associated with depression/comorbid depression and other psychiatric disorders after adjusting for the fasting condition, gender and age . Both agWe identified zinc deficiency in 41.0% of the psychogeriatric patients. The prevalence rates of zinc deficiency and zinc levels in the three main diagnostic groups are presented in The major findings of this study were as follows: 1) There was a significantly higher prevalence of zinc deficiency in the psychogeriatric patients compared with the elderly controls. 2) The prevalence of zinc deficiency was significantly higher in patients without depression compared with patients with depression as the main or comorbid diagnosis. 3) There was no significant relationship between zinc levels and MADRS scores in patients with depression as the main or comorbid diagnosis.We found a high prevalence of zinc deficiency in the patient group compared with the control group. Several studies have demonstrated lower zinc levels in patients with depression than in healthy controls Research in the field of zinc status and psychiatric disorders has primarily focused on depression. Several studies have found a connection between low zinc levels and depression In the present study, the serum zinc levels in patients with depression did not correlate with the MADRS scores. Although the findings might suggest that the magnitude of the serum zinc decline did not reflect the severity of the depression, other explanations for these results are plausible. The present findings correspond to similar results in two other studies To our knowledge, no previous studies have examined zinc deficiency across a broader range of psychiatric disorders among elderly people. The present findings are interesting because they suggest that zinc may play a role in a wide range of psychiatric disorders. Among patients with thyrotoxicosis, some individuals develop anxiety, others develop depression or psychosis, and still others, do not develop psychiatric disorders at all Several hypotheses may explain the relation between depression and zinc deficiency. Zinc can down regulate the glutamate response by inhibiting post-synaptic N-methyl-D-aspartate receptors (NMDA) The present study did not include dietary data for the patient or control groups. Therefore, differences in the dietary intake of zinc might have contributed to the findings. Several studies have supported a connection between low dietary zinc and depression; however, no studies have investigated whether there is an association between low dietary zinc levels and a broader range of psychiatric disorders. A study of Europeans aged 60–84 years found a relationship between low dietary zinc intake, plasma zinc status and depressive symptoms In the present study, the level of albumin was lower in the patient group than in the control group. In a logistic regression model, albumin and gender were significant predictors of zinc deficiency. In a model without albumin, belonging to the patient group was the strongest predictor. The relationship between zinc and albumin is complex. It has been argued that reduced albumin levels only partially explain a reduction in zinc levels A major strength of this study was the inclusion of patients who suffered from different psychiatric disorders and the comparison of these individuals with a large group of controls. The diagnostic procedures that were applied to the patient group were extensive. In addition to diagnostic instruments, clinical observations and data from medical records were used. Another strength of the study was that we controlled for confounding factors, including age, gender, smoking habits, BMI, albumin levels, and whether the patient was living alone or with another individual. These factors have allowed us to make interesting observations regarding the zinc levels in elderly psychiatric patients and in elderly controls.Although we do not believe that zinc supplementation is common among the elderly in our uptake area, we lacked data on zinc supplement intake in the control group. We also lacked data regarding psychiatric symptoms in the control group. However, this group was quite large and unlikely to include a substantial number of persons with severe psychiatric illness. In addition, the blood-sampling time point differed in the two groups. Zinc levels tend to decrease slightly during the day, as reflected in In this study, we found that zinc deficiency is quite common among psychogeriatric patients and appears to be even more prominent in patients without depression. However, the present investigation does not provide a clear answer as to whether the observed differences represent a causal relationship between zinc deficiency and psychiatric symptoms. Although the causes of the differences in zinc deficiency rates are unknown, we propose several possible explanations. Differences in albumin levels may explain a smaller part of the differences in zinc levels. Another factor might be differences in the dietary intake of zinc. Prior studies have suggested potential differences in the dietary intake of zinc between depressed patients and controls. This factor might also apply to patients with other psychiatric disorders compared with controls. Increased levels of inflammatory factors might also contribute to lower levels of zinc in depressed patients; however, it is unknown whether this could also be a factor in patients with other psychiatric disorders. Although there might be different causes of low zinc levels, animal studies